HK40128411A - Method and system for visualizing color gradient of human face or cosmetic skin attributes based on such color gradient - Google Patents

Description

Methods and systems for visualizing color gradients in human facial features or for visualizing cosmetic skin properties based on such color gradients.

Technical Field

The present invention relates to methods and systems for visualizing a person’s skin color gradient or for visualizing skin cosmetic properties based on such skin color gradient, the methods and systems demonstrating an improved match with the person’s skin color or skin condition and/or an improved match with the person’s perception of their skin color or skin condition.

Background Technology

Various digital tools for skin assessment have been developed to meet consumer needs and provide information about their skin properties.

For example, U.S. Publication No. US2020184642A1 (11100639B2) relates to a method for skin examination, and more specifically to a method for performing skin examination based on RBX color space transformation. This U.S. publication discloses a method for detecting skin conditions (particularly the degree of skin redness, more specifically by the intensity of skin redness). In [0058], the U.S. publication discloses the following: “All individuals showed no difference in average red intensity values. However, as shown in Figure 5, the severe rosacea group, moderate rosacea group, mild rosacea group, and normal group were ranked from highest to lowest based on the difference between the average red intensity value and the average green intensity value (i.e., the R-G value).

Another example could be PCT application publication No. WO2019144247A1, which relates to a system and method for assessing and monitoring facial acne from digital photographic images.

Another example is U.S. Publication No. 2010/0284610A1 (“'610 Publication”), which relates to a skin color assessment method for evaluating skin color from an input image including a facial region. '610 Publication describes dividing the facial region of an image into predetermined regions based on a first feature point formed by at least 25 pre-defined regions and a second feature point set using the first feature point. '610 Publication also describes performing skin color distribution assessment by generating a skin color distribution based on an average value using the L*, a*, b*, _Cab * and _hab* color system, the tristimulus values X, Y, Z of the XYZ color system, and at least one of RGB, hue H, lightness V, chroma C, melanin amount, and hemoglobin amount; then performing an assessment based on measured results with respect to the divided regions; and displaying the measured results or assessment results on a screen.

However, the inventors have discovered that measurements obtained using such methods may not match a person's actual skin condition and/or may not match their perception of that condition. Individuals receiving such measurements may not readily accept recommendations for subsequent skincare products to improve their skin condition.

Therefore, there is still a need for a method to visualize a person’s skin color or cosmetic skin attributes, which shows a match between improvements in a person’s skin color or skin condition and/or a match between improvements in a person’s perception of their skin color or skin condition.

Summary of the Invention

This invention relates to a method for visualizing at least one color gradient of a person, the method comprising the following steps:

a) Obtain a first digital image of at least a portion of the person's face, wherein the first digital image is selected from at least one region of an input image of the face;

b) Define multiple tiles across the first digital image obtained;

c) For the at least one color gradient, analyze the first digital image for each of the defined plurality of patches;

d) To uniquely assign a single-degree label to each of the defined plurality of tiles based on at least one color gradient of the tile being analyzed; and

e) Display at least some of the plurality of tiles, each having a uniquely assigned single-degree label, to visualize at least one color gradient;

The at least one color gradient is a gradient calculated on the a* channel image of the first digital image in the L*a*b* chromaticity system.

The present invention also relates to a method for visualizing at least one cosmetic skin attribute of a person, the method comprising the following steps:

a) Obtain a first digital image of at least a portion of the person's face, wherein the first digital image is selected from at least one region of an input image of the face;

b) Define multiple tiles across the first digital image obtained;

c) Based on at least one color gradient, for each of the defined plurality of patches, analyze the first digital image for the at least one cosmetic skin attribute;

d) To uniquely assign a single-degree label to each of the defined plurality of tiles based on at least one cosmetic skin attribute of the tile being analyzed; and

e) Display at least some of the plurality of tiles, each having a uniquely assigned degree label, to visualize at least one cosmetic skin attribute.

This invention relates to a system for visualizing at least one color gradient of a person, the system comprising:

An image acquisition unit is configured to acquire a first digital image of at least a portion of a person's face, wherein the first digital image is selected from at least a region of an input image of the face; wherein preferably, the image acquisition unit includes a non-transitory computer-readable storage medium configured to store the acquired first digital image;

An image processing unit, coupled to the image acquisition unit, is configured to define a plurality of patches across the acquired first digital image, to analyze the first digital image for each of the defined plurality of patches for the at least one color gradient, and to uniquely assign a single-degree label to each of the defined plurality of patches based on the at least one color gradient of the patch being analyzed.

Display generation unit, coupled to the image processing unit, is used for at least some of the plurality of tiles, each having a uniquely assigned single-degree label, to visualize at least one color gradient.

The at least one color gradient is a gradient calculated on the a* channel image of the first digital image in the L*a*b* chromaticity system.

This invention relates to a system for visualizing the cosmetic properties of human skin, the system comprising:

An image acquisition unit is configured to acquire a first digital image of at least a portion of a person's face, wherein the first digital image is selected from at least a region of an input image of the face; wherein preferably, the image acquisition unit includes a non-transitory computer-readable storage medium configured to store the acquired first digital image;

An image processing unit, coupled to the image acquisition unit, is configured to define a plurality of patches across the acquired first digital image, to analyze the first digital image for each of the defined plurality of patches based on at least one color gradient for the at least one cosmetic skin attribute, and to uniquely assign a single-degree label to each of the defined plurality of patches based on the at least one cosmetic skin attribute of the patch being analyzed.

A display generation unit, coupled to the image processing unit, is used to visualize at least some of the plurality of tiles, each having a uniquely assigned single-degree label, for visualizing at least one cosmetic skin attribute.

This invention provides methods and systems for visualizing a person's skin tone gradient or for visualizing skin cosmetic properties based on such skin tone gradient, demonstrating an improved match to the person's skin tone or skin condition and/or an improved match to the person's perception of their skin tone or skin condition. The inventors have surprisingly discovered that, by using color gradients, the methods of this invention can provide an improved match to a person's skin tone or skin condition and/or an improved match to the person's perception of their skin tone or skin condition, particularly an improved match to the person's perception selected from the group consisting of: stressed skin, healthy skin, inflamed skin, latent aging skin, and mixtures thereof. In particular, compared to known digital tools for skin assessment, the methods of this invention provide improved results for the early detection of skin defects, especially for the early detection of skin aging (i.e., latent aging skin). Furthermore, the methods of this invention provide a simple and convenient way to assess cumulative stress (stressed skin) and inflammatory symptoms (inflammatory skin) via image analysis, symptoms previously measured only by bioassays, and stressed skin and/or inflammatory skin may be signals of latent aging skin.

Cosmetic skin properties can be imperceptible, including those that are not visually perceptible, those that are difficult to define clearly (such as stressed skin, healthy skin, and skin with hidden signs of aging), those that cannot be detected by the naked eye, and/or those that are visually perceptible to consumers but which they do not understand. The advantage of identifying imperceptible cosmetic skin properties is that it enables consumers to make informed decisions and take proactive actions to improve their skin condition.

Attached Figure Description

It should be understood that the foregoing general description and the following detailed description depict various embodiments and are intended to provide an overview or framework for understanding the attributes and features of the subject matter protected by the claims. Drawings are included to provide a further understanding of the various embodiments, and these drawings are incorporated in and form part of this specification. The drawings illustrate the various embodiments described herein and, together with the description, serve to explain the principles and operation of the subject matter protected by the claims.

Figure 1 is a diagram illustrating an exemplary system according to the present invention for visualizing color gradients or at least one cosmetic skin attribute via a network;

Figure 2 is a perspective view illustrating an alternative exemplary system for visualizing cosmetic skin properties according to the present invention, particularly the system of Figure 1 configured as an exemplary stand-alone imaging system.

Figure 3 is a block diagram illustrating the components of an exemplary system for visualizing color gradients or cosmetic skin properties according to the present invention;

Figures 4A to 4C are exemplary flowcharts illustrating a series of processes for visualizing color gradients or cosmetic skin properties according to the present invention;

Figure 5 is a flowchart illustrating a method for visualizing color gradients or cosmetic skin properties according to the present invention;

Figures 6A to 6C are exemplary flowcharts illustrating the details of the steps in obtaining a first digital image in a method for visualizing color gradients or cosmetic skin properties according to the present invention;

Figure 7 is a flowchart illustrating, by way of example, the steps of obtaining a first digital image according to the present invention;

Figure 8 is an illustrative image illustrating the steps of defining multiple tiles in a method for visualizing color gradients or cosmetic skin properties according to the present invention;

Figure 9 is a flowchart illustrating, by way of example, the steps of displaying multiple blocks according to the present invention;

Figure 10 is a flowchart illustrating an exemplary process 500 of analyzing image data for each of a defined plurality of tiles according to the present invention.

Figure 11 is an exemplary illustration of displaying multiple tiles according to the present invention, and in particular, an exemplary illustration of a second digital image inserted on a first digital image;

Figure 12 is a flowchart illustrating an exemplary process for displaying multiple blocks according to the present invention;

Figure 13A is an illustrative picture of a first digital image, and Figures 13B and 13C are illustrative pictures of displaying multiple tiles according to the present invention, and in particular, illustrative pictures of a second digital image inserted on the first digital image.

Figure 14 is a flowchart illustrating an exemplary method for visualizing at least one cosmetic skin property according to the present invention;

Detailed Implementation

Before describing the invention in detail, the following terms are defined, and any undefined terms shall be given their ordinary meanings as understood by one of skill in the art.

As used herein, “cosmetic skin properties” include all skin properties that provide visual/aesthetic effects on a region of the body or affect the appearance and/or feel of the skin. Some non-limiting examples of cosmetic skin properties may include skin shape, skin elasticity, skin tone, skin pigmentation, skin texture, skin pores, cosmetic skin inflammation, skin hydration, skin sebum levels, acne, moles, skin luminosity, skin shine, dullness, uneven skin tone, or skin barrier. Technical personnel should understand that the above cosmetic skin attributes are standard terms, and their corresponding definitions can be found in the following published references: "Handbook of cosmetic science and technology, ^3rd edition, editors Andre O. Barel, Marc Paye, Howard I. Maiback, CRC Press, 2009";"Cosmetic Science and Technology - Theoretical Principles and Applications, editors Kazutami Sakamoto, Robert Y. Lochhead, Howard I. Maibach, Yuji Yamashita, Elsavier, 2017";"Cosmetic Dermatology: Products and Procedures, editor: Zoe Diana". Draelos, Blackwell Publishing Ltd, 2010 (Cosmetic Dermatology: Products and Procedures, Editor(s): Zoe Diana Draelos, Blackwell Publishing Ltd, 2010). Cosmetic skin attributes do not include skin attributes related to medical conditions or underlying medical conditions. Cosmetic skin attributes are preferably selected from the group consisting of: stressed skin, healthy skin, inflamed skin, latent aging skin, skin age, skin morphology, skin tone, skin pigmentation, skin pores, skin hydration, skin sebum level, acne, moles, skin luminosity, skin radiance, skin dullness and skin barrier, prediction of future cosmetic skin attributes, and combinations thereof. Cosmetic skin attributes are more preferably selected from the group consisting of: stressed skin, healthy skin, inflamed skin, latent aging skin, skin age, skin morphology, skin tone, skin pigmentation, skin hydration, skin sebum level, moles, skin luminosity, skin radiance, skin dullness and skin barrier, prediction of future cosmetic skin attributes, and combinations thereof. The skin type for beauty purposes is more preferably selected from the following groups: stressed skin, healthy skin, inflamed skin, skin with hidden signs of aging, and a combination thereof.

The term "tile" as used in this article includes units that form parts of a digital image, such as pixels, and thus "tiles" form the entire digital image.

As used herein, “digital image data” includes image data acquired from an image acquiring device, including (but not limited to) a digital camera, a photo scanner, a computer-readable storage medium capable of storing digital images, and any electronic device that includes the ability to take pictures. Digital image data may also include color channel images converted from RGB images to color channel images in a color system.

The term “single degree mark” as used in this article includes all electronic visual representations, including (but not limited to) graphic symbols, numerical values, color codes, lighting techniques, and combinations thereof.

As used in this article, “L*a*b*” refers to the universally accepted color space designated by the International Commission on Illumination (“CIE”). The three coordinates represent (i) the lightness of the color (i.e., L*=0 produces black and L*=100 indicates diffuse white); (ii) the position of the color between magenta and green (i.e., negative a* values indicate green and positive a* values indicate magenta); and (iii) the position of the color between yellow and blue (i.e., negative b* values indicate blue and positive b* values indicate yellow).

As used herein, “skin age” refers to apparent age, which is the age of a person’s skin as visually estimated or perceived based on physical appearance, preferably based on a person’s face, more preferably based on at least a portion of a person’s face, more preferably based on at least a region of interest (ROI) of at least a portion of a person’s face, compared to the appearance of skin of standard age. More preferably, the at least one ROI is selected from the group consisting of: the skin area around the eyes (“eye area”), the skin area around the cheeks (“cheek area”), the skin area around the mouth (“mouth area”), and combinations thereof, and even more preferably the skin area around the cheeks (“cheek area”).

The term "skin tone" as used in this article generally refers to the overall appearance of base skin tone or color uniformity. Skin tone is typically characterized over a large area of skin. This area can be more than 100 ^mm² , but larger areas can be envisioned, such as the entire facial skin or other human skin surfaces (e.g., arms, legs, back, hands, neck).

As used in this article, “skin wrinkles” generally refers to folds, ridges, or creases in the skin, and includes (but is not limited to) fine lines, ultra-fine lines, fine wrinkles, ultra-fine wrinkles, wrinkles, and fine lines. Skin wrinkles can be measured in terms of density and/or length, for example.

The term "skin luminosity" used in this article generally refers to the amount of light reflected by the skin, and can also be called skin luster.

The term "skin texture" as used in this article generally refers to the shape or roughness of the skin surface.

The term "skin tension" as used in this article usually refers to the firmness or elasticity of the skin.

The term "skin sebum level" as used in this article generally refers to the amount of sebum, an oily or waxy substance secreted by the sebaceous glands in the skin.

As used in this article, "skin spots" generally refers to discoloration or uneven pigmentation of the skin (e.g., hyperpigmentation, spots). Skin spots can be assessed based on factors such as the density, size, and/or extent of discoloration.

The term "skin care products" as used in this article refers to products that contain active skin care ingredients and regulate and/or improve skin condition.

As used herein, "digital image" refers to a digital image formed by pixels in an imaging system (including (but not limited to) standard RGB, etc.) and acquired under different lighting conditions and/or modes. Non-limiting examples of digital images include color images (RGB), monochrome images, video, multispectral images, hyperspectral images, etc. Non-limiting lighting conditions include white light, blue light, UV light, IR light, light at a specific wavelength, such as light sources emitting, for example, 100 nm to 1000 nm, 300 nm to 700 nm, 400 nm to 700 nm, or different combinations of the upper and lower limits above, or any combination of integers within the ranges listed above. The digital image can be acquired from an image acquiring device, including (but not limited to) a digital camera, a photo scanner, a computer-readable storage medium capable of storing digital images, and any electronic device including image capturing capabilities.

In the following description, the systems, methods, and apparatus described are systems, methods, and apparatus for visualizing the color gradient of a human face or for visualizing cosmetic skin properties based on the color gradient.

In one exemplary embodiment, the system is a standalone imaging system (shown in Figure 2) located at a retail cosmetics counter for analyzing and/or recommending beauty and skincare products based on visualized color gradients and/or visualized cosmetic skin properties. However, it is conceivable that the system and method could be configured for use anywhere via a portable electronic device including an image acquisition unit and a display, such as, for example, as shown in Figure 1, where the portable electronic device is networked to a device for generating a graphical user interface for visualizing color gradients or cosmetic skin properties for display on a display.

system

Figure 1 is a schematic diagram illustrating an exemplary system 10 for visualizing color gradients or cosmetic skin properties according to the present invention. System 10 may include a network 100, which may be embodied as a wide area network (such as a mobile phone network, public switched telephone network, satellite network, Internet, etc.), a local area network (such as wireless fidelity, Wi-Max, ZigBee ^™ , Bluetooth ^™ , etc.), and/or other forms of networking capabilities. A portable electronic device 12 and a device 14 for generating a graphical user interface for visualizing color gradients or cosmetic skin properties for display on a display are coupled to the network 100. Device 104 is remotely located and connected to the portable electronic device via the network 100.

Portable electronic device 12 may be a mobile phone, tablet computer, laptop computer, personal digital assistant, and/or other computing device configured to capture, store, and/or transmit digital images such as digital photographs. Therefore, portable electronic device 12 may include an input device 12a for receiving user input, an image acquisition device 18 for acquiring an image, such as a digital camera, and an output device 12b for displaying the image. Portable electronic device 12 may also be configured to communicate with other computing devices via network 100. Portable electronic device 12 may also include an image processing device (not shown) coupled to the image acquisition device 18 for analyzing the acquired first digital image to obtain color gradient values or, based on the color gradient values, to obtain cosmetic skin properties. The image processing device preferably includes a processor having computer-executable instructions. Portable electronic device 12 may also include a display generation unit (not shown, such as an electronic LED/LCD display) for generating a display to visualize the color gradient or cosmetic skin properties.

Device 14 may include a non-transitory computer-readable storage medium 14a (hereinafter referred to as the "storage medium") that stores image acquisition logic 144a, image analysis logic 144a, and graphical user interface (hereinafter referred to as the "GUI") logic 144c. Storage medium 14a may include random access memory (such as SRAM, DRAM, etc.), read-only memory (ROM), registers, and/or other forms of computational storage hardware. Image acquisition logic 144a, image analysis logic 144b, and GUI logic 144c define computer-executable instructions. Processor 14b is coupled to storage medium 14a, wherein processor 14b is configured to implement, based on computer-executable instructions, the method 200 according to the invention for visualizing color gradients or cosmetic skin properties, as described below with respect to the process flowcharts of Figures 4A to 4C and the flowchart of Figure 5.

method

Referring to Figures 4A and 5, when processor 14b is activated, processor 14b causes, in step 202, to acquire, for example, a first digital image 51 of at least a portion of the subject's face via image acquisition logic 144a. Processor 14b defines a plurality of patches 54 across the acquired image data 20 (step 204). The plurality of patches 54 may be adjacent to define a patch diagram 55, as shown in Figure 4B. In step 206, the processor analyzes the image data for each image data of each patch among the defined plurality of patches 54, for a color gradient or at least one cosmetic skin attribute. In step 208, a single-degree label 40 is uniquely assigned to each patch 54 among the defined plurality of patches based on the analyzed color gradient or the analyzed cosmetic skin attribute. In step 210, at least some of the patches, each with a uniquely assigned single-degree label, are displayed to visualize the color gradient or cosmetic skin attribute, as shown in Figure 4C. By analyzing image data from input digital images provided by users (consumers), and organizing and displaying the analyzed image data for each of a defined plurality of tiles in a single screenshot, the method 200 according to the invention allows users/consumers to easily identify cosmetic skin properties while avoiding the cumbersome task of navigating through user interfaces displaying information in separate windows under different lighting systems required to visualize cosmetic skin properties.

In one exemplary embodiment, a second digital image, with each tile having a uniquely assigned single-degree marker, may be inserted into the first digital image 51. It should be understood that the size of the tile 54 can be defined by the number of pixels on the horizontal side (tile width, W) and the number of pixels on the vertical side (tile height, H). In the exemplary method according to the invention, each tile may include the following tile sizes: no greater than 100 x 100 pixels, 1 x 1 pixel to 100 x 100 pixels, 2 x 2 pixels to 100 x 100 pixels, 5 x 5 pixels to 90 x 90 pixels, 40 x 40 pixels to 70 x 70 pixels, or different combinations of the above upper and lower limits or any combination of integers within the ranges listed above. Alternatively or concurrently, the area of a tile may form about 1% to about 20% of the ROI area, preferably about 1% to about 10%, more preferably about 1% to about 5%. The technical effect of tile sizes within the above ranges is that they are capable of extracting meaningful information that matches a person's skin color or skin condition and/or a person's perception of their skin color or skin condition.

Referring to FIG1, a digital image can be acquired from a portable electronic device 12 using network 100 and transmitted to device 14 for use in the method 200 according to the invention. An input device 12a may be coupled to or integrated with the portable electronic device 12 for receiving user input for activating processor 14b. The portable electronic device 12 may include an output device 12b for displaying multiple tiles, each tile having a uniquely assigned single-degree marker. The input device 12a may include (but is not limited to) a mouse, a touchscreen display, etc. The output device 12b may include, but is not limited to, a touchscreen display, a non-touchscreen display, a printer, a projector for projecting a facial image FIG30 onto a display surface such as a mirror, as described below with respect to FIG2.

Figure 2 is a perspective view of system 10 configured as an exemplary standalone imaging system located at a retail cosmetics counter for visualizing color gradients and/or at least one cosmetic skin attribute, and can also be used to recommend beauty and skin care products based on the visualized color gradients and/or at least one cosmetic skin attribute. Figure 3 is a block diagram of the exemplary system 10 of Figure 2. Referring to Figures 2 and 3, system 10 includes a housing 11 for device 14 of Figure 1, which is connected to an image acquisition device 18 for acquiring digital images of a subject to visualize at least one cosmetic skin attribute. Referring to Figure 2, system 10 may include a mirror 16, and the image acquisition device 18 may be mounted within housing 11 behind mirror 16 such that the image acquisition device 18 is hidden from view. The image acquisition device 18 may be a digital camera, an analog camera connected to digital circuitry, a scanner, a video camera, etc. System 10 may include lamps 30, such as LED lights, arranged around housing 11 to form an LED lighting system for assisting in the generation of digital images of a subject. System 10 has an input device 112a for receiving user input. System 10 may also include an output device 112b, such as a projector, configured to receive and project the facial image 30 onto the mirror 16 for display. The projector is not shown in Figure 2 because it may be separate from the housing 11 but coupled to the device 14 to form a peripheral component of system 10. System 10 may also include a second output device 112c, such as one or more speakers, optionally coupled to an amplifier to generate audio guidance outputs to supplement and/or enhance the overall consumer experience.

To illustrate the manner in which system 10 and method 200 visualize color gradients or at least one cosmetic skin attribute according to the present invention, it is helpful to understand the following operations: how a digital image of the subject's face is obtained in step 202, how tiles are defined in step 204, how image data is analyzed in step 206, how a unique single-degree label is assigned to each tile in step 208, and how the tiles are displayed in step 210. Therefore, steps 202, 204, 206, 208, and 210 of method 200 according to the present invention are described below as separate processes for performing each step. Each process can also be described as a subroutine, i.e., a series of program instructions that execute the corresponding step according to method 200 according to the present invention.

Obtaining digital images

The steps 202 of obtaining a digital image according to the method 200 of the present invention are described with reference to Figures 6A, 6B and 6C, which are a series of process flowcharts illustrating how to obtain a first digital image, and Figure 7 is a flowchart of an exemplary process 300 for obtaining a digital image corresponding to step 202.

Figure 6A illustrates an input image 50a of face 1. The input image 50a can be captured by a user, for example, using camera 18 in step 302 of process 300 as shown in Figure 7. Figure 6B illustrates step 304 of cropping the input image 50a to obtain edited image data 50b including at least a portion of the face. The input image 50a can be cropped by identifying anchor features 1a of the face, including (but not limited to) facial features such as eyes, nose, nostrils, corners of the mouth, etc.; and cropping accordingly. While eyes are depicted as anchor features 1a in Figure 6B, it should be understood that this is merely an example, and any prominent or detectable facial feature can be an anchor feature. The edited image data 50b can be the first digital image 51 obtained in step 308. Alternatively, as shown in Figure 6C, the edited image data 50b can be further processed by cropping to remove one or more unwanted portions of the input image 50a, thereby obtaining a first digital image 51 in step 308 including at least a portion of face 1 defined by boundary line 52. Preferably, the first digital image is a cross-polarized image. The obtained first digital image 51 may include at least one region of interest (ROI) 2 of at least a portion of the face 1 defined by a boundary line 52. The ROI 2 may be the entire portion of the face 1, preferably at least a portion of the face, and more preferably one or more skin regions defining at least a portion of the face 1.

Optionally, process 300 may include step 306, wherein ROI 2 may be selected from the skin area around the cheek (“cheek area 2b”), preferably ROI 2 is a portion of at least a part of the subject’s face 1, more preferably, the obtained first digital image defines the left or right side of the face 1. ROI 2 may include at least 5%, 10% to 100%, or 25% to 90% of the obtained first digital image.

Limited tiles

Figure 8 is an illustration of a plurality of patches 54 on the first digital image data 51. Figure 9 is a flowchart illustrating a process 400 defining the plurality of patches 54 on the first digital image data 51. Referring to Figure 8, the first digital image data 51 includes at least a portion of a face 1 defined by a boundary line 52, as described above with reference to Figure 6C. Process 400 includes defining an outer perimeter 53 that surrounds the boundary line 52 surrounding the obtained first digital image (step 402). The obtained first digital image 51 is formed by a total number of pixels; for example, the obtained first digital image 51 may have the number of pixels determined at step 304 or step 306, depending on the image size after cropping the input image 50a. Therefore, the total image size based on the obtained first digital image 51 can be defined in step 404. For example, if the tile size is set to 40 x 40 pixels to 70 x 70 pixels, the number of tiles 54 forming a plurality of tiles 54 across the obtained first digital image 51 in step 406 will be obtained by dividing the total image size by the specified tile size. Alternatively or concurrently, the area of a tile may form about 1% to about 20% of the ROI area, preferably about 1% to about 10%, more preferably about 1% to about 5%.

Analyze image data

Figure 10 is a flowchart illustrating a process 500 according to the present invention for analyzing image data for each of a defined plurality of tiles. The process 500 may begin at step 502, wherein at least one color channel is extracted from the obtained first digital image to provide an image of the extracted color channels for analysis to obtain color gradient values, or for analysis to determine cosmetic skin properties based on the color gradient.

In the following description, at least one color channel image is an image in the L*a*b* color system selected from the group consisting of: L-channel images, a-channel images, b-channel images, and combinations thereof, preferably a-channel images, b-channel images, and mixtures thereof, more preferably a-channel images. However, it should be understood that at least one color channel may also be a chromophore system, and at least one color channel may be a melanin channel or a hemoglobin channel. The color system may also be the HSL/HSV color system and the CMYK color system.

Preferably, at least one color gradient is selected from the group consisting of: a gradient calculated on the a* channel image (red channel image) of the first digital image in the L*a*b* chromaticity system; and a gradient calculated on the b* channel image (yellow channel image) of the first digital image in the L*a*b* chromaticity system; and a mixture thereof. More preferably, at least one color gradient is selected from the group consisting of: a gradient calculated on the a* channel image (red channel image) of the first digital image in the L*a*b* chromaticity system.

The extracted color channels can be filtered in step 504, and the filtered color channels can be analyzed for color gradients or cosmetic skin properties. It should be understood that other descriptive statistical data (including but not limited to standard deviation, mean, etc.) can also be used to analyze the filtered color channels. The technical effect of using the color gradient according to the present invention is that it has a higher correlation with a person's skin color or skin condition and/or a person's perception of their skin color or skin condition.

Preferably, filtering the first digital image (more specifically, the color channel image) using a smoothing filter (preferably a Gaussian filter and/or a frequency filter, more preferably a difference-of-Gaussian (DoG) filter in the frequency filter) helps to eliminate noise introduced during image capture. In particular, the frequency filter helps to evaluate the spatial patterns of color and shape features separately. Optionally, method 200 may also include applying an image correction factor to the filtered color channels before analyzing them.

In step 506, cosmetic skin properties of at least a portion of the human skin are determined based on gradient values.

Preferably, at least one color gradient is obtained through the following steps:

1) Calculate the average intensity value of a specific color for each tile.

2) Calculate the gradient value of a tile by calculating the gradient of the average intensity value between adjacent tiles using the following equation:

Where I _{_i,j} is the average intensity value of the patch at position (i, j) calculated in step (1) above, I _{_i+1,j} is the average intensity value of the patch at position (i+1, j) calculated in step (1) above, and I _{_i,j+1} is the average intensity value of the patch at position (i, j+1) calculated in step (1) above.

Therefore, |I _i,j – I _{i+1, j} | can represent the gradient along the x-axis, and |I _i,j – I _{i, j+1} | can represent the gradient along the y-axis.

Table 1 below lists each gradient value, based on which the corresponding color channel image and preferred cosmetic skin properties will be determined. The color channel images described in Table 1 are images selected from the group consisting of the following in the L*a*b* color system: L-channel image, a-channel image, b-channel image, c-channel image, and combinations thereof.

Table 1

Color channel images gradient value To determine the preferred cosmetic skin properties a-channel image a-gradient value Stressed skin, healthy skin, inflamed skin, and skin with hidden signs of aging. b-channel image b-gradient value Skin pigmentation, dull skin L-channel image L-gradient value Skin tone, dull skin, and enlarged skin pores

Preferably, the color channel image is an a-channel image, the gradient value is an a-gradient, and the preferred cosmetic skin attribute to be determined is selected from the group consisting of: stressed skin, healthy skin, inflamed skin, and skin with latent aging.

Preferably, the cosmetic skin attribute is generated as a value indicating the cosmetic skin attribute of at least a portion of a person's skin relative to the condition of a defined population. Specifically, in visual perception research, consumers may be asked to rank digital images (e.g., photographs) of a defined population based on cosmetic skin attributes on a predetermined scale. The ranked digital images may be stored in a database for analysis according to method 500.

More preferably, the cosmetic skin attribute is generated as a function of the gradient values of at least one image, defined by F (gradient value), wherein the function is determined by a model built on a training dataset, wherein the training dataset includes: (i) multiple color channel images defining a population, wherein each of the multiple color channel images includes facial skin of a person within the defined population; and (ii) an associated category definition based on the cosmetic skin attribute. More preferably, the cosmetic skin attribute is generated as a function of the gradient value combined with the base skin color defined by F (gradient value, base skin color) at the patch.

Preferably, the age of the subjects and the average age of the limited population can each be independently between 18 and 60 years old, preferably between 20 and 40 years old, more preferably between 25 and 35 years old, and even more preferably between 28 and 32 years old.

Techniques for constructing training datasets are known to those skilled in the art of image processing methods and will not be described further.

The model is a regression model or a classification model; wherein the model is preferably a classification model, more preferably a machine learning classification model, and most preferably a machine learning random forest classification model or a gradient boosting classification model.

The use of machine learning models achieves the following advantages: accuracy, reproducibility, and speed in execution when the method is implemented as a native application on a portable electronic device. Specifically, the model's weights allow for a smaller hardware footprint in the native application, and therefore the method according to the invention can be easily deployed in portable electronic devices such as mobile phones with a mobile phone operating system (OS), including (but not limited to) iOS for Apple ^™ phones or Android OS for Android phones.

A classification model can be used to categorize consumers into multiple groups, each group having different degrees of the same cosmetic skin attribute condition. Preferably, consumers are categorized into two groups to define the associated category based on a visual rating of the cosmetic skin attribute or any other numerical value. For example, the method can display a heatmap configured to classify skin into high-level or low-level cosmetic skin attribute conditions based on a threshold assigned to each group within that group.

The following data is based on correlations with results from a visual perception study that used statistical analysis employing the Pearson correlation coefficient (r). The correlation results are shown in Table 2 below.

Table 2

A higher Pearson correlation coefficient (r) means that the gradient value is a greater factor influencing the condition of the cosmetic skin attribute studied in the visual perception study. Specifically, the visual perception study was conducted based on a predetermined number of panel members = 577 and the age of the panel members = 20-50. The panel members were required to grade each cosmetic attribute (such as stressed skin (as an example of a cosmetic skin attribute)) on a scale of 1 to 6.

Based on the results of visual perception research and the aforementioned correlation results, it has been found that the α-gradient value of the filtered image (passed through a frequency filter) has a higher correlation with the aforementioned cosmetic skin attributes. Therefore, using the α-gradient value to determine the cosmetic skin attributes of at least a portion of human skin in a digital image can be used to transform visually imperceptible cosmetic skin attributes into cosmetic skin attributes that can be explained to consumers in a consumer-relevant manner.

The inventors have discovered that the α-gradient also indicates vascular status. For example, a lower α-gradient indicates a normal vascular status; a moderate α-gradient indicates more vascular dilation (temporal region), which is a signal of temporal inflammation; and a higher α-gradient indicates more vascular dilation (temporal region) and more vascular development (chronic), which is a signal of chronic inflammation.

Referring to Figure 10, analyzing image data may include analyzing at least two color channels, specifically the red channel and the yellow channel. In this case, at least one color gradient is the gradient calculated in the L*a*b* chromaticity system on the a* channel image (red channel image) of the first digital image and the gradient calculated in the L*a*b* chromaticity system on the b* channel image (yellow channel image) of the first digital image.

show

The method according to the invention further includes the step of displaying at least some of a plurality of tiles, each having a uniquely assigned single-degree label, to visualize at least one color gradient or, based on that color gradient, to visualize cosmetic skin properties. Such visualization of the color gradient value or cosmetic skin property may be a heatmap (such as those shown in Figures 13B and 13C).

Figure 11 is an illustration of a second digital image 60 inserted on a first digital image 51. The second digital image 60 includes at least a portion of the subject's face with a plurality of displayed patches 54, each patch having a uniquely assigned mono-degree marker 40.

Figure 12 is a flowchart illustrating a process 600 for displaying multiple tiles according to the present invention. Process 600 may begin at step 602, where the processor reads the analyzed image data of each tile 54 and uniquely assigns a single-degree marker to each of the multiple tiles 54 based on the analyzed color gradient or analyzed cosmetic skin attributes of the tile 54 (step 604). When the single-degree marker is illumination, the analyzed image data of each tile in the tile may be transformed in step 606 to reflect the brightness of the corresponding level of illumination at each tile. In an exemplary example, a tile with a higher level of illumination has a higher color gradient value but a worse condition in at least one cosmetic skin attribute, relative to a tile with a lower level of illumination but a better condition in at least one cosmetic skin attribute. Specifically, method 200 may further include displaying at least one product recommendation item to process the displayed color gradient or cosmetic skin attribute.

Figure 14 is a flowchart illustrating a method 700 for visualizing color gradients or at least one cosmetic skin attribute according to the present invention. Figure 13A is a color image illustrating a first digital image of at least a portion of a subject's face shown in step 702 of the method 700 of Figure 14. Figures 13B and 13C are color images illustrating a second digital image of at least a portion of a subject's face and multiple patches, each having a uniquely assigned single-degree label, wherein in step 704, the second digital image is interpolated onto the first digital image. Figure 13B is an example of visualization of color gradients according to the present invention. In Figure 13B, lighter patches correspond to higher color gradient values (poorer skin condition), and darker patches correspond to lower color gradient values (better skin condition). Figure 13C is an example of visualization of cosmetic skin attributes based on color gradients according to the present invention, particularly inflammatory skin and/or latent aging skin, which can also be a prediction of skin pigmentation, such as the location of spots/melanin localization. In Figure 13C, lighter patches correspond to poorer skin condition, while darker patches correspond to better skin condition. Compared to other visualizations such as a* average and spots, these visualizations of color gradients or cosmetic skin properties of the present invention provide an improved match with a person’s skin tone or skin condition and/or an improved match with a person’s perception of their skin tone or skin condition.

Human-computer interface

This invention may include a human-computer interface (hereinafter referred to as the "user interface") for providing product recommendations based on color gradients or cosmetic skin attributes, or for processing cosmetic skin attributes. The user interface may be a graphical user interface on a portable electronic device including a touchscreen display/display with input devices and image acquisition devices. The user interface may include a first area of the touchscreen display displaying a first digital image of at least a portion of a subject's face acquired from the image acquisition device and a second digital image interpolated on the first digital image, the second digital image having at least a portion of the subject's face and a plurality of tiles of the display, each having a uniquely assigned single-degree label. The user interface may also include a second area of the touchscreen display, distinct from the first area, displaying selectable icons for receiving user input, wherein if the user activates the selectable icon, an image of at least one product recommendation item for processing the displayed cosmetic skin attribute is displayed on the touchscreen display.

The method for determining cosmetic skin condition according to the invention described above may further include, for example, the step of creating a cosmetic skin attribute diary by generating a calendar or timetable to track improvements in cosmetic skin attributes over a predetermined period of time. For example, when a consumer uses the method on day 1, the date and facial analysis are recorded and stored in memory. Subsequently, whenever the consumer uses the method according to the invention in the future (after a predetermined period, 1 week, 1 month, 6 months), the consumer's facial skin is analyzed again, and the consumer can compare how his/her facial skin looks at that time relative to the predetermined period from day 1. The method according to the invention can be configured as: a downloadable software application stored as a native application on a portable electronic device; or a web application accessible through a consumer-specific login account, allowing the consumer to perform self-skin analysis based on the method according to the invention and to view and/or monitor improvements (a reduction in the ROI of poor cosmetic skin condition) over a period of time.

The user interface 930 may also include a second selectable icon 942, which, when selected, enables the repeatability of the method for determining cosmetic skin properties according to the present invention. For example, the method 500 described above can be repeated.

combination

Representative embodiments of the present disclosure described above may be described as follows:

1. A method for visualizing at least one color gradient of a person, the method comprising the following steps:

a. Obtaining a first digital image of at least a portion of the face of the person, wherein the first digital image is selected from at least one region of an input image of the face;

b. Define multiple tiles across the first acquired digital image;

c. For the at least one color gradient, analyze the first digital image for each of the defined plurality of patches;

d. To uniquely assign a single-degree label to each of the defined plurality of tiles based on at least one color gradient of the analyzed tile; and

e. Display at least some of the plurality of tiles, each having a uniquely assigned single-degree label, to visualize at least one color gradient;

The at least one color gradient is a gradient calculated on the a* channel image of the first digital image in the L*a*b* chromaticity system.

2. A method for visualizing at least one cosmetic skin attribute of a person, the method comprising the following steps:

a. Obtaining a first digital image of at least a portion of the face of the person, wherein the first digital image is selected from at least one region of an input image of the face;

b. Define multiple tiles across the first acquired digital image;

c. Based on at least one color gradient, for each of the defined plurality of patches, analyze the first digital image for each of the at least one cosmetic skin attribute;

d. To uniquely assign a single-degree label to each of the defined plurality of tiles based on at least one cosmetic skin attribute of the tile being analyzed; and

e. Display at least some of the plurality of tiles, each having a uniquely assigned degree label, to visualize at least one cosmetic skin attribute.

3. The method according to feature 2 above, wherein the at least one color gradient is a gradient calculated on the a* channel image of the first digital image in the L*a*b* chromaticity system.

4. The method according to any one of the foregoing features, wherein, prior to step (c), the first digital image is filtered by using a smoothing filter and/or a frequency filter.

5. The method according to any one of the foregoing features, wherein the first digital image is a cross-polarized image.

6. The method according to any one of the foregoing features, wherein the at least one color gradient is obtained by the following steps:

1) Calculate the average intensity value of a specific color for each tile.

2) The gradient value of a tile is obtained by calculating the gradient of the average intensity value between adjacent tiles using the following equation:

Where I _{_i,j} is the average intensity value of the patch at position (i, j) calculated in step (1) above, I _{_i+1,j} is the average intensity value of the patch at position (i+1, j) calculated in step (1) above, and I _{_i,j+1} is the average intensity value of the patch at position (i, j+1) calculated in step (1) above.

7. The method according to feature 2 above, wherein the cosmetic skin attribute is selected from the group consisting of: skin age, skin morphology, skin tone, skin pigmentation, skin pores, skin inflammation, skin hydration, skin sebum level, acne, moles, skin luminosity, skin radiance, skin dullness and skin barrier, prediction of future cosmetic skin attributes, and combinations thereof.

8. The method according to feature 7 above, wherein the cosmetic skin attribute is generated as a value indicating the condition of at least a portion of the skin of the person relative to a defined population, and is generated as a function of the gradient values of at least one color channel image defined by F (gradient value), wherein the function is determined by a model built on a training dataset, wherein the training dataset includes: (i) multiple color channel images of the defined population, wherein each of the multiple color channel images includes facial skin of a person in the defined population; and (ii) an associated category definition based on the cosmetic skin attribute.

9. The method according to feature 8 above, wherein the cosmetic skin attribute is generated as a function of the gradient value combined with the base skin color defined by F(gradient value, base skin color) at the patch.

10. The method according to any one of features 8 to 9 above, wherein the at least one color channel image comprises an a-channel image; wherein the gradient value is an a-gradient value.

11. The method according to any one of the foregoing features 8 to 10, wherein the model is a regression model or a classification model; wherein the model is preferably a classification model, more preferably a machine learning classification model, and most preferably a machine learning random forest classification model or a gradient boosting classification model.

12. The method according to the foregoing features, wherein the first digital image obtained includes at least one region of interest (ROI) of at least a portion of the subject’s face, wherein the at least one ROI is a skin area around the cheek (“cheek area”).

13. The method according to the foregoing features, wherein defining multiple tiles across the obtained first digital image is defining multiple tiles across the region of interest, wherein the area of each tile is about 1% to 20% of the area of the ROI.

14. The method according to the foregoing features, wherein defining multiple tiles across the obtained first digital image is defining multiple tiles across the region of interest, wherein the area of each tile is about 1% to about 10% of the area of the ROI.

15. The method according to the foregoing features, wherein defining multiple tiles across the obtained first digital image is defining multiple tiles across the region of interest, wherein the area of each tile is about 1% to about 5% of the area of the ROI.

16. The method according to the foregoing features, the method further comprising the step of displaying a comparison between a degree marker of each of the defined plurality of tiles and a predetermined value associated with a defined population.

17. The method according to the foregoing features, wherein the display in step (e) comprises a second digital image inserted into at least a portion of the subject’s face and a plurality of tiles of the display, each having a uniquely assigned single-degree marker.

18. The method according to the aforementioned features, wherein the single-degree mark is selected from the group consisting of: graphic symbols, numerical values, color codes, illumination, and combinations thereof.

19. The method according to the foregoing features, the method further comprising displaying at least one product recommendation item to process at least one displayed color gradient or displayed cosmetic skin attributes.

20. A system for visualizing at least one color gradient of a person, the system comprising:

An image acquisition unit is configured to acquire a first digital image of at least a portion of the face of the person, wherein the first digital image is selected from at least a region of an input image of the face; wherein preferably, the image acquisition unit includes a non-transitory computer-readable storage medium configured to store the acquired first digital image;

An image processing unit, coupled to the image acquisition unit, is configured to define a plurality of patches across the acquired first digital image, to analyze the first digital image for each of the defined plurality of patches for the at least one color gradient, and to uniquely assign a single-degree label to each of the defined plurality of patches based on the at least one color gradient of the patch being analyzed.

The display generation unit, coupled to the image processing unit, is used to visualize at least some of the plurality of tiles, each having a uniquely assigned single-degree label, for visualizing at least one color gradient.

The at least one color gradient is a gradient calculated on the a* channel image of the first digital image in the L*a*b* chromaticity system.

21. A system for visualizing cosmetic skin properties of a person, the system comprising:

An image acquisition unit is configured to acquire a first digital image of at least a portion of the face of the person, wherein the first digital image is selected from at least a region of an input image of the face; wherein preferably, the image acquisition unit includes a non-transitory computer-readable storage medium configured to store the acquired first digital image;

An image processing unit, coupled to the image acquisition unit, is configured to define a plurality of patches across the acquired first digital image, to analyze the first digital image for each of the defined plurality of patches based on at least one color gradient for the at least one cosmetic skin attribute, and to uniquely assign a single-degree label to each of the defined plurality of patches based on the at least one cosmetic skin attribute of the patch being analyzed.

A display generation unit, coupled to the image processing unit, is used to visualize at least some of the plurality of tiles, each having a uniquely assigned single-degree label, for visualizing at least one cosmetic skin attribute.

Unless expressly excluded or otherwise limited, every reference cited herein, including any cross-references or related patents or patent applications, and any patent application or patent claiming priority to or benefiting from it, is incorporated herein by reference in its entirety. A reference to any document is not an admission that it is prior art concerning any invention disclosed or claimed herein, nor is it an admission that it, alone or in any combination with any other reference, teaches, suggests, or discloses any such invention. Furthermore, where any meaning or definition of a term in this invention conflicts with any meaning or definition of the same term in a referenced document, the meaning or definition given to that term in this invention shall prevail.

While specific embodiments of the invention have been illustrated and described, it will be apparent to those skilled in the art that various other changes and modifications can be made without departing from the spirit and scope of the invention. Therefore, it is intended that all such changes and modifications falling within the scope of the invention be covered by the appended claims.

Claims (14)

1. A method for visualizing at least one color gradient of a person, the method comprising the following steps: a) Obtain a first digital image of at least a portion of the face of the person, wherein the first digital image is selected from at least one region of an input image of the face; b) Define multiple tiles across the first digital image obtained; c) For the at least one color gradient, analyze the first digital image for each of the defined plurality of patches; d) To uniquely assign a single-degree label to each of the defined plurality of tiles based on at least one color gradient of the analyzed tile; and e) Display at least some of the plurality of tiles, each having a uniquely assigned single-degree label, to visualize at least one color gradient; The at least one color gradient is a gradient calculated on the a* channel image of the first digital image in the L*a*b* chromaticity system. 2. A method for visualizing at least one cosmetic skin attribute of a person, the method comprising the following steps: a) Obtain a first digital image of at least a portion of the face of the person, wherein the first digital image is selected from at least one region of an input image of the face; b) Define multiple tiles across the first digital image obtained; c) Based on at least one color gradient, for the at least one cosmetic skin attribute, analyze the first digital image for each of the defined plurality of patches, preferably wherein the at least one color gradient is a gradient calculated on the a* channel image of the first digital image in the L*a*b* chromaticity system. d) To uniquely assign a single-degree label to each of the defined plurality of tiles based on at least one cosmetic skin attribute of the tile being analyzed; and e) Display at least some of the plurality of tiles, each having a uniquely assigned single-degree label, to visualize at least one cosmetic skin attribute; Preferably, the cosmetic skin attribute is selected from the group consisting of: skin age, skin morphology, skin tone, skin pigmentation, skin pores, skin inflammation, skin hydration, skin sebum level, acne, moles, skin luminosity, skin radiance, skin dullness and skin barrier, prediction of future cosmetic skin attributes, and combinations thereof. 3. The method according to any one of the preceding claims, wherein, prior to step (c), the first digital image is filtered by using a smoothing filter and/or a frequency filter. 4. The method according to any one of the preceding claims, wherein the first digital image is a cross-polarized image. 5. The method according to any one of the preceding claims, wherein the at least one color gradient is obtained by the following steps: 1) Calculate the average intensity value of a specific color for each tile; 2) The gradient value of a tile is obtained by calculating the gradient of the average intensity value between adjacent tiles using the following equation: , Where I _{_i,j} is the average intensity value of the patch at position (i, j) calculated in step (1) above, I _{_i+1,j} is the average intensity value of the patch at position (i+1, j) calculated in step (1) above, and I _{_i,j+1} is the average intensity value of the patch at position (i, j+1) calculated in step (1) above. 6. The method according to any one of claims 2 to 5, wherein the cosmetic skin attribute is generated as a value indicating the condition of at least a portion of the person's skin relative to a defined population, and is generated as a function of the gradient values of at least one color channel image defined by F (gradient value), wherein the function is determined by a model built on a training dataset, wherein the training dataset comprises: (i) Multiple color channel images of the defined population, wherein each color channel image of the multiple color channel images includes the facial skin of a person in the defined population; (ii) Based on the associated category definition of the aforementioned cosmetic skin attributes, Preferably, the cosmetic skin attribute is generated as a function of the gradient value combined with the base skin color defined by F(gradient value, base skin color) at the patch; preferably, the at least one color channel image includes an a-channel image; wherein the gradient value is an a-gradient value. Preferably, the model is a regression model or a classification model; more preferably, the model is a classification model, more preferably a machine learning classification model, and most preferably a machine learning random forest classification model or a gradient boosting classification model. 7. The method according to any one of the preceding claims, wherein the first digital image obtained includes at least one region of interest (ROI) of at least a portion of the subject's face, wherein the at least one ROI is a skin area around the cheek ("cheek area"). 8. The method according to any one of the preceding claims, wherein defining a plurality of tiles across the obtained first digital image is defining a plurality of tiles across the region of interest, wherein the area of each tile is about 1% to 20% of the area of the ROI, preferably about 1% to about 10% of the area of the ROI, more preferably about 1% to about 5% of the area of the ROI. 9. The method according to any one of the preceding claims, the method further comprising the step of displaying a comparison between a degree marker of each of the defined plurality of tiles and a predetermined value associated with a defined population. 10. The method according to any one of the preceding claims, wherein the display in step (e) comprises a second digital image inserted into at least a portion of the subject's face and a plurality of tiles of the display, each having a uniquely assigned unidegree marker. 11. The method according to any one of the preceding claims, wherein the single-degree mark is selected from the group consisting of graphic symbols, numerical values, color codes, illumination, and combinations thereof. 12. The method according to any one of the preceding claims, the method further comprising displaying at least one product recommendation item to process at least one displayed color gradient or displayed cosmetic skin properties. 13. A system for visualizing at least one color gradient of a person, the system comprising: An image acquisition unit is configured to acquire a first digital image of at least a portion of the face of the person, wherein the first digital image is selected from at least a region of an input image of the face; wherein preferably, the image acquisition unit includes a non-transitory computer-readable storage medium configured to store the acquired first digital image; An image processing unit, coupled to the image acquisition unit, is configured to define a plurality of patches across the acquired first digital image, to analyze the first digital image for each of the defined plurality of patches for the at least one color gradient, and to uniquely assign a single-degree label to each of the defined plurality of patches based on the at least one color gradient of the patch being analyzed. The display generation unit, coupled to the image processing unit, is used to visualize at least some of the plurality of tiles, each having a uniquely assigned single-degree label, for visualizing at least one color gradient. The at least one color gradient is a gradient calculated on the a* channel image of the first digital image in the L*a*b* chromaticity system. 14. A system for visualizing the cosmetic properties of human skin, the system comprising: An image acquisition unit is configured to acquire a first digital image of at least a portion of the face of the person, wherein the first digital image is selected from at least a region of an input image of the face; wherein preferably, the image acquisition unit includes a non-transitory computer-readable storage medium configured to store the acquired first digital image; An image processing unit, coupled to the image acquisition unit, is configured to define a plurality of patches across the acquired first digital image, to analyze the first digital image for each of the defined plurality of patches based on at least one color gradient for the at least one cosmetic skin attribute, and to uniquely assign a single-degree label to each of the defined plurality of patches based on the at least one cosmetic skin attribute of the patch being analyzed. A display generation unit, coupled to the image processing unit, is used to visualize at least some of the plurality of tiles, each having a uniquely assigned single-degree label, for visualizing at least one cosmetic skin attribute.