JP6943149B2 - Visual simulation equipment, visual simulation methods, and programs for visual simulation equipment - Google Patents

Description

The present invention relates to a visual simulation device that creates a visual simulation image, a visual simulation method that creates a visual simulation image, and a program for a visual simulation device that creates a visual simulation image.

The visual functions (visual acuity, color vision, lightness sensation, contrast sensitivity, visual field, etc.) possessed by a person are unique to each person and are rarely exactly the same as those of other people. This is because visual function is affected by both genetic and acquired factors (aging, illness, accidents, etc.). For example, in Japan, it is said that about 5% of the male population and 0.2% of the female population are congenital color blind. It is difficult for people with congenital color vision deficiency to distinguish between red and green on a daily basis. In addition, it is known that the appearance of things may be deteriorated by suffering from age-related cataract, and the number of people suffering from cataract increases with age. In this way, people's appearances vary widely. For example, even traffic signals and signs differ from person to person, and it may be difficult for some people to distinguish colors. Therefore, techniques for simulating human vision (how things look) have been studied based on neurophysiology research and visual psychology research (for example, Patent Documents 1-3 and Non-Patent Documents 1).

Patent Document 1 discloses a technique for realizing a color universal color design that is easy for a person with color vision deficiency to identify and does not give a sense of discomfort to a healthy person. Patent Document 2 discloses a visual simulated experience device for simulating a visual state. Patent Document 3 discloses an image signal processing device used for simulating and displaying the color vision of a person with color vision deficiency. Non-Patent Document 1 discloses an image conversion technique for simulating the appearance of colors of a dichromat.

JP-A-2007-240508 Japanese Unexamined Patent Publication No. 2011-13373 International Publication No. 2011/039811 Pamphlet

Brettel et al. , "Computerized simulation of color appearance for discromats", Journal of the Optical Society of Optica A, Vol. 14,2647-2655

As described above, human visual functions are classified into a plurality of types such as visual acuity, color vision, lightness sensation, contrast sensitivity, visual field, and the like. However, the techniques described in Patent Documents 1-3 and the techniques described in Non-Patent Document 1 are limited in the visual functions that can be simulated, and are not supposed to simulate the visual functions of each person.

Therefore, a technique capable of simulating the visual function of each person is required.

The feature configuration of the visual simulation apparatus according to the present invention is a brain wave database created based on the amplitude change of the stationary visual evoked potential signal acquired from the brain wave signal of the subject who viewed the visual object, and the visual simulation of the subjects. The target person setting unit that sets the target person to perform the visual simulation, the correction parameter extraction unit that extracts the correction parameter for the target person that corrects the original image of the visual simulation target from the brain wave database, and the original image of the target person. An image conversion unit that converts an image captured in the primary visual field into a visual field image, a correction image generation unit that generates a corrected visual field image based on the visual field image and the correction parameters, and the corrected visual field image. A natural image conversion unit that converts a natural image into a natural image captured by the subject's retina and a display unit that displays the natural image are provided.

With such a feature configuration, the appearance of the subject's thing is simulated based on the amplitude change of the stationary visual evoked potential signal acquired from the brain wave signal, and the appearance of the subject's thing is given to a person other than the subject. Can be shown. In addition, the stationary visual evoked potential signal acquired from the electroencephalogram signal contains the subjectivity of the subject, but can be objectively simulated. In this way, according to this visual simulation device, it is possible to simulate the visual function of each person, and it is possible to support a design design that is easy for the target person to see.

Further, the electroencephalogram database is created for each visual function, and the corrected image generation unit superimposes a correction parameter for each visual function on the visual cortex image converted from the original image, and the corrected visual cortex image. It is preferable to generate.

People often see things differently due to congenital and acquired reasons. This is because the influence of congenital and acquired reasons differs depending on the visual function. Therefore, according to this configuration, when correcting the original image, the correction parameters for each visual function are superimposed to generate the corrected visual cortex image, so that the correction suitable for the target person set by the target person setting unit is performed. It is possible to generate a visual cortex image.

Further, the correction parameter is created by normalizing the amplitude change of the stationary visual evoked potential signal of the plurality of subjects based on the average value of the amplitude change of the preset group among the plurality of subjects. It is preferable that it is done.

With such a configuration, it is possible to simulate how things look not only to individuals but also to groups.

Further, the feature configuration of the visual simulation method according to the present invention is a subject setting step for setting a subject to perform a visual simulation, and a constantness acquired from a brain wave signal of a subject including at least the subject who has seen the visual object. A correction parameter extraction step for extracting a correction parameter for the subject who corrects the original image of the visual simulation target from a brain wave database created based on a change in the amplitude of the visual evoked potential signal, and a correction parameter extraction step for extracting the original image of the subject. An image conversion step of converting to a visual field image which is an image captured in the primary visual field, a correction image generation step of generating a corrected visual field image based on the visual field image and the correction parameters, and the corrected visual field image. The point is that it includes a natural image conversion step of converting the natural image into a natural image captured by the subject's retina and a display step of displaying the natural image.

Even with such a visual simulation method, there is substantially no difference from the above-mentioned visual simulation apparatus, and it is possible to obtain the same effect as the visual simulation apparatus.

Further, the feature configuration of the program for the visual simulation apparatus according to the present invention is acquired from the target person setting function for setting the target person to perform the visual simulation and the brain wave signal of the subject including at least the target person who has seen the visual object. A correction parameter extraction function that extracts correction parameters for the subject who corrects the original image of the visual simulation target from the brain wave database created based on the amplitude change of the stationary visual evoked potential signal, and the original image. An image conversion function that converts an image captured in the primary visual field of the target person into a visual field image, a correction image generation function that generates a corrected visual field image based on the visual field image and the correction parameters, and the above. It is characterized by having a natural image conversion function for converting a corrected visual field image into a natural image captured by the subject's retina, and a display function for displaying the natural image.

Further, even with such a program for the visual simulation device, it is possible to obtain the same effect as the above-mentioned visual visual simulation device.

It is a block diagram which shows the structure to the visual simulation apparatus. It is a figure which shows the visual object. It is a figure which shows an example of the acquired electric signal. It is a figure which shows the stationary visual evoked potential. It is a figure which shows an example of an electroencephalogram database. It is a figure which shows an example of an electroencephalogram database. This is an example of an image correction matrix for color vision correction. It is a figure which shows the simulation result. It is a figure which shows the simulation result. This is an example of an image correction matrix for color vision correction. It is a figure which shows the natural image for a young person and the natural image for an old person.

The visual simulation apparatus according to the present invention is configured to have a function of simulating the appearance of each person. Hereinafter, the visual simulation device 1 of the present embodiment will be described.

FIG. 1 is a diagram schematically showing the configuration of the visual simulation device 1. As shown in FIG. 1, the visual simulation device 1 includes an electroencephalogram database 10, a subject setting unit 20, a correction parameter extraction unit 30, an image conversion unit 40, a correction image generation unit 50, a natural image conversion unit 60, and a display unit 70. Each of the functional units is provided, and these functional units are constructed by hardware, software, or both with a CPU as a core member in order to perform the processing related to the above-mentioned simulation.

The electroencephalogram database 10 is created based on the amplitude change of the stationary visual evoked potential signal acquired from the electroencephalogram signal of the subject who viewed the visual object. A visual object is an image shown to a subject in order to evaluate the visual function of the subject. The visual function refers to, for example, color vision, visual acuity, contrast sensitivity, and lightness sensation. The visual objects used to evaluate the visual function are set according to the evaluation items of the visual function. The evaluation items are color vision evaluation, visual acuity evaluation, contrast sensitivity evaluation, and lightness sensation evaluation.

For example, a visual object used for color vision evaluation includes a first display and a second display as shown in FIG. The first display and the second display used for color vision evaluation are composed of patterns different from each other. The first display is a display in which a first pattern having a gray tone and a second pattern having a gray tone different from the first pattern are repeatedly displayed on the display screen. The first pattern and the second pattern are set so that the size is apparently 10 degrees, and the shape is set as a circle having a mosaic patch structure. The mosaic patch structure is a structure in which a plurality of circular patches are arranged to form one circular shape. The size of each patch is apparently set randomly within the range of 0.2 degrees to 0.5 degrees, and the arrangement is randomly determined so that the patches do not overlap each other. Luminance noise within the range of ^{20 cd / m 2} to 60 cd / m 2 is added to each patch.

The gray tone is a color created based on gray. Therefore, when the color name is indicated by an RGB value, it is not limited to (128,128,128), for example, (220,220,220), (211,21,211), (192,192,192), and the like. , (169,169,169), (128,128,128), (105,105,105) and the like.

Further, the brightness of each color of the first display is changed and colored within a predetermined range. For example, from gray defined by the basic color (186,186,186) to -22.5 for each patch. , -15, 7.5, 7.5, 15, 22.5 cd / m ² , and the brightness is adjusted so that any of the brightness deviations occurs. Which patch the brightness deviation is applied to is randomly determined.

The second display is a display in which the third pattern of the chromatic color and the fourth pattern of the chromatic color different from the chromatic color of the third pattern are repeatedly displayed on the display screen. The chromatic color is a color other than the color displayed when white and black are displayed in gradation. In this embodiment, two displays are used as the second display. On the other hand, in the second display, red is used as the chromatic color of the third pattern, and green is used as the chromatic color of the fourth pattern. On the other hand, in the second display, blue is used as the chromatic color of the third pattern, and yellow is used as the chromatic color of the fourth pattern. The chromatic colors red (Red) and green (Green) are both colors on the LM axis of color vision, and are a pair that is difficult to distinguish in a person with congenital red-green color vision deficiency. The chromatic colors blue and yellow are both colors on the S- (L + M) axis of color vision, and are a pair that is difficult to distinguish in a person with congenital blue-yellow color vision abnormality. In the following, when distinguishing between them, the second display in which red and green are used is shown as "RG system second display", and the second display in which blue and yellow are used is referred to as "BY system second display". Shown as "display".

Similar to the first pattern and the second pattern in the first display, the third pattern and the fourth pattern in the second display are also set so that the size is apparently 10 degrees, and the shape is a mosaic patch structure. Set in a circle with. The size of each patch is apparently set randomly within the range of 0.2 degrees to 0.5 degrees, and the arrangement is randomly determined so that the patches do not overlap each other.

Further, similarly to the first display, the brightness of each color of the second display is also changed and colored within a predetermined range. For example, the basic colors (red, green, blue, yellow) of each pattern are changed for each patch. ) To -22.5, -15, -7.5, 7.5, 15, and 22.5 cd / m ² so that the brightness deviates from the brightness. Which patch the brightness deviation is applied to is randomly determined. For such visual objects (first display and second display), it is preferable that the background (background) is unified to the same color (for example, set to gray).

Such a visual object is displayed on the display screen in a preset display form (blinking at a predetermined blinking cycle (blinking frequency)), and the brain wave of the subject who sees the display screen is transmitted to the subject's head. It is acquired as an electric signal by the attached detection electrode. The detection electrodes are attached to four locations (POZ, OZ, O1, O2 according to the international 10-20 method) corresponding to the positions of the cerebral visual cortex in the occipital region of the subject. The visual cortex is the part of the cerebral cortex that is directly related to vision and is located in the occipital lobe. The detection electrodes are attached to the back of the head so that the brain waves emitted from the visual cortex when the subject sees the first display and the second display can be easily detected. At this time, a GND electrode and a REF electrode are also attached to the earlobe of the subject.

Here, the magnitude of the electroencephalogram signal is several μV level. Therefore, in order to facilitate signal processing, the acquired electroencephalogram signal is signal-amplified using a biological amplifier. The amplified electroencephalogram signal is recorded by analog-to-digital conversion at a predetermined sampling frequency. The acquisition and processing of such an electroencephalogram signal is performed in synchronization with the display of the visual object described above. A method of showing such a visual object to a subject and acquiring an electroencephalogram signal of the subject at that time is known, for example, as disclosed in Japanese Patent Application No. 2015-247199, and thus description thereof will be omitted.

FIG. 3 shows an example of an electric signal based on the above-mentioned electroencephalogram signal. The electrical signal shown in FIG. 3 is subjected to frequency analysis (for example, Fourier transform) to obtain an average frequency-power spectral density waveform as shown in FIG. The horizontal axis is the frequency of the electroencephalogram signal, and the vertical axis is the power spectral density (PSD). The signal as shown in FIG. 4 is referred to as the above-mentioned Steady State Visual Evoked Potential (SSVEP) signal. Here, as shown in FIG. 4, the SSVEP signal is acquired for each of the first display, the RG system second display, and the BY system second display. Here, the base harmonics frequency component of SSVEP (1F component appearing at a frequency equal to the blinking frequency of the first display and the second display) and the nth (however, n ≧ 3) harmonics component (4F component, 6F component) are In many cases, the amplitude is smaller than that of the 2F component, and even if the display on the display screen is changed, no significant change appears. Therefore, for example, the secondary harmonics frequency component of SSVEP (frequency that is twice the blinking frequency of the visual object). It is preferable to make a judgment based on the amplitude of the component (2F component) appearing in.

Such SSVEP signals are acquired from a plurality of subjects, and the amplitude change of the SSVEP signal with respect to the RG system second display and the amplitude change of the SSVEP signal with respect to the BY system second display are stored in a database as an SSVEP response. It is shown in FIGS. 5 and 6. FIG. 5 shows a plurality of subjects classified by age (young and old), and FIG. 6 shows a plurality of subjects according to color vision ability (normal color vision, eye disease suffering, and congenital color blindness). It is classified by. In FIGS. 5 and 6, the vertical axis represents the SSVEP response to the BY system second display, and the horizontal axis represents the SSVEP response to the RG system second display. The younger subjects are subjects aged 20 to 50 years, and the elderly subjects are subjects aged 51 years or older. FIG. 5 is a normalization of the average value of the amplitude change of the SSVEP signal of the young person as a reference value (1.0), and FIG. 6 shows the average value of the amplitude change of the SSVEP signal of the normal color vision person as the reference value (1). It is normalized as .0). On both the vertical and horizontal axes, the larger the value, the larger the SSVEP response to the color change of the visual object (the amplitude change of the SSVEP signal was large, and the subject clearly perceived the color change).

The relationship between the SSVEP response to the BY system second display and the SSVEP response to the RG system second display shown in FIGS. 5 and 6 is stored in advance in the above-mentioned electroencephalogram database 10.

Returning to FIG. 1, the target person setting unit 20 sets a target person to perform a visual simulation among the subjects. The subject is a person presented with a visual object in the above-mentioned electroencephalogram database 10 in order to memorize the relationship between the SSVEP response to the BY system second display and the SSVEP response to the RG system second display. .. Visual simulation is a simulation of how things look. When there is only one subject, the subject to be visually simulated is the subject, which is set by the subject setting unit 20. On the other hand, when there are a plurality of subjects, a target person to perform a visual simulation is selected from the plurality of subjects and set by the target person setting unit 20. The setting of the target person by the target person setting unit 20 is performed by the input of the user.

The step of setting a target person to perform such a visual simulation is referred to as a target person setting step in the visual simulation method. The target person set by the target person setting unit 20 is transmitted to the correction parameter extraction unit 30 described later as the target person information indicating the target person.

The correction parameter extraction unit 30 extracts correction parameters for the subject who corrects the original image of the visual simulation target from the electroencephalogram database 10. The original image to be visually simulated is an image used to simulate what a person looks like. This original image may be a still image or a moving image. Further, the original image may be, for example, a digital image handled by a personal computer, a digital camera, a car navigation system, or the like, or an analog image such as a painting itself or a photograph taken by a film camera. .. The correction parameters for the subject correspond to the numerical values shown on the horizontal axis and the vertical axis of FIGS. 5 and 6. That is, among the points showing the SSVEP response of the subject in the electroencephalogram database 10, the numerical values constituting the coordinates of the points showing the SSVEP response of the subject set by the subject setting unit 20 correspond. As described above, the correction parameter indicates that the amplitude change of the SSVEP signal of a plurality of subjects is set in a preset group among the plurality of subjects (in FIG. 5, a group classified by age, in FIG. 6). Is created by normalizing the subjects based on the average value of the amplitude change of the group (group classified by color vision ability).

For the subject who corrects the original image of the visual simulation target from the brain wave database 10 created based on the amplitude change of the SSVEP signal acquired from the brain wave signal of the subject including at least the subject who saw such a visual object. The step of extracting the correction parameter is referred to as a correction parameter extraction step in the visual simulation method. The correction parameters extracted by the correction parameter extraction unit 30 are transmitted to the correction image generation unit 50, which will be described later.

The image conversion unit 40 converts the original image into a visual cortex image which is an image captured in the subject's primary visual cortex. The original image is an image used for simulating how a person looks as described above, and is input to the image conversion unit 40. The primary visual cortex is a functional part of the brain that constitutes the above-mentioned visual cortex. The image captured in the primary visual cortex is the total amount of visual information perceived in the primary visual cortex. Researchers have known that images captured in such a primary visual cortex are different from images captured in the human retina. Further, a method of converting such an image captured by the human retina into an image captured by the primary visual cortex has also been known by previous studies.

For example, when the original image is displayed on the display of the display device, gamma correction (gamma value = 2.2 in the sRGB display) is generally performed so as to be perceptually natural. Therefore, the image conversion unit 40 converts the RGB values corrected for display display into linear RGB values. the corrected RGB value for sRGB display displays the _{(R G, G G, B} G), the linear RGB values _{(R L, G L, B} L) when _{to, R G, G G, B} G 0 in the case of .04045 below, (1) - (3) can be converted by the _formula, when R _{G, G G, B G} is greater than 0.04045, the equation (4) - conversion (6) can. _{Incidentally, R G, G G, B} G is the RGB value of each pixel of the original image.

When the white point of the display is set to D65, the linear RGB value can be converted into the value in the XYZ color space by the equation (7).

Further, the value in the XYZ color space is converted into the value in the LMS space. This conversion can be performed by, for example, the equation (8).

Further, the value in the LMS space is converted into the value in the DKL space. The background color was set to (R', G', B') = (186,186,186), that is, (L ₀ , M ₀ , S ₀ ) = (0.5078, 0.4334, 0.3025). At that time, this conversion can be performed by the equation (9).

In this way, the image conversion unit 40 converts the original image into a visual cortex image which is an image captured in the primary visual cortex of the subject. The step of converting such an original image into a visual cortex image, which is an image captured in the primary visual cortex of the subject, is called an image conversion step in the visual simulation method. The data related to the visual cortex image converted by the image conversion unit 40 is transmitted to the correction image generation unit 50, which will be described later.

The correction image generation unit 50 generates a correction visual cortex image based on the visual cortex image and the correction parameter. The visual cortex image is an image converted from the original image by the image conversion unit 40, and the data of the visual cortex image is transmitted to the correction image generation unit 50. The correction parameter is a correction parameter extracted by the correction parameter extraction unit 30.

The corrected image generation unit 50 corrects the visual cortex image according to the correction parameters. This correction is performed by the equation (10) in the DKL space.

M in Eq. (10) is called an image correction matrix and is composed of correction parameters. The correction parameters are different for each person and for each visual function. Therefore, the image correction matrix M may change each time.

FIG. 7 shows an example of the image correction matrix M. As the image correction matrix M of A in FIG. 7, the image correction matrix M of the subject A (when the subject A is the subject) in FIG. 5 is shown. Similarly, the image correction matrix M of B, C, D, E, and F in FIG. 7 shows the image correction matrix M of the subjects B, C, D, E, and F in FIG. 5, respectively. In each image correction matrix M of FIG. 7, m ₁₁ indicates a luminance correction value, and 1.00 indicates that the luminance correction is not performed. _{Further, m 22} in each image correction matrix M in FIG. 7 indicates a correction value based on the SSVEP response to the RG system second display, and m ₃₃ in each image correction matrix M indicates a correction value for the BY system second display. The correction value based on the SSVEP response is shown.

In the present embodiment, the electroencephalogram database 10 is described by taking the SSVEP response related to color vision as an example, but when the electroencephalogram database 10 is created for each visual function, the corrected image generation unit 50 is an original image. It is preferable to superimpose the correction parameters for each visual function on the visual cortex image converted from the above to generate the corrected visual cortex image.

The corrected image generation unit 50 corrects the visual cortex image in this way. A step of generating a corrected visual cortex image based on such a visual cortex image and a correction parameter is called a correction image generation step in the visual simulation method. The data related to the corrected visual field image generated by the corrected image generation unit 50 is transmitted to the natural image conversion unit 60, which will be described later.

The natural image conversion unit 60 converts the corrected visual cortex image into a natural image captured by the subject's retina. As described above, the correction image generation unit 50 transmits data related to the correction visual cortex image to the natural image conversion unit 60. A natural image captured by the subject's retina means an image recognized by the human retina.

The natural image conversion unit 60 first converts the color coordinates of each pixel of the corrected visual cortex image from the DKL space to the LMS space. This conversion is performed using the equation (11). Here, the background color set by the equation (9) is commonly used. Further, the 3 × 3 matrix of the equation (11) corresponds to the inverse matrix of the 3 × 3 matrix of the equation (9).

Next, the color coordinates of each pixel are converted from the LMS space to the XYZ space. This conversion is performed using Eq. (12). The 3 × 3 matrix of Eq. (12) corresponds to the inverse matrix of the 3 × 3 matrix of Eq. (8).

Further, the color coordinates of each pixel are converted from the XYZ space to the sRGB space. In this conversion, first, the linear RGB values from the XYZ space to the sRGB space are calculated using the equation (13). Here, the white point of the display is set as D65 as in the equation (7).

Subsequently, the linear RGB value is gamma-corrected for display. _{R 'L, G' L,} B ' when _L is 0.0031308 below, (14) - (16) was performed using, _{R' L, G 'L,} B' _L is 0.0031308 If it is larger, it is carried out using Eqs. (17)-(19).

The natural image conversion unit 60 converts the corrected visual cortex image into a natural image in this way. The step of converting such a corrected visual cortex image into a natural image captured by the subject's retina is called a natural image conversion step in the visual simulation method. The data related to the natural image by the natural image conversion unit 60 is transmitted to the display unit 70, which will be described later.

The display unit 70 displays a natural image. That is, the display unit 70 is configured to have a display, and the natural image converted by the natural image conversion unit 60 is displayed on this display. At this time, the displayed natural image corresponds to the image that the subject who is the target of the visual simulation sees on the retina. By viewing such an image by another person, it becomes possible to grasp the image that the target person is seeing.

FIG. 8 shows the visual simulation results of each person up to the subjects A to F shown in FIG. 5 described above when the so-called xy chromaticity diagram is used as the original image. As shown in FIG. 8, in the subject A and the subject B who had SSVEP responses larger than or almost equal to the average of young people to the red-green change and the blue-yellow change, depending on the degree. The color was emphasized. In addition, in the subject CF, whose SSVEP response was smaller than the average of young people to the red-green change and the blue-yellow change, the tint was weakened according to the degree. .. In particular, in subject D, who is a type 2 dichromat, the red component and the green component were missing.

Further, FIG. 9 shows the average G of young people shown in FIG. 5, the average H of old people shown in FIG. 5, and the average of normal color vision people shown in FIG. 6 when the xy chromaticity diagram is used as the original image. I, the average J of the congenital color blind person (congenital red-green color blind person) shown in FIG. 6, and the average K of the eye disease affected person shown in FIG. 6 are shown. As shown in FIG. 9, in the elderly group in which the SSVEP response to the red-green change and the blue-yellow change was smaller than that in the young group, the tint was reduced accordingly. In addition, the red component and the green component were significantly weakened in the congenital red-green dysfunction group, which had a smaller SSVEP response to the blue-yellow change than in the normal color vision group. In addition, in the group of patients with eye diseases, the SSVEP response to the red-green change and the blue-yellow change was small, so that the color was weak overall. Note that FIG. 10 shows the image correction matrix M used when obtaining the simulation result of FIG. 9.

The display unit 70 displays such a simulation result. The step of displaying such a natural image is called a display step in the visual simulation method.

As described above, according to the present visual simulation device 1, it is possible to simulate the appearance of each person's things and to grasp how each person looks from the simulation result.

FIG. 11 compares the simulation results of a young person and an old person who performed a visual simulation using a more specific image. FIG. 11A shows a WEB page, FIG. 11B shows a screen of a car navigation system, and FIG. 11C shows a view from the driver's seat of a car. Overall, the appearance of the elderly is less colored than that of the young. From the comparison of the two, it is understood that the display that is functioning effectively in the young is difficult to see in the elderly. Specifically, for example, the display portion of the traveling lane (for example, the portion indicated by the reference numeral T) in FIG. 11 (b), the sign with the tree in the background (for example, the portion indicated by the reference numeral U), and the like are displayed. , Older people are more difficult to see than younger people. It is unavoidable that the visual function deteriorates due to aging and the appearance of things deteriorates, but it is possible to visually recognize by making the visibility / usability of the product correspond to each other based on the difference in the appearance of things. It becomes possible to make it easier. Therefore, it is preferable to use the present visual simulation device 1 to simulate what such an easily visible display looks like. As a result, it is possible to create a display object by selecting a color suitable for the target person who sees the display object and prevent the target person from overlooking.

Further, according to the present visual simulation device 1, for example, it is possible to grasp a design that is easy to see for a person who is a target of a product by using the above-mentioned visual simulation result. Therefore, it is possible to know the validity of the design from the visual simulation results without gathering people for each product development and conducting a visibility survey. Specifically, the visual simulation results are universal designs for products (for example, traffic signals, traffic signs, information bulletin boards, guide maps, etc.) that try to present important information to all people who make up society in public places. Products), products with biased user characteristics (for example, equipment in hospitals, equipment in elderly care facilities, localized design products such as nursing care products), products that suit individual tastes (for example, navigation) It can be used for designing systems, personalized design products such as automobile dashboards and web pages), and products used in visual function tests (for example, medical devices such as visual function test devices).

[Other Embodiments]
In the above embodiment, the correction parameter is described as being created by normalizing the amplitude change of the SSVEP signal of a plurality of subjects based on the average value of the amplitude change of a preset group among the plurality of subjects. However, the correction parameters may be created, for example, in a table or a map without normalization as described above.

In the above embodiment, the visual simulation device 1 and the visual simulation method have been described, but it is also possible to configure the program as a program for the visual simulation device 1.

In such a case, the program for the visual simulation device 1 includes a target person setting function for setting a target person to perform visual simulation, and a stationary visual induction obtained from a brain wave signal of a subject including at least the target person who has seen a visual object. A correction parameter extraction function that extracts correction parameters for the subject who corrects the original image of the visual simulation target from the brain wave database 10 created based on the amplitude change of the potential signal, and an original image in the primary visual field of the subject. An image conversion function that converts the captured image into a visual field image, a corrected image generation function that generates a corrected visual field image based on the visual field image and correction parameters, and a corrected visual field image that is captured by the subject's retina. It is preferable to have a natural image conversion function for converting to a natural image and a display function for displaying a natural image.

The program for such a visual simulation device 1 is substantially the same as the visual simulation device 1 and the visual simulation method, and the visual simulation can be performed as described above by using the program. It is preferable to store such a program in a storage medium such as a CD or DVD.

In the above embodiment, the visual object for color vision evaluation has been described as an example, but the visual object is suitable for each evaluation item by using the visual acuity evaluation, the contrast sensitivity evaluation, and the brightness sensation evaluation. It is also possible to perform visual simulation.

In the above embodiment, as the correction database, an example classified by age and an example classified by color vision ability have been described. However, the correction database is described by, for example, gender, eye disease, type of color vision deficiency, and region (for example, Asia). , Africa, Europe, etc.), it is also possible to classify by race.

The present invention can be used in a program for a visual simulation device that creates a visual simulation image, a visual simulation method that creates a visual simulation image, and a visual simulation device that creates a visual simulation image.

1: Visual simulation device 10: EEG database 20: Target subject setting unit 30: Correction parameter extraction unit 40: Image conversion unit 50: Correction image generation unit 60: Natural image conversion unit 70: Display unit

Claims (5)

An electroencephalogram database created based on the amplitude change of the stationary visual evoked potential signal obtained from the electroencephalogram signal of the subject who saw the visual object,
A target person setting unit that sets a target person to perform a visual simulation among the subjects, and a target person setting unit.
A correction parameter extraction unit that extracts correction parameters for the subject to correct the original image of the visual simulation target from the electroencephalogram database, and a correction parameter extraction unit.
An image conversion unit that converts the original image into a visual cortex image that is an image captured in the primary visual cortex of the subject, and an image conversion unit.
A correction image generation unit that generates a correction visual cortex image based on the visual cortex image and the correction parameter,
A natural image conversion unit that converts the corrected visual cortex image into a natural image captured by the subject's retina.
A display unit that displays the natural image and
A visual simulation device equipped with. The electroencephalogram database is created for each visual function,
The visual simulation device according to claim 1, wherein the corrected image generation unit superimposes a correction parameter for each visual function on the visual cortex image converted from the original image to generate the corrected visual cortex image. The correction parameter is created by normalizing the amplitude change of the stationary visual evoked potential signal of the plurality of subjects based on the average value of the amplitude change of a preset group among the plurality of subjects. The visual simulation apparatus according to claim 1 or 2. Target person setting step to set the target person to perform visual simulation, and
The subject who sees the visual object and corrects the original image of the visual simulation target from the electroencephalogram database created based on the amplitude change of the stationary visual evoked potential signal acquired from the brain wave signal of the subject including at least the subject. Correction parameter extraction step to extract correction parameters for
An image conversion step of converting the original image into a visual cortex image which is an image captured in the primary visual cortex of the subject, and
A correction image generation step of generating a correction visual cortex image based on the visual cortex image and the correction parameter,
A natural image conversion step of converting the corrected visual cortex image into a natural image captured by the subject's retina, and
A display step for displaying the natural image and
Visual simulation method with. Target person setting function to set the target person to perform visual simulation, and
The subject who sees the visual object and corrects the original image of the visual simulation target from the electroencephalogram database created based on the amplitude change of the stationary visual evoked potential signal acquired from the brain wave signal of the subject including at least the subject. Correction parameter extraction function that extracts correction parameters for
An image conversion function that converts the original image into a visual cortex image that is an image captured in the primary visual cortex of the subject, and
A correction image generation function that generates a correction visual cortex image based on the visual cortex image and the correction parameter,
A natural image conversion function that converts the corrected visual cortex image into a natural image captured by the subject's retina,
The display function for displaying the natural image and
A program for a visual simulation device that includes.

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