JP7665159B2 - Clear image acquisition system, clear image acquisition method, and program - Google Patents

Description

The present invention relates to a clear image acquisition system, a clear image acquisition method, and a program.

In a manufacturing line, a method is known for performing visual inspection of a product (workpiece) using photographed images, as disclosed in the following document:

JP 2022-47442 A

Products on the production line may be subject to vibrations. Therefore, in cases where clear images of the product cannot be obtained due to vibrations, visual inspection using image processing is difficult.

In consideration of the above circumstances, the present invention aims to provide a clear image acquisition system that can acquire clear images of vibrating objects.

According to one aspect of the present invention, a clear image acquisition system is provided. The clear image acquisition system includes a processor. The processor is configured to execute a receiving step and a processing step. In the receiving step, input of a plurality of images of a vibrating object captured successively is received. In the processing step, a clear image having motion blur smaller than a predetermined standard is extracted from the plurality of images.

According to this aspect, images with less motion blur than a standard are extracted from multiple images captured continuously, making it possible to automatically obtain clear images of vibrating objects.

1 is a configuration diagram showing a clear image acquisition system 1. FIG. FIG. 2 is a block diagram showing a hardware configuration of an information processing device 2. FIG. 2 is a block diagram showing a hardware configuration of a user terminal 3. 2 is a schematic diagram showing a configuration of an imaging device 4. FIG. A block diagram showing functions realized by the user terminal 3 (processor 33). 11 is a flow diagram showing a process for adjusting the angle of incidence on the camera 41. FIG. 10 is a schematic diagram illustrating the relationship between the angle of the galvanometer mirror 44 and the position of the center point P of the object T. FIG. FIG. 11 is a flowchart showing a first extraction process. FIG. 2 is a conceptual diagram showing the movement of a center point P of an object between two images. FIG. 11 is a flowchart showing a second extraction process. FIG. 13 is a diagram illustrating an example of an amplitude spectrum.

The following describes embodiments of the present invention with reference to the drawings. The various features shown in the following embodiments can be combined with each other.

The program for realizing the software appearing in this embodiment may be provided as a non-transitory computer-readable recording medium, or may be provided so that it can be downloaded from an external server, or may be provided so that the program is started on an external computer and its functions are realized on a client terminal (so-called cloud computing).

In this embodiment, a "unit" may also include, for example, a combination of hardware resources implemented by a circuit in the broad sense and software information processing that can be specifically realized by these hardware resources. In addition, this embodiment handles various types of information, which may be represented, for example, by physical values of signal values representing voltage and current, high and low signal values as a binary bit collection consisting of 0 or 1, or quantum superposition (so-called quantum bits), and communication and calculations may be performed on a circuit in the broad sense.

In the broad sense, a circuit is a circuit realized by at least appropriately combining a circuit, circuitry, a processor, and memory. In other words, it includes application specific integrated circuits (ASICs), programmable logic devices (e.g., simple programmable logic devices (SPLDs), complex programmable logic devices (CPLDs), and field programmable gate arrays (FPGAs)), etc.

1. Hardware Configuration This section describes the hardware configuration.

<Clear image acquisition system 1>
1 is a configuration diagram showing a clear image acquisition system 1. The clear image acquisition system 1 includes an information processing device 2, a user terminal 3, and a photographing device 4. The information processing device 2 and the user terminal 3 are configured to be able to communicate with each other via a telecommunications line. In one embodiment, the clear image acquisition system 1 is made up of one or more devices or components. For example, if the clear image acquisition system 1 is made up of only the information processing device 2 or the user terminal 3, the clear image acquisition system 1 can be the information processing device 2 or the user terminal 3. These components will be described below.

<Information processing device 2>
2 is a block diagram showing a hardware configuration of the information processing device 2. The information processing device 2 includes a communication bus 20, a communication unit 21, a storage unit 22, and a processor 23. The communication unit 21, the storage unit 22, and the processor 23 are electrically connected via the communication bus 20 inside the information processing device 2.

<Communication unit 21>
The communication unit 21 is preferably a wired communication means such as USB, IEEE 1394, Thunderbolt (registered trademark), wired LAN network communication, etc., but may also include wireless LAN network communication, mobile communication such as 3G/LTE/5G, BLUETOOTH (registered trademark) communication, etc. as necessary. In other words, it is more preferable to implement it as a collection of multiple communication means. In other words, the information processing device 2 may communicate various information from the outside via the communication unit 21 and the network.

<Storage unit 22>
The storage unit 22 stores various information defined by the above description. This can be implemented, for example, as a storage device such as a solid state drive (SSD) that stores various programs and the like related to the information processing device 2 executed by the processor 23, or as a memory such as a random access memory (RAM) that stores temporarily required information (arguments, arrays, etc.) related to the program calculations. The storage unit 22 stores various programs, variables, etc. related to the information processing device 2 executed by the processor 23.

<Processor 23>
The processor 23 processes and controls the overall operation related to the information processing device 2. The processor 23 is, for example, a central processing unit (CPU). The processor 23 realizes various functions related to the information processing device 2 by reading out a predetermined program stored in the storage unit 22. That is, information processing by software stored in the storage unit 22 can be specifically realized by the processor 23, which is an example of hardware, and executed as each functional unit included in the processor 23. These will be described in more detail in the next section. The processor 23 is not limited to being single, and may be implemented to have multiple processors 23 for each function. Also, a combination of these may be used.

<User terminal 3>
3 is a block diagram showing a hardware configuration of the user terminal 3. The user terminal 3 includes a communication bus 30, a communication unit 31, a storage unit 32, a processor 33, a display unit 34, and an input unit 35. The communication unit 31, the storage unit 32, the processor 33, the display unit 34, and the input unit 35 are electrically connected via the communication bus 30 inside the user terminal 3. The description of the communication unit 31, the storage unit 32, and the processor 33 will be omitted because they are similar to the description of each unit in the information processing device 2.

<Display unit 34>
The display unit 34 displays a screen of a graphical user interface (GUI) that can be operated by the user. The display unit 34 may be included in the housing of the user terminal 3 or may be attached externally. Specifically, the display unit 34 may be implemented as a display device such as a CRT display, a liquid crystal display, an organic EL display, or a plasma display. It is preferable that these display devices are implemented by selectively using them according to the type of the user terminal 3.

<Input unit 35>
The input unit 35 accepts an operation input made by a user. The operation input is transferred as a command signal to the processor 33 via the communication bus 30. The processor 33 may execute a predetermined control or calculation based on the transferred command signal as necessary. The input unit 35 may be included in the housing of the user terminal 3, or may be externally attached. For example, the input unit 35 may be implemented as a touch panel integrated with the display unit 34. When the input unit 35 is implemented as a touch panel, the user can input a tap operation, a swipe operation, or the like to the input unit 35. As the input unit 35, a switch button, a mouse, a QWERTY keyboard, or the like can be adopted instead of a touch panel.

The information processing device 2 may be in an on-premise form or in a cloud form. As an information processing device 2 in a cloud form, for example, the above-mentioned functions and processes may be provided in the form of SaaS (Software as a Service) or cloud computing.

<Photographing device 4>
4 is a schematic diagram showing the configuration of the imaging device 4. The imaging device 4 has a camera 41, a plurality of lenses 42, a light source 43, a galvanometer mirror 44 (an example of a reflecting member), and a drive circuit 46.

The camera 41 captures multiple images of a target object T placed on the vibration table V. The camera 41 is a high-speed camera (high-speed vision) with a built-in image sensor 41A. The lens 42 is placed between the camera 41 and the galvanometer mirror 44. The light source 43 irradiates light onto the object T.

The galvanometer mirror 44 has a reflective surface that reflects the light reflected from the object T toward the camera 41. Specifically, the galvanometer mirror 44 is a two-axis rotating mirror having two mirrors, an X-axis mirror 44A and a Y-axis mirror 44B. The X-axis mirror 44A and the Y-axis mirror 44B are configured to be able to rotate independently. Note that two galvanometer mirrors 44 are shown in FIG. 4, but these are schematic views of the same galvanometer mirror 44 viewed from different directions. The upper galvanometer mirror 44 in the figure is viewed from above, and the lower galvanometer mirror 44 is viewed from the front.

The driving circuit 46 is a circuit that changes the orientation of the reflecting surface of the galvanometer mirror 44. The driving circuit 46 has a DA converter 46A, a first motor driver 46B, and a second motor driver 46C. The DA converter 46A converts a digital signal from the user terminal 3 into an analog signal and inputs it to the first motor driver 46B and the second motor driver 46C. The first motor driver 46B rotates the X-axis mirror 44A based on the input signal from the user terminal 3 to change the angle of the reflecting surface. The second motor driver 46C rotates the Y-axis mirror 44B based on the input signal from the user terminal 3 to change the angle of the reflecting surface.

In this section, the functional configuration of the present embodiment will be described. Information processing by the software stored in the storage unit 32 is specifically realized by the processor 33, which is an example of hardware, and can be executed as each functional unit included in the processor 33.

Figure 5 is a block diagram showing functions realized by the user terminal 3 (processor 33). Specifically, the user terminal 3 (processor 33) includes a reception unit 331, an adjustment unit 332, and a processing unit 333.

<Reception Unit 331>
The reception unit 331 is configured to acquire various information. For example, the reception unit 331 accepts input of a plurality of images of a vibrating object T continuously captured by the photographing device 4 from a fixed position. Specifically, the reception unit 331 acquires images from the camera 41. Note that the resolution of the images handled by the adjustment unit 332 and the processing unit 333 is on the order of several hundred pixels x several hundred pixels (e.g., 320 pixels x 240 pixels).

<Adjustment unit 332>
The adjustment unit 332 is configured to control the photographing device 4. For example, the adjustment unit 332 calculates the position of an object T in at least one of the multiple images acquired from the photographing device 4, and adjusts the angle of incidence of reflected light from the object T to the camera 41 based on the position of the object T. This makes it possible to increase the clarity of the photographed image itself before the processing unit 333 performs the extraction process.

Specifically, the adjustment unit 332 adjusts the orientation of the reflecting surface of the galvanometer mirror 44 based on the position of the center point of the object T. This makes it possible to adjust the angle of incidence on the camera 41 with a relatively simple configuration without increasing the size of the imaging device 4.

More specifically, the adjustment unit 332 adjusts the orientation of the reflective surface of the galvanometer mirror 44 so that the center point of the object T approaches the center of the angle of view of the camera 41. This makes it possible to calculate the adjustment amount of the orientation of the reflective surface in a simple procedure.

Figure 6 is a flow diagram showing the adjustment process of the angle of incidence on the camera 41. First, the adjustment unit 332 stores the image captured by the camera 41 in memory as a monochrome image (step S110). Next, the adjustment unit 332 smoothes the image using a known method to smooth the numerical changes of adjacent pixels (step S120). After smoothing, the adjustment unit 332 binarizes each pixel to white (pixel value 0) or black (pixel value 255) using a threshold (step S130). The threshold here is, for example, an arbitrary value between 30 and 60 (for example, 45), and pixels with pixel values less than the threshold are white, and pixels with pixel values equal to or greater than the threshold are black.

Next, the adjustment unit 332 extracts the contour that is located near the center of the angle of view and has the largest size from the binarized image as the contour of object T (step S140). After extracting the contour, the adjustment unit 332 sets the center of gravity of the figure defined by the extracted contour as the center point of object T (step S150). The center of gravity is found, for example, as the center point of the circumscribing circle of the contour. Alternatively, the center of gravity may be calculated using image moments. After calculating the center point of object T, the adjustment unit 332 calculates the deviation (vector movement amount) between the center of the image (i.e., the center of the angle of view) and the center point of object T (step S160).

Finally, the adjustment unit 332 adjusts the orientation of the reflecting surface of the galvanometer mirror 44 so that the vector movement amount becomes zero (step S170). Specifically, the adjustment unit 332 inputs voltage values that control the X-axis rotation amount and Y-axis rotation amount of the galvanometer mirror 44 to the first motor driver 46B and the second motor driver 46C.

7 is a schematic diagram illustrating the relationship between the angle of the galvanometer mirror 44 and the position of the center point P of the object T. The relationship between the X-axis rotation voltage V _xk in the kth image (frame) and the X-axis rotation amount θ _xk (deg) is expressed by the following formula (1) using the ratio K between the rotation amount of the X-axis mirror 44A and the input voltage. Note that FIG. 7 shows an example where K=0.5 (K ^-1 =2).

The angle θ _xl (deg) of the incident light from the object T to the X-axis mirror 44A is twice the X-axis rotation amount θ _xk , and is therefore expressed by the following formula (2). Furthermore, from formulas (1) and (2), the following formula (3) is established.

The angle θ _xl of the incident light to the X-axis mirror 44A is determined by the amount of movement X (mm) of the center point P of the object T on the X-axis and the light distance L _x + L _y (mm) from the X-axis mirror 44A to the object T, and therefore the following equation (4) holds.

The coordinates of the center point P of the object T in the image are reset to the center of the angle of view by the rotation of the X-axis mirror 44A by the adjustment unit 332. Therefore, the movement amount X is calculated as the sum of the x coordinates of the center point P for each frame by the following formula (5).

From equations (2), (4), and (5), the voltage value V _x (V) to be transmitted to the first motor driver 46B is calculated by the following equation (6).

The command value for X-axis rotation from the user terminal 3 to the DA converter 46A needs to be an analog value. Therefore, for example, Ax expressed by the following formula (7) is input to the DA converter 46A.

The rotation amount of the Y-axis mirror 44B is calculated in a similar manner. However, in the Y-axis rotation, the light distance from the Y-axis mirror 44B to the object T is L _y (mm). Therefore, for example, A _y expressed by the following formula (8) is input to the DA converter 46A as a command value for Y-axis rotation from the user terminal 3 to the DA converter 46A.

The adjustment unit 332 repeats the adjustment of the angle of incidence on the camera 41 (steps S110 to S170) while the camera 41 is capturing an image. In other words, the adjustment unit 332 causes the image capture device 4 to track the object in real time.

<Processing unit 333>
The processing unit 333 is configured to process various information. For example, the processing unit 333 extracts clear images in which motion blur is smaller than a predetermined standard from a plurality of images captured by the image capture device 4. Specifically, the processing unit 333 executes either a first extraction process or a second extraction process.

The image processed by the processing unit 333 is an image captured while the image capture device 4 (galvanometer mirror 44) is adjusted by the adjustment unit 332. In addition, the first extraction process or the second extraction process by the processing unit 333 may be performed in parallel with the image capture by the image capture device 4.

<First Extraction Process>
The first extraction process is a process of visualizing the amount of movement (vibration trajectory) of the center point of an object and extracting an image with a small amount of movement. In the first extraction process, the processing unit 333 calculates the amount of movement of the center point of the object in multiple images and extracts an image with a small amount of movement as a clear image. In other words, the processing unit 333 uses the amount of movement of the center point of the object as the "magnitude of motion blur" to extract a clear image. This makes it possible to extract an image taken when the movement of the object due to vibration is small.

In detail, the processing unit 333 extracts the contours of the object in each of the multiple images, and sets the center of gravity of the figure defined by the contours as the center point of the object. This makes it possible to calculate the amount of movement of the object in a simple procedure.

Figure 8 is a flow diagram showing the first extraction process. First, the processing unit 333 stores the image captured by the camera 41 in memory as a monochrome image (step S210). Next, the processing unit 333 smoothes the image using a known method to smooth the numerical changes of adjacent pixels (step S220). After smoothing, the processing unit 333 binarizes each pixel to white (pixel value 0) or black (pixel value 255) using a threshold (step S230). The threshold here is, for example, an arbitrary value between 30 and 60 (for example, 45), and pixels with pixel values less than the threshold are white, and pixels with pixel values equal to or greater than the threshold are black.

Next, the processing unit 333 extracts the contour that is located near the center of the angle of view and has the largest size from the binarized image as the contour of the object (step S240). After extracting the contour, the processing unit 333 sets the center of gravity of the figure defined by the extracted contour as the center point of the object (step S250). The method of determining the center of gravity is the same as the adjustment process of the angle of incidence by the adjustment unit 332. After calculating the center point of the object, the processing unit 333 calculates the deviation (vector movement amount) of the center point of the object in two temporally consecutive images, the first image (the k-1th image) and the second image (the kth image) (step S260).

9 is a conceptual diagram showing the movement of the center point P of an object between two images. The movement amount delta Lk in the kth image (frame) is calculated by the following formula (9).

Next, the processing unit 333 determines whether the vector movement amount is equal to or less than a threshold value (e.g., 1 pixel) (step S270). If the vector movement amount is equal to or less than the threshold value (S270: YES), the processing unit 333 determines that the second image of the two images for which the vector movement amount was calculated is a "clear image" (step S280). On the other hand, if the vector movement amount exceeds the threshold value (S270: NO), the processing unit 333 determines that the second image of the two images for which the vector movement amount was calculated is a "non-clear image" (step S290). The vector movement amount threshold value can be set appropriately based on the distance of 1 pixel (mm), the exposure time (ms) of the camera 41, etc.

The processing unit 333 repeats the first extraction process (steps S210 to S290) for all of the multiple images accepted by the accepting unit 331. This classifies the captured images into "clear images" or "non-clear images."

<Second Extraction Process>
The second extraction process is a process for visualizing the image sharpness and extracting images with high sharpness. In the second extraction process, the processing unit 333 calculates an amplitude spectrum by discrete Fourier transform of a plurality of images, and extracts a clear image based on the distribution of the amplitude spectrum. In other words, the processing unit 333 uses the distribution of the amplitude spectrum as the "degree of motion blur" to extract a clear image. This makes it possible to quantify the image sharpness and the criteria for determining the sharpness, thereby improving the accuracy of extracting a clear image.

In detail, the processing unit 333 extracts, as a clear image, an image in which the number of points in the amplitude spectrum whose amplitude is less than a certain value is equal to or greater than a threshold value. This makes it possible to calculate the clarity and the criteria for determining clarity in a simple procedure.

Figure 10 is a flow diagram showing the second extraction process. In the second extraction process, a certain number of images capturing a common object are processed. First, the processing unit 333 stores the images captured by the camera 41 as monochrome images in memory (step S310). Next, the processing unit 333 smoothes the images using a known method to smooth out the numerical value changes of adjacent pixels (step S320).

After smoothing, the processing unit 333 performs a discrete Fourier transform (fast Fourier transform) on the image to calculate an amplitude spectrum (Fourier transform image) (step S330). FIG. 11 is a diagram showing an example of an amplitude spectrum. The amplitude spectrum distribution shown in FIG. 11A is obtained by performing a discrete Fourier transform on the captured image.

After calculating the amplitude spectrum, the processing unit 333 creates an image in which the amplitude spectrum is converted (binarized) to white (pixel value 0) or black (pixel value 255) using a threshold (step S340). The threshold here is an arbitrary value between 70 and 150 (e.g. 110), for example, and pixels with amplitudes below the threshold are white, and pixels with amplitudes above the threshold are black. This results in the black and white image shown in Figure 11B. The white pixels in this image are points with small amplitudes, and the more white pixels there are, the clearer the image before the Fourier transform is.

After binarization, the processing unit 333 applies a mask to the image (step S350). Specifically, the low-frequency and periodic regions of the vibration spectrum are masked in black. This results in the masked black-and-white image shown in FIG. 11C.

The low-frequency regions to be masked are the four corners of the image in FIG. 11A (areas surrounded by dashed circles), and are, for example, regions that are within 16 pixels from the corners of the image (within a circle with a diameter of 32 pixels). The low-frequency regions are noise regions that occur when the contours of an object are blurred. Similarly, the periodic regions to be masked are strips at a certain distance from the four sides of the image in FIG. 11A (areas surrounded by dashed squares), and are, for example, regions that are within 16 pixels from the sides of the image. The periodic regions are regions where white lines appear depending on the vibration direction, shooting background, etc., and where white pixels appear even when the image is not clear.

After the masking process, the processing unit 333 counts the white pixels (points whose amplitude is less than a certain value) contained in the masked black-and-white image (step S360). After counting the white pixels, the processing unit 333 determines whether the number of images in which the white pixels have been counted is equal to or greater than a certain value (e.g., 100 to 1000, specifically, 500) (step S370). If the number of counted images is less than the certain value (S370: NO), the processing unit 333 executes steps S310 to S360 for the next image.

On the other hand, if the number of counted images is equal to or greater than a certain number (S370: YES), the processing unit 333 determines whether the number of white pixels in each image is equal to or greater than a threshold (step S380). If the number of white pixels is equal to or greater than the threshold (S380: YES), the processing unit 333 determines that this image is a "clear image" (step S390). On the other hand, if the number of white pixels is less than the threshold (S380: NO), the processing unit 333 determines that this image is a "non-clear image" (step S400).

The threshold value used to determine whether an image is clear is set, for example, by the following procedure. That is, the number of white pixels in the multiple images counted in S360 is defined as "clearness," and the maximum value of the sharpness of the multiple images is defined as Wmax, and the minimum value is defined as Wmin. The threshold value Wt is calculated as the top 20% of the difference between the maximum and minimum sharpness values, using the following formula (10).

4. Functions The functions of the present embodiment can be summarized as follows: By extracting images with less motion blur than a standard from a plurality of images captured continuously, it is possible to automatically obtain clear images of a vibrating object.

The above describes an embodiment of the present invention, but the present invention is not limited to this and can be modified as appropriate without departing from the technical concept of the invention.

5. Others In the above embodiment, the user terminal 3 performs various storage and control, but multiple external devices may be used instead of the user terminal 3. In other words, various information and programs may be distributed and stored in multiple external devices using block chain technology or the like.

The aspect of this embodiment is not limited to the clear image acquisition system 1, and may be an information processing method or a program. The clear image acquisition method includes each step of the clear image acquisition system 1. The program causes a computer to function as the clear image acquisition system 1.

In the clear image acquisition system 1, the processor 23 of the information processing device 2 may have an adjustment unit 332 and/or a processing unit 333. However, from the viewpoint of reducing the time lag between image acquisition by the image capture device 4 and adjustment of the image capture device 4 by the adjustment unit 332 (feedback to the image capture device 4), it is preferable that the adjustment unit 332 be included in the processor 33 of the user terminal 3.

The adjustment unit 332 may adjust the orientation or position of the camera 41 or the target instead of or in addition to adjusting the orientation of the galvanometer mirror 44. Therefore, the imaging device 4 does not necessarily have to have a galvanometer mirror 44.

It may be provided in the following ways:

(1) A clear image acquisition system comprising a processor configured to execute a receiving step and a processing step, in which the receiving step receives input of a plurality of images of a vibrating object captured successively, and the processing step extracts a clear image from the plurality of images in which motion blur is smaller than a predetermined standard.

(2) In the clear image acquisition system described in (1) above, in the processing step, the amount of movement of the center point of the object in the multiple images is calculated, and the image with the small amount of movement is extracted as the clear image.

(3) In the clear image acquisition system described in (2) above, in the processing step, the contours of the object in each of the multiple images are extracted, and the center of gravity of the figure defined by the contours is set as the center point.

(4) In the clear image acquisition system described in (1) above, in the processing step, an amplitude spectrum is calculated by a discrete Fourier transform of the multiple images, and the clear image is extracted based on the distribution of the amplitude spectrum.

(5) A clear image acquisition system as described in (4) above, in which in the processing step, an image in which the number of points in the amplitude spectrum whose amplitude is less than a certain value is equal to or greater than a threshold value is extracted as the clear image.

(6) A clear image acquisition system according to any one of (1) to (5) above, further comprising a photographing device, the photographing device having a camera for acquiring the plurality of images, and the processor configured to further execute an adjustment step, in which the adjustment step calculates the position of the object in at least one of the plurality of images, and adjusts the angle of incidence of the reflected light from the object to the camera based on the position of the object.

(7) In the clear image acquisition system described in (6) above, the photographing device further includes a reflective member having a reflective surface that reflects the reflected light toward the camera, and in the adjustment step, the orientation of the reflective surface is adjusted based on the position of the center point of the object.

(8) In the clear image acquisition system described in (7) above, in the adjustment step, the orientation of the reflecting surface is adjusted so that the central point approaches the center of the angle of view of the camera.

(9) A method for acquiring a clear image, comprising each step of the clear image acquisition system described in any one of (1) to (8) above.

(10) A program for causing a computer to function as the clear image acquisition system according to any one of (1) to (8) above.
Of course, this is not the case.

Finally, various embodiments of the present disclosure have been described, but these are presented as examples and are not intended to limit the scope of the invention. The novel embodiments can be implemented in various other forms, and various omissions, substitutions, and modifications can be made without departing from the spirit of the invention. The embodiments and modifications thereof are within the scope and spirit of the invention, and are included in the scope of the invention and its equivalents as set forth in the claims.

1: Clear image acquisition system 2: Information processing device 3: User terminal 4: Photographing device 20: Communication bus 21: Communication unit 22: Memory unit 23: Processor 30: Communication bus 31: Communication unit 32: Memory unit 33: Processor 34: Display unit 35: Input unit 41: Camera 41A: Image sensor 42: Lens 43: Light source 44: Galvanometer mirror 44A: X-axis mirror 44B: Y-axis mirror 46: Drive circuit 46A: DA converter 46B: First motor driver 46C: Second motor driver 331: Reception unit 332: Adjustment unit 333: Processing unit

Claims (9)

A clear image acquisition system, comprising:
A processor is provided.
The processor is configured to perform a receiving step and a processing step;
In the receiving step, input of a plurality of images of a vibrating object successively captured is received,
In the processing step, an amplitude spectrum is calculated by a discrete Fourier transform of the multiple images, and a clear image having motion blur smaller than a predetermined standard is extracted from the multiple images based on an image in which the low-frequency region and periodic region of the amplitude spectrum are masked . 2. The clear image acquisition system according to claim 1,
In the processing step, a movement amount of a center point of the object in the plurality of images is calculated, and the image with the smallest movement amount is extracted as the clear image. 3. The clear image acquisition system according to claim 2,
A clear image acquisition system, in which the processing step extracts contours of the object in each of the multiple images, and sets the center of gravity of a figure defined by the contours as the center point. 2. The clear image acquisition system according to claim 1 ,
In the processing step, an image in which the number of points in the amplitude spectrum whose amplitude is less than a certain value is equal to or greater than a threshold value is extracted as the clear image. 2. The clear image acquisition system according to claim 1,
Further comprising an imaging device;
the imaging device has a camera for acquiring the plurality of images;
The processor is further configured to perform an adjustment step;
A clear image acquisition system, in which the adjustment step calculates the position of the object in at least one of the multiple images, and adjusts the angle of incidence of reflected light from the object to the camera based on the position of the object. 6. The clear image acquisition system according to claim 5 ,
the photographing device further includes a reflecting member having a reflecting surface that reflects the reflected light toward the camera;
A clear image acquisition system, wherein the adjustment step adjusts the orientation of the reflective surface based on the position of the center point of the object. 7. The clear image acquisition system according to claim 6 ,
In the adjustment step, the orientation of the reflecting surface is adjusted so that the central point approaches the center of the angle of view of the camera. A method for acquiring a clear image, comprising:
A method for obtaining a clear image, comprising the steps of the system for obtaining a clear image according to any one of claims 1 to 7 . A program,
A program for causing a computer to function as the clear image acquisition system according to any one of claims 1 to 7 .