Inspection method, inspection device, and program

Abstract

An inspection method includes: an acquisition step (S12) of acquiring a one-dimensional brightness distribution feature by applying image processing to the brightness of an inspection image of a pixel region of a display panel captured by an imaging device, the image processing being compressed to a one-dimensional brightness; a generation step (S13) for generating a spectral intensity distribution feature by performing Fourier transform processing on the one-dimensional brightness distribution feature; a calculation step (S14) for calculating the magnification of the imaging device on the basis of one or more peak positions included in the spectral intensity distribution characteristics on the basis of the periodic structure of the pixels reflected in the pixel region; and an estimation step (S15) for estimating a current focal position, which is the focal position of the imaging device in the inspection image, on the basis of magnification information indicating the relationship between the focal position and magnification in the imaging device, and the calculated magnification.

Description

Technical Field

[0001] The present disclosure relates to an inspection method, an inspection device, and a program. Background Art

[0002] In the production process of display panels, various inspections are performed to ensure product quality, among which image inspection accounts for a large proportion.

[0003] In recent years, in image inspection, in addition to the desire to improve the judgment accuracy of operators, the judgment accuracy of automatic inspection has also been desired, and thus high-quality images are required.

[0004] In order to perform image inspection with high-quality images, a high-quality imaging element or optical system is generally used in the inspection device. In addition, in order to obtain high-quality images, an autofocus mechanism related to the focus accuracy of the image is also important, and an autofocus mechanism such as contrast detection AF is used in the inspection device (for example, Patent Document 1).

[0005] Contrast detection AF is a method of searching for the contrast peak of an image while changing the focus position. That is, in contrast detection AF, dedicated AF hardware is not required, and the image itself is used for automatic focusing. Therefore, contrast detection AF has the advantage of high focus accuracy.

[0006] (Prior art literature)

[0007] (Patent Document)

[0008] Patent Document 1: Japanese Patent No. 3316684 Summary of the invention

[0009] Problems to be solved by the invention

[0010] However, although the contrast detection AF used in Patent Document 1 has the advantage of high focus accuracy, it has the disadvantage of slow operation speed because it does not know whether the direction of the camera position with blurred focus is in the + (positive) direction or the - (negative) direction relative to the in-focus position. Since the beat is an important factor in the inspection device, the use of contrast detection AF in the inspection device will become a major disadvantage.

[0011] In addition to contrast detection AF, laser AF is also known as an autofocus mechanism. Laser AF has the advantage of fast operation speed because it irradiates laser light onto the panel to directly measure the distance to the surface of the panel. However, laser AF requires dedicated AF hardware, and high-precision AF hardware has the disadvantage of being expensive. And when the inspection device uses laser AF, since the distance between the laser detector and the surface of the display panel is measured, there will also be problems such as the need to calibrate the distance between the optical system used to convert the focus position and the surface of the display panel.

[0012] In view of the above circumstances, an object of the present disclosure is to provide an inspection method and the like that can perform processing for rapid autofocusing without requiring dedicated hardware.

[0013] Means for solving problems

[0014] In order to achieve the above-mentioned purpose, an inspection method involved in one embodiment of the present invention is a display panel inspection method performed by a computer, comprising the following steps: an acquisition step, in which a one-dimensional brightness distribution feature is acquired by applying image processing to compress the brightness of an inspection image of a pixel area of ​​the display panel captured by a camera device into a one-dimensional brightness, wherein the one-dimensional brightness is compressed with a vertical direction of an arrangement direction of a plurality of sub-pixels constituting each pixel as an axis, and the each 1 pixel is a pixel among a plurality of pixels constituted by a plurality of sub-pixels; a generation step, in which a spectrum intensity distribution feature is generated by performing Fourier transform processing on the one-dimensional brightness distribution feature; a calculation step, in which a magnification of the camera device is calculated based on one or more peak positions included in the spectrum intensity distribution feature according to the fact that the plurality of pixels in the pixel area are formed in a periodic structure; and an estimation step, in which a current focus position is estimated based on magnification information showing a relationship between a focus position and a magnification in the camera device and the calculated magnification, wherein the current focus position is the focus position of the camera device in the inspection image.

[0015] In this way, the current focus position of the imaging device 20 in the inspection image can be estimated by only calculation processing without the need for dedicated hardware. In addition, from the performance of computers equipped with processors in recent years, it is possible to quickly perform brightness compression on the inspection image captured by the imaging device 20 and compress it into one dimension and perform Fourier transform processing.

[0016] Therefore, according to the inspection method of this aspect, processing for rapid autofocusing can be performed without the need for dedicated hardware.

[0017] Furthermore, in the calculation step, it may be that the peak position of the fundamental frequency among the one or more peak positions is estimated to be the peak position corresponding to the structure of 1 pixel unit of the pixel area reflected in the inspection image, thereby calculating the magnification of the camera device based on the peak position of the fundamental frequency.

[0018] Furthermore, for example, in the generating step, the spectrum intensity distribution feature may be generated by performing two Fourier transform processes on the one-dimensional brightness distribution feature.

[0019] And regarding the magnification information, for example, when the value of the basic frequency obtained by Fourier transforming the one-dimensional brightness distribution characteristics of each of the multiple focus positions of the camera device is used as the magnification, the magnification information is information showing the relationship between the magnification at this time and the multiple focus positions, and the one-dimensional brightness distribution characteristics are the one-dimensional brightness distribution characteristics of the image of the pixel area of ​​the display panel captured by the camera device.

[0020] And for example, the inspection method may also include an adjustment step, in which the movement amount of the camera device required for focusing is calculated based on the estimated current focus position and the magnification information, and the position of the camera device is adjusted using the movement amount.

[0021] Furthermore, in order to achieve the above-mentioned purpose, an inspection device involved in one embodiment of the present disclosure is an inspection device for a display panel, the inspection device comprising: an acquisition unit, which acquires a one-dimensional brightness distribution feature by applying image processing to compress the brightness of an inspection image of a pixel area of ​​the display panel captured by a camera device into a one-dimensional brightness, wherein the one-dimensional brightness is compressed with a direction perpendicular to the arrangement direction of a plurality of sub-pixels constituting each pixel as an axis, and wherein each pixel is a pixel among a plurality of pixels constituted by a plurality of sub-pixels; a generation unit, which generates a spectral intensity distribution feature by performing Fourier transform processing on the one-dimensional brightness distribution feature; a calculation unit, which calculates a magnification of the camera device based on one or more peak positions included in the spectral intensity distribution feature, according to the fact that the plurality of pixels in the pixel area are formed in a periodic structure; and an estimation unit, which estimates a current focus position based on magnification information showing a relationship between a focus position and a magnification in the camera device and the calculated magnification, wherein the current focus position is the focus position of the camera device in the inspection image.

[0022] Furthermore, in order to achieve the above-mentioned purpose, a program involved in one embodiment of the present disclosure is a program for causing a computer to execute a method for inspecting a display panel, causing the computer to execute the following steps: an acquisition step, obtaining a one-dimensional brightness distribution feature by applying image processing to compress the brightness of an inspection image of a pixel area of ​​the display panel captured by an imaging device into a one-dimensional brightness, wherein the one-dimensional brightness is compressed with a direction perpendicular to the arrangement direction of a plurality of sub-pixels constituting each pixel as an axis, and wherein each pixel is a pixel among a plurality of pixels constituted by a plurality of sub-pixels; a generation step, generating a spectrum intensity distribution feature by performing Fourier transform processing on the one-dimensional brightness distribution feature; a calculation step, calculating a magnification of the imaging device based on one or more peak positions included in the spectrum intensity distribution feature according to the fact that the plurality of pixels in the pixel area are formed in a periodic structure; and an estimation step, estimating a current focus position based on magnification information showing a relationship between a focus position and a magnification in the imaging device and the calculated magnification, wherein the current focus position is the focus position of the imaging device in the inspection image.

[0023] In addition, these general or specific methods can be implemented by devices, methods, integrated circuits, computer programs, or computer-readable recording media such as CD-ROMs, or by any combination of systems, methods, integrated circuits, computer programs, and recording media.

[0024] Effects of the Invention

[0025] According to the present disclosure, it is possible to provide a testing method and the like that can perform autofocus quickly with high focus accuracy without requiring dedicated hardware. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 A schematic configuration of an inspection system including an inspection device according to an embodiment is shown.

[0027] Figure 2 An example of the hardware configuration of a computer that realizes the functions of the inspection device according to the embodiment by software is shown.

[0028] Figure 3 This is a block diagram showing an example of the functional configuration of the inspection device according to the embodiment.

[0029] Figure 4 An example of an inspection image of a pixel region of a display panel according to the embodiment is shown.

[0030] Figure 5 Shows the Figure 4The one-dimensional brightness distribution characteristics of the inspection image are shown when the brightness is compressed on the X-axis.

[0031] Figure 6 Shows the Figure 4 The one-dimensional brightness distribution characteristics of the inspection image are shown when the brightness is compressed on the Y axis.

[0032] Fig. 7A This is another example of the inspection image of the pixel region of the display panel according to the embodiment.

[0033] Figure 7B Shows the Fig. 7A The one-dimensional brightness distribution characteristics of the inspection image are shown when the brightness is compressed on the Y axis.

[0034] Figure 8 This is a diagram for explaining an example of one-dimensional brightness distribution characteristics after fast Fourier transform processing is performed by the generating unit involved in the embodiment.

[0035] Fig. 9 Shows the Figure 6 The one-dimensional brightness distribution characteristics are the spectral intensity distribution characteristics when the fast Fourier transform is performed twice.

[0036] Fig.10 This is a diagram for explaining another example of the one-dimensional brightness distribution characteristics after the fast Fourier transform process is performed by the generating unit involved in the embodiment.

[0037] Fig.11 Shows the Figure 7B The one-dimensional brightness distribution characteristics are the spectral intensity distribution characteristics when the fast Fourier transform is performed twice.

[0038] Fig.12 An example of magnification information when the value of the fundamental frequency according to the embodiment is used as the magnification is shown.

[0039] Fig.13 This is a flowchart showing the operation of the inspection device according to the embodiment. DETAILED DESCRIPTION

[0040] The following is a detailed description of the embodiments of the present disclosure using the accompanying drawings. In addition, the embodiments to be described below are all specific examples of the present disclosure. The numerical values, shapes, materials, specifications, constituent elements, configuration positions of constituent elements, connection methods, steps, order of steps, etc. shown in the following embodiments are all examples, and their main purpose is not to limit the present disclosure. In addition, the constituent elements of the following embodiments that are not recorded in the independent technical solutions of the present disclosure will be described as arbitrary constituent elements. In addition, the various figures are not rigorous illustrations. In each figure, the same figure mark is given to substantially the same structure, and there are cases where repeated descriptions are omitted or simplified.

[0041] (Implementation Method)

[0042] Hereinafter, the inspection device and the like according to the present embodiment will be described.

[0043] [1. Check the system]

[0044] Hereinafter, the inspection device 10 according to the present embodiment will be described with reference to the drawings.

[0045] Figure 1 The schematic configuration of an inspection system including the inspection device 10 according to the present embodiment is shown.

[0046] Figure 1 The inspection system shown includes an inspection device 10 , an imaging device 20 , a mounting table 21 , and a mounting table driving unit 22 .

[0047] The inspection device 10 is a device for performing image inspection using an inspection image obtained by photographing a pixel area of ​​a display panel 30. Here, the display panel 30 is a liquid crystal display panel, an organic EL display panel, etc., and may be a rigid panel or a flexible panel. In the pixel area of ​​the display panel 30, a plurality of pixels are arranged in a matrix. Each of the plurality of pixels is composed of a plurality of sub-pixels such as RGB sub-pixels, for example.

[0048] The camera device 20 is composed of an optical system that focuses the lens by a full-group focus method or the like, and photographs the pixel area of ​​the display panel 30. In an optical system such as a full-group focus method, the focal position and the magnification ratio have a strong correlation. In addition, the camera device 20 may also be composed of an optical system that focuses the lens by an internal focus method or the like, and photographs the pixel area of ​​the display panel 30. In an optical system such as an internal focus method, the focal position and the magnification ratio also have a strong correlation. The magnification ratio is the ratio of the size of the image formed on the image plane to the actual size of the subject. Furthermore, the camera device 20 is Figure 1 As shown, a certain distance is maintained from the display panel 30, such as Figure 1As shown in (a) to (c), the focus position is adjusted by moving. Figure 1 The following positions are shown as an example: Figure 1 (b) is the best focus position, i.e. the focus position. Figure 1 (a) and (c) are the locations where the focus is blurred.

[0049] The imaging device 20 acquires an inspection image of the display panel 30 by capturing an image of a pixel region of the display panel 30. Figure 1 By moving the position of (a), (b) or (c) shown, the focus position of the optical system of the imaging device 20 can be adjusted. In addition, although the imaging device 20 is controlled by the inspection device 10, it can also be controlled by another computer.

[0050] The mounting table 21 holds the display panel 30 .

[0051] The stage drive unit 22 is composed of a ball screw, a guide rail, and a motor, and moves the stage 21 relative to the imaging device 20. The stage drive unit 22 is controlled by the inspection device 10, but may be controlled by another computer.

[0052] [1-1. Hardware Configuration of Inspection Device 10]

[0053] Before describing the functional configuration of the inspection device 10 according to the present embodiment, Figure 2 An example of the hardware configuration of the inspection device 10 according to the present embodiment will be described.

[0054] Figure 2 An example of the hardware configuration of the computer 1000 that realizes the functions of the inspection device 10 according to the present embodiment by software is shown.

[0055] Computer 1000 Figure 2 As shown, a computer includes an input device 1001, an output device 1002, a CPU 1003, an internal storage 1004, a RAM 1005, a GPU 1006, a reading device 1007, a transceiver 1008, and a bus 1009. The input device 1001, the output device 1002, the CPU 1003, the internal storage 1004, the RAM 1005, the GPU 1006, the reading device 1007, and the transceiver 1008 are connected via the bus 1009.

[0056] The input device 1001 is a device that becomes a user interface such as input keys, a touch pad, a touch screen display, etc., and accepts operations from the user. In addition, in addition to accepting contact operations from the user, the input device 1001 can also be configured to accept operations performed by voice or remote operations such as a remote controller.

[0057] The output device 1002 can also serve as the input device 1001 and is composed of a touch panel or a touch screen display, etc., to notify the user of information that the user should know.

[0058] The internal storage 1004 is a flash memory or the like. In addition, at least one of a program for realizing the functions of the inspection device 10 and an application utilizing the functions of the inspection device 10 may be stored in advance in the internal storage 1004. In addition, the internal storage 1004 may store the sequence of image processing described later, the formula for Fourier transform (FFT) processing, the formula for fast Fourier transform (FFT) processing, the sequence including the program, the sequence of calculating the magnification of the camera 20, the sequence of estimating the current focus position of the camera 20, the magnification information of the camera 20, and the like.

[0059] RAM 1005 is a random access memory (Random Access Memory) and is used to store data and the like when executing a program or an application.

[0060] The GPU 1006 is a graphics processing unit that copies programs, applications, and data stored in the internal storage 1004 to a dedicated RAM built into the GPU and performs graphics processing according to instructions in the programs or applications.

[0061] The reading device 1007 reads information from a recording medium such as a USB (Universal Serial Bus) memory. The reading device 1007 reads the program or / and application from the recording medium recording the program or application, and stores the program or application in the internal storage 1004.

[0062] The transceiver 1008 is a communication line for wireless or wired communication. The transceiver 1008 can communicate with a server device connected via a network, download the above-mentioned program and / or application from the server device, and store it in the internal storage 1004.

[0063] CPU 1003 is a central processing unit (Central Processing Unit), which copies the program and application stored in the internal storage 1004 to RAM 1005, and sequentially reads and executes the instructions in the program and / or application from RAM 1005.

[0064] [1-2. Functional Configuration of Inspection Device 10]

[0065] Next, use Figure 3 Each functional configuration of the inspection device 10 according to the present embodiment will be described.

[0066] Figure 3 This is a block diagram showing an example of the functional configuration of the inspection device 10 according to the present embodiment.

[0067] Inspection device 10 Figure 3 As shown, the inspection device 10 includes an acquisition unit 101, a generation unit 102, a calculation unit 103, an estimation unit 104, and a focus adjustment unit 105. The focus adjustment unit 105 is not essential in the inspection device 10, and may be provided externally.

[0068] [1-2-1. Acquisition unit 101]

[0069] The acquisition unit 101 acquires an inspection image of a pixel area of ​​the display panel 30 captured by the camera device 20. The acquisition unit 101 acquires a one-dimensional brightness distribution feature by applying image processing to the brightness of the acquired inspection image, wherein the image processing is a process of compressing the brightness of the acquired inspection image into a one-dimensional brightness with the vertical direction of the arrangement direction of the plurality of sub-pixels constituting one pixel of the plurality of pixels as an axis. In addition, each of the plurality of pixels is composed of a plurality of sub-pixels. Furthermore, the acquisition unit 101 can realize the above-mentioned image processing function and acquisition function by executing a control program stored in a memory by a processor in a computer that realizes the functions of the inspection device 10.

[0070] Figure 4 is an example of an inspection image of a pixel region of the display panel 30 according to the present embodiment. Figure 4 An example of an inspection image when the image is in focus is shown as an inspection image 61. In the pixel area shown in the inspection image 61, a plurality of pixels (pixels) and a plurality of sub-pixels (sub-pixels) are shown. Each of the plurality of pixels is a constituent unit of the image displayed by the display panel 30, and the plurality of sub-pixels are points that further divide a pixel into a single color such as RGB. That is, in Figure 4The inspection image 61 shows a pixel area of ​​the display panel 30, which is composed of a plurality of pixels that function as one pixel by gathering sub-pixels (sub-pixels) that become monochromatic dots such as RGB. Figure 4 In the example shown, one pixel is formed by vertically long rectangular sub-pixels whose width of the B (Blue) sub-pixel is larger than that of the R (Red) and G (Green) sub-pixels, arranged in a matrix. Figure 4 The pixel region shown in the inspection image 61 is formed by a periodic structure of a plurality of pixels. Hereinafter, the arrangement direction of the plurality of sub-pixels constituting one pixel is referred to as the X-axis, that is, the arrangement direction of the plurality of sub-pixels constituting one pixel among the plurality of pixels each composed of the plurality of sub-pixels is referred to as the X-axis. Furthermore, the vertical direction of the arrangement direction of the plurality of sub-pixels constituting one pixel is referred to as the Y-axis.

[0071] Figure 5 Shows the Figure 4 The one-dimensional brightness distribution feature 62 of the inspection image 61 is shown when the brightness is compressed on the X-axis. Figure 6 Shows the Figure 4 The one-dimensional brightness distribution feature 63 of the inspection image 61 shown is a result of compressing the brightness on the Y axis. Figure 5 as well as Figure 6 In the figure, the vertical axis is brightness, or more precisely, the sum of brightness. Figure 5 In the figure, the horizontal axis represents the X coordinate, that is, the pixel position on the X axis. Figure 6 In the above, the horizontal axis represents the Y coordinate, that is, the pixel position on the Y axis. In addition, the compression on the X axis means that at each pixel position on the X axis, the sum of the brightness of all pixels along the Y axis of the pixel position is calculated. Similarly, the compression on the Y axis means that at each pixel position on the Y axis, the sum of the brightness of all pixels along the X axis of the pixel position is calculated.

[0072] In this embodiment, the acquisition unit 101 acquires, for example, Figure 4 The inspection image 61 shown in FIG. 1 is used as an inspection image of the pixel region of the display panel 30 captured by the camera device 20. The acquisition unit 101 applies image processing to compress the brightness of the acquired inspection image 61 into a one-dimensional brightness on the Y axis, thereby acquiring, for example, Figure 6 The one-dimensional brightness distribution characteristic 63 is shown.

[0073] Here, the reason why the brightness of the inspection image 61 is compressed on the Y axis instead of on the X axis will be described using Figure 5 The one-dimensional brightness distribution characteristics 62 and Figure 6 The one-dimensional brightness distribution characteristic 63 shown is used for explanation.

[0074] Figure 5 The one-dimensional brightness distribution feature 62 shown is that the brightness is compressed in the X-axis, that is, the arrangement direction of the multiple sub-pixels constituting one pixel. The arrangement of one pixel unit is periodic, while the arrangement of multiple sub-pixels in one pixel unit (that is, the arrangement of sub-pixels along the X-axis) is asymmetric. Figure 5 The one-dimensional brightness distribution feature 62 shown in the figure becomes a complex shape. Figure 6 The one-dimensional brightness distribution feature 63 shown is that the brightness is compressed in the direction perpendicular to the Y axis, that is, the arrangement direction of the plurality of sub-pixels constituting one pixel. Since the arrangement of the pixel units along the Y axis is the same, Figure 6 The one-dimensional brightness distribution feature 63 shown becomes a simple shape. That is, in the generator 102 described later, the Fourier transform process (fast Fourier transform process) is performed. If you want to know what kind of shape (waveform) is synthesized to form the shape (waveform) of the one-dimensional brightness distribution feature, it is hoped that the one-dimensional brightness distribution feature has a simple shape. In addition, when the unit pitch is equal, that is, when the widths of the sub-pixels R, G, and B are equal, the brightness can be compressed on the X axis or on the Y axis.

[0075] In this way, the acquisition unit 101 can acquire the one-dimensional brightness distribution feature based on the inspection image of the pixel region of the display panel 30 captured by the imaging device 20 .

[0076] Furthermore, for comparison, a case where a blurred inspection image, that is, an out-of-focus inspection image is acquired will be described.

[0077] Fig. 7A This is another example of the inspection image of the pixel region of the display panel 30 according to the present embodiment. Figure 7B The Y axis shows Fig. 7A The one-dimensional brightness distribution feature 66 of the inspection image 65 is shown when the brightness is compressed.

[0078] That is, the acquisition unit 101 acquires, for example, Fig. 7A The inspection image 65 with out-of-focus shown in the figure is used as the inspection image of the pixel area of ​​the display panel 30 captured by the camera device 20. Then, the acquisition unit 101 applies image processing to compress the brightness of the acquired inspection image 65 into one-dimensional brightness on the Y axis, thereby acquiring, for example, Figure 7B The one-dimensional brightness distribution characteristic 66 is shown. Figure 7B The shape of the one-dimensional brightness distribution feature 66 is similar to Figure 6 It can be seen that the shape of the one-dimensional brightness distribution feature 63 shown is different.

[0079] [1-2-2. Generating unit 102]

[0080] The generator 102 generates a spectrum intensity distribution feature by performing Fourier transform processing on the one-dimensional brightness distribution feature. The generator 102 can realize the Fourier transform processing and generation function by executing a control program stored in a memory by a processor in a computer realizing the functions of the inspection device 10 .

[0081] In addition, although the following description takes the case of using fast Fourier transform processing as an example, the present invention is not limited to this, and any algorithm may be used as long as it is Fourier transform processing.

[0082] Furthermore, the generation unit 102 is not limited to performing the fast Fourier transform process once on the one-dimensional brightness distribution feature acquired by the acquisition unit 101, and the fast Fourier transform process may be performed twice. More specifically, the generation unit 102 may perform the fast Fourier transform process twice on the one-dimensional brightness distribution feature acquired by the acquisition unit 101 to generate the spectrum intensity distribution feature. Here, the spectrum intensity distribution feature may also be generated by performing the fast Fourier transform process multiple times.

[0083] Figure 8 This is a diagram for explaining an example of one-dimensional brightness distribution characteristics after fast Fourier transform processing is performed by the generator 102 according to the present embodiment. Figure 8 (a) shows Figure 6 One-dimensional brightness distribution characteristics 63, Figure 8 (b) shows the Figure 8 The one-dimensional brightness distribution characteristic 63 of (a) is a spectrum intensity distribution characteristic 63a when a fast Fourier transform process is performed once. Fig. 9 Shown for Figure 6 The spectral intensity distribution characteristic 63b is obtained when the one-dimensional brightness distribution characteristic 63 is subjected to two fast Fourier transform processes.

[0084] In this embodiment, the generating unit 102 is for example Figure 8 The one-dimensional brightness distribution characteristic 63 shown in (a) is subjected to fast Fourier transform processing once or twice.

[0085] For example, Figure 8 The shape of the one-dimensional brightness distribution feature 63 shown in (a) is regarded as a waveform, and a fast Fourier transform is performed on it to generate Figure 8 The spectral intensity distribution characteristic 63a shown in (b) is shown in FIG. Figure 8 The shape of the one-dimensional brightness distribution feature 63 shown in (a) is regarded as a waveform and subjected to two fast Fourier transform processes to generate Fig. 9The spectral intensity distribution characteristic 63b is shown.

[0086] Here, a case where the one-dimensional brightness distribution feature 66 of the inspection image 65 which is out of focus, that is, out of focus, is subjected to the fast Fourier transform process once or twice will also be described.

[0087] Fig.10 This is a diagram for explaining another example of the one-dimensional brightness distribution characteristics after the fast Fourier transform process is performed by the generator 102 according to the present embodiment. Fig.10 (a) shows Figure 7B The one-dimensional brightness distribution characteristics of 66, Fig.10 (b) shows the Fig.10 The spectral intensity distribution characteristic 66a is obtained when the one-dimensional brightness distribution characteristic 66 of (a) is subjected to a single fast Fourier transform process. Fig.11 Shown for Figure 7B The spectral intensity distribution characteristic 66b is obtained when the one-dimensional brightness distribution characteristic 66 is subjected to two fast Fourier transform processes.

[0088] For example, Fig.10 The shape of the one-dimensional brightness distribution feature 66 shown in (a) is regarded as a waveform, and a fast Fourier transform is performed on it to generate Fig.10 The spectral intensity distribution characteristic 66a shown in (b) is shown in FIG. Figure 8 The shape of the one-dimensional brightness distribution feature 63 shown in (a) is regarded as a waveform and subjected to two fast Fourier transform processes to generate Fig.11 The spectral intensity distribution characteristic 66b is shown.

[0089] exist Fig.10 If the spectral intensity distribution characteristic 66a shown in (b) is Figure 8 By comparing the spectral intensity distribution feature 63a shown in (b) with the waveform of the power spectrum without high-frequency components, it can be seen.

[0090] Thus, the generator 102 can generate a spectral intensity distribution feature by treating the shape of the one-dimensional brightness distribution feature of the inspection image as a waveform and performing fast Fourier transform processing. From the generated spectral intensity distribution feature, it can be seen that the waveform of the one-dimensional brightness distribution feature of the inspection image includes frequency components and their amplitudes.

[0091] [1-2-3. Calculation unit 103]

[0092] The calculation unit 103 calculates the magnification of the imaging device 20 from one or more peak positions included in the spectrum intensity distribution characteristics based on the fact that a plurality of pixels are formed in a periodic structure in the pixel region of the display panel 30. More specifically, the calculation unit 103 estimates that the peak position of the fundamental frequency among the one or more peak positions is the peak position corresponding to the structure of one pixel unit of the pixel region projected in the inspection image, thereby calculating the magnification of the imaging device 20 based on the peak position of the fundamental frequency. In addition, the calculation unit 103 can realize the calculation function by, for example, executing a control program stored in a memory by a processor in a computer that realizes the function of the inspection device 10.

[0093] In this embodiment, the calculation unit 103 calculates the magnification of the imaging device 20 based on the frequency of the waveform included in the spectral intensity distribution characteristics generated by the generation unit 102 and the size of the power spectrum, and the structural properties of the pixel area of ​​the display panel 30. The magnification is the ratio of the size of the image projected on the image plane to the actual size of the object. That is, in this embodiment, the magnification is the ratio of the size of the pixel area projected in the inspection image captured by the imaging device 20 to the size of the pixel in the actual pixel area of ​​the display panel 30.

[0094] More specifically, the calculation unit 103 performs the calculation according to Figure 8 Among the one or more waveforms included in the spectrum intensity distribution feature 63a of (b), the waveform represented by the dotted circle of a is the waveform having the lowest frequency component, and the frequency of the waveform represented by the dotted circle of a is estimated to be the fundamental frequency.

[0095] In this Figure 8 As shown in (a), the one-dimensional brightness distribution feature 63 is composed of 1000 data (1000 pixels). Figure 8 As shown in (b), the peak value of the waveform of the fundamental frequency of the spectrum intensity distribution feature 63a, that is, the waveform represented by the dotted circle of a, is 7. Since the calculation unit 103 can calculate 1000 / 7=143, it is estimated that Figure 8 The waveform corresponding to the 143 data period in the one-dimensional brightness distribution characteristic 63 shown in (a) is the waveform represented by the dotted circle of a. Figure 4 FIG. 6 shows a pixel region having a periodic structure in which eight pixels are arranged in the Y-axis direction of the inspection image 61. Figure 8 In the one-dimensional brightness distribution feature 63 shown in (a), eight waveforms represented by dotted circles of a are shown. It can be known from this that the waveform represented by the dotted circle of a is a waveform corresponding to 1 pixel unit. Therefore, it can be known that in the spectrum intensity distribution feature 63a, the waveform of the fundamental frequency represented by the dotted circle of a is a waveform corresponding to 1 pixel unit.

[0096] Likewise, for example in Figure 8 The spectral intensity distribution characteristic 63a of (b) estimates that the waveform represented by the dotted circle in b is Figure 8 The waveform represented by the dotted circle b in the one-dimensional brightness distribution feature 63 shown in (a) of FIG. More specifically, Figure 8 As shown in (a), the one-dimensional brightness distribution feature 63 is composed of 1000 data (data of 100 pixels). Figure 8 As shown in (b), in the spectrum intensity distribution feature 63a, the value of the peak position of the waveform indicated by the dotted circle in b is 14. Since the calculation unit 103 can calculate 1000 / 14=71, it is estimated that Figure 8 In the one-dimensional brightness distribution characteristic 63 shown in (a), the waveform corresponding to 71 data cycles is the waveform represented by the dotted circle b. Figure 8 In (a), the waveform represented by the dotted circle of b corresponds to the two raised waveforms included in the waveform represented by the dotted circle of a. Figure 8 In the spectrum intensity distribution characteristic 63a of (b), the frequency of the peak position of the waveform indicated by the dotted circle in b is twice the fundamental frequency.

[0097] Similarly, the calculation unit 103 estimates that Figure 8 The waveform represented by the dotted circle c in the spectrum intensity distribution characteristic 63a of (b) is Figure 8 The waveform represented by the dotted circle c in the one-dimensional brightness distribution characteristic 63 shown in (a) of FIG. Figure 8 In (a), the waveform indicated by the dotted circle c corresponds to the waveform of the three protruding peaks included in the waveform indicated by the dotted circle c. Figure 8 In the spectrum intensity distribution characteristic 63a of (b), the frequency of the peak position of the waveform indicated by the dotted circle c is three times the fundamental frequency.

[0098] In this way, the calculation unit 103 can calculate the fundamental frequency based on the peak positions of one or more waveforms included in the spectrum intensity distribution characteristics, and can calculate the data period of one pixel unit based on the structural properties of the periodic structure of pixels in the pixel area of ​​the display panel 30. Based on this, the calculation unit 103 can calculate the size of the pixels in the pixel area reflected in the inspection image captured by the imaging device 20, and can therefore calculate the magnification using the size of the pixels in the actual pixel area of ​​the display panel 30.

[0099] In the present embodiment, the calculation unit 103 may calculate the amplification factor using the value of the peak position of the fundamental frequency obtained by performing one or two fast Fourier transform processes on the one-dimensional brightness distribution feature.

[0100] More specifically, the calculation unit 103 can obtain the one-dimensional brightness distribution feature by performing a fast Fourier transform process. Figure 8 The value 7 of the fundamental frequency of the spectrum intensity distribution feature 63a of (b) is calculated as the magnification. In addition, the calculation unit 103 may also use the value obtained by performing two fast Fourier transform processes on the one-dimensional brightness distribution feature. Fig. 9 The value of the fundamental frequency of the spectrum intensity distribution characteristic 63b is calculated as the magnification. Fig. 9 In the spectrum intensity distribution characteristic 63b, the waveform represented by the dotted circle d is the waveform having the lowest frequency component, and the frequency of the peak position of the waveform represented by the dotted circle d is the fundamental frequency.

[0101] Although the spectral intensity distribution feature 63a of the in-focus inspection image 61 has been described above, the spectral intensity distribution feature 66a of the out-of-focus inspection image 65 is also the same, which will be described below.

[0102] The calculation unit 103 is, for example, Fig.10 Among the one or more waveforms included in the spectrum intensity distribution feature 66a of (b), the waveform represented by the dotted circle of a has the lowest frequency component, so the frequency of the waveform represented by the dotted circle of a can be estimated as the fundamental frequency.

[0103] More specifically, if Fig.10 As shown in (a) of FIG. 1 , the one-dimensional brightness distribution feature 66 is composed of 1000 data (data of 100 pixels). Fig.10 As shown in (b), the value of the peak position of the waveform of the fundamental frequency represented by the dotted circle of a in the spectrum intensity distribution feature 66a is 7. Since the calculation unit 103 can calculate 1000 / 7=143, it can be estimated that Fig.10 The one-dimensional brightness distribution feature 66 shown in (a) corresponds to the waveform of the 143 data cycle, which is represented by the dotted circle of a. Fig.10 The waveform indicated by the dotted circle a in (a) is a waveform corresponding to one pixel unit. From this, it can be known that the waveform of the fundamental frequency indicated by the dotted circle a in the spectrum intensity distribution feature 66a is a waveform corresponding to one pixel unit.

[0104] Similarly, for example, it can be estimated that Fig.10The spectral intensity distribution characteristic 66a of (b) is represented by the dotted circle in b. Fig.10 The one-dimensional brightness distribution characteristic 66 shown in (a) is represented by the waveform of the dotted circle in b. More specifically, as Fig.10 As shown in (a) of FIG. 1 , the one-dimensional brightness distribution feature 66 is composed of 1000 data (data of 100 pixels). Fig.10 As shown in (b), the value of the peak position of the waveform indicated by the dotted circle in b in the spectrum intensity distribution feature 66a is 14. Since the calculation unit 103 can calculate 1000 / 14=71, Fig.10 In the one-dimensional brightness distribution feature 66 shown in (a), the waveform that can be estimated to be equivalent to 71 data cycles is the waveform represented by the dotted circle b. Fig.10 In (a), the waveform indicated by the dotted circle of b corresponds to the two raised waveforms included in the waveform indicated by the dotted circle of a. Fig.10 In the spectrum intensity distribution characteristic 66a of (b), the frequency of the peak position of the waveform indicated by the dotted circle in b is twice the fundamental frequency.

[0105] Thus, regarding the fundamental frequency, the spectral intensity distribution feature 66a of the out-of-focus inspection image 65 can be processed in the same manner as the spectral intensity distribution feature 63a of the in-focus inspection image 61. That is, the calculation unit 103 can calculate the magnification based on the spectral intensity distribution feature 66a of the out-of-focus inspection image 65.

[0106] In addition, the calculation unit 103 can also obtain the one-dimensional brightness distribution feature by performing a fast Fourier transform process. Fig.10 The value 7 of the fundamental frequency of the spectrum intensity distribution feature 66a of (b) is calculated as the magnification. In addition, the calculation unit 103 may also use the value obtained by performing two fast Fourier transform processes on the one-dimensional brightness distribution feature. Fig.11 The value of the fundamental frequency of the spectrum intensity distribution characteristic 66b is calculated as the magnification. Fig.11 In the spectrum intensity distribution characteristic 66b, since the waveform represented by the dotted circle d is the waveform having the lowest frequency component, the frequency of the peak position of the waveform represented by the dotted circle d is the fundamental frequency.

[0107] [1-2-4. Estimation unit 104]

[0108] The estimation unit 104 estimates the current focus position, which is the focus position of the imaging device 20 in the inspection image, based on the magnification information indicating the relationship between the focus position and the magnification in the imaging device 20 and the magnification calculated by the calculation unit 103. The estimation unit 104 can realize the estimation function by executing a control program stored in a memory, for example, by a processor in a computer realizing the functions of the inspection device 10.

[0109] In the optical system such as the full-group focus method of the camera device 20 involved in this embodiment, the focal position and the magnification are 1:1. The magnification information showing the relationship between the focal position and the magnification in the camera device 20 can be acquired in advance. In addition, even in the case where the camera device 20 involved in this embodiment has an optical system such as an inner focus, there is a strong correlation between the focal position and the magnification in the optical system such as the inner focus. Therefore, the magnification information showing the relationship between the focal position and the magnification in the camera device 20 can be acquired in advance.

[0110] Therefore, the estimation unit 104 can estimate the current focus position of the imaging device 20 in the inspection image based on the magnification calculated by the calculation unit 103 by referring to the magnification information.

[0111] In addition, as described above, in the present embodiment, there may be a case where the value of the fundamental frequency obtained by performing a fast Fourier transform process on the one-dimensional brightness distribution characteristics of the image of the pixel area of ​​the display panel 30 captured by the camera device 20 is used as the magnification. In this case, information showing the relationship between the value of the fundamental frequency (magnification) obtained by performing a fast Fourier transform process on the one-dimensional brightness distribution characteristics of each of the multiple focus positions of the camera device 20 and the multiple focus positions can be used as the magnification information of the camera device 20.

[0112] Fig.12 An example of magnification information when the value of the fundamental frequency according to the present embodiment is used as the magnification is shown. Fig.12 The FFT value shown is a value of a fundamental frequency obtained by performing fast Fourier transform processing twice on the one-dimensional brightness distribution feature.

[0113] exist Fig.12 , as magnification information 70 , the relationship between the FFT value obtained from the image of the pixel region of the display panel 30 captured at a plurality of focus positions of the imaging device 20 and the focus position is shown. Fig.12The magnification information 70 shown is produced as follows. First, 100 focus shift images are acquired. The 100 focus shift images are obtained by photographing the pixel area of ​​the display panel 30 by shifting the focus position of the camera 20 in a range of -500μm to 500μm in 10μm increments. Next, the one-dimensional brightness distribution characteristics of the 100 acquired focus shift images after being compressed on the Y axis are subjected to two fast Fourier transform processes, and the value of the basic frequency of the 100 focus shift images, i.e., the FFT value, is calculated based on the above. Thus, an approximate straight line is obtained by linearly approximating the relationship between 100 different focus positions and FFT values. In this way, a magnification information 70 shown in FIG. 1 is produced. Fig.12 The magnification information 70 is shown.

[0114] The estimation unit 104 can be based on Fig.12 The magnification information 70 shown in FIG. 1 is used to estimate the current focus position of the imaging device 20 based on the magnification calculated by the calculation unit 103, that is, the FFT value. Fig.12 The distance from the current focus position to the focus position of 0 μm, which is the focus position, is calculated based on the magnification information 70 shown.

[0115] In addition Fig.12 In the example shown, although the fast Fourier transform process is performed twice on the one-dimensional brightness distribution feature, and the value of the fundamental frequency obtained by the process is used as the FFT value, the present invention is not limited to this. The value of the fundamental frequency obtained by performing a fast Fourier transform process once on the one-dimensional brightness distribution feature can also be used as the FFT value. Even in this case, it is possible to produce the same Fig.12 Since the magnification information 70 shown is the same as the magnification information 70 shown in FIG. 1 , the estimation unit 104 can estimate the current focus position of the imaging device 20 based on the magnification calculated by the calculation unit 103 , that is, the FFT value, based on the magnification information similarly created.

[0116] [1-2-5. Focus adjustment unit 105]

[0117] The focus adjustment unit 105 calculates the movement amount of the imaging device 20 required for focusing based on the current focus position and magnification information estimated by the estimation unit 104, and uses the calculated movement amount to adjust the position of the imaging device 20. In addition, the focus adjustment unit 105 can realize the above-mentioned adjustment function by executing a control program stored in a memory by a processor in a computer that realizes the functions of the inspection device 10.

[0118] As described above, in the present embodiment, there may be a case where the value of the fundamental frequency obtained by performing a fast Fourier transform process on the one-dimensional brightness distribution characteristics of the image of the pixel area of ​​the display panel 30 captured by the camera device 20 is used as the magnification. In this case, information showing the relationship between the value of the fundamental frequency (FFT value) and a plurality of focal positions can be used as the magnification information, wherein the value of the fundamental frequency is obtained by performing a fast Fourier transform process on the one-dimensional brightness distribution characteristics of each of the plurality of focal positions of the camera device 20. An example of the magnification information is the above-mentioned Fig.12 The focus adjustment unit 105 uses the magnification information 70. Fig.12 The magnification information shown or Fig.12 The distance from the current focus position to the focus position of 0 μm, which is the focus position, can be calculated by using the approximate straight line included in the magnification information shown. Fig.12 The amount of movement of the imaging device 20 required for focusing is calculated based on the magnification information shown and the current focus position estimated by the estimation unit 104, and the position of the imaging device 20 can be adjusted using the calculated amount of movement.

[0119] In this way, the inspection device 10 can align the focus of the imaging device 20 and obtain a high-quality inspection image that is in focus.

[0120] [1-3. Operation of the inspection device 10]

[0121] An example of the operation of the inspection device 10 having the above-described configuration will be described below.

[0122] Fig.13 This is a flowchart showing the operation of the inspection device 10 according to the present embodiment.

[0123] First, the inspection device 10 acquires an inspection image of a pixel region of the display panel 30 (S11). More specifically, the acquisition unit 101 acquires an inspection image of a pixel region of the display panel 30 captured by the imaging device 20. For example, the acquisition unit 101 acquires Figure 4 The inspection image 61 or Fig. 7A The inspection image 65 shown is an inspection image of the pixel region of the display panel 30 .

[0124] Next, the inspection device 10 applies image processing of compressing the inspection image obtained in step S11 into one-dimensional brightness on the Y axis to obtain a one-dimensional brightness distribution feature (S12). More specifically, the acquisition unit 101 applies image processing of compressing the brightness into one-dimensional brightness to the brightness of the acquired inspection image to obtain a one-dimensional brightness distribution feature, and the image processing of compressing the brightness into one-dimensional brightness is performed with the vertical direction (Y axis) of the arrangement direction of multiple sub-pixels constituting 1 pixel as the axis, and the 1 pixel is each pixel of a plurality of pixels respectively constituted by a plurality of sub-pixels. For example, the acquisition unit 101 acquires Figure 6 The one-dimensional brightness distribution characteristics 63 or Figure 7B The one-dimensional brightness distribution feature 66 shown is a one-dimensional brightness distribution feature in which the brightness of the inspection image is compressed on the Y axis.

[0125] Next, the inspection device 10 generates a spectral intensity distribution feature by performing a fast Fourier transform process on the one-dimensional brightness distribution feature obtained in step S12 (S13). More specifically, the generation unit 102 generates a spectral intensity distribution feature by performing a fast Fourier transform process on the one-dimensional brightness distribution feature obtained in step S12 once or twice.

[0126] For example, the calculation unit 103 performs a fast Fourier transform process on the one-dimensional brightness distribution feature to generate Figure 8 The spectrum intensity distribution characteristic 63a shown in (b), or Fig.10 In addition, the calculation unit 103 may perform two fast Fourier transform processes on the one-dimensional brightness distribution feature to generate Fig. 9 The spectral intensity distribution characteristic 63b shown, or Fig.11 The spectral intensity distribution characteristic 66b is shown as such a spectral intensity distribution characteristic.

[0127] Next, the inspection device 10 calculates the magnification of the camera device 20 based on the peak positions of one or more waveforms included in the spectral intensity distribution characteristics generated in step S13 (S14). More specifically, the calculation unit 103 calculates the magnification of the camera device 20 based on the frequency and power spectrum of the waveform included in the spectral intensity distribution characteristics generated by the generation unit 102, and the structural properties of the pixel area of ​​the display panel 30. The calculation unit 103 estimates that the peak position of the fundamental frequency among the one or more peak positions is the peak position corresponding to the structure of 1 pixel unit of the pixel area reflected in the inspection image, and calculates the magnification of the camera device 20 based on the peak position of the fundamental frequency. For example, the calculation unit 103 is based on Figure 8 (b) spectral intensity distribution characteristics 63a or Fig.10The fundamental frequency is calculated based on the peak positions of one or more waveforms included in the spectrum intensity distribution feature 66a of (b), and the amplification factor is calculated using the calculated fundamental frequency.

[0128] Next, the inspection device 10 estimates the current focal position of the camera 20 that captured the inspection image based on the magnification information of the camera 20 (S15). More specifically, the estimation unit 104 estimates the current focal position, which is the focal position of the camera 20 in the inspection image, based on the magnification information showing the relationship between the focal position and the magnification in the camera 20 and the calculated magnification. In addition, the one-dimensional brightness distribution characteristics of the image of the pixel area of ​​the display panel 30 captured may be processed by fast Fourier transform once or twice, and the value of the fundamental frequency obtained by the process may be used as the magnification. In this case, the current focal position can be estimated based on the calculated magnification by using information showing the relationship between the value of the fundamental frequency (magnification) obtained by fast Fourier transform once or twice and a plurality of focal positions as the magnification information of the camera 20.

[0129] [1-4. Effects, etc.]

[0130] The inspection device 10 and the like according to the present embodiment applies image processing to compress the brightness of the inspection image of the pixel area of ​​the display panel 30 photographed by the camera device 20 into one-dimensional brightness, wherein the one-dimensional brightness is compressed with the vertical direction of the arrangement direction of the plurality of sub-pixels constituting each pixel as the axis, and the plurality of sub-pixels are arranged in the plurality of pixels constituted by the plurality of sub-pixels. The one-dimensional brightness distribution feature obtained by performing such image processing is subjected to Fourier transform processing to generate a spectrum intensity distribution feature. This Fourier transform is performed at least once, and may be performed twice. Furthermore, the inspection device 10 and the like according to the present embodiment calculates the magnification of the camera device 20 based on one or more peak positions included in the spectrum intensity distribution feature, based on the fact that the plurality of pixels in the pixel area are formed in a periodic structure. Thus, the current focus position of the camera device 20 in the inspection image is estimated based on the magnification information showing the relationship between the focus position and the magnification in the camera device 20 and the calculated magnification.

[0131] In this way, the inspection device 10 and the like according to the present embodiment compresses the inspection image captured by the camera device 20 into one dimension by brightness compression, and performs Fourier transform processing. Then, the current focus position of the camera device 20 in the inspection image is estimated by using the spectrum intensity distribution characteristics obtained by the Fourier transform processing. The focus position in the optical system such as the lens of the camera device 20 has a strong correlation with the magnification, and the current focus position is estimated based on the spectrum intensity distribution characteristics by using the property that a periodic structure is formed in the pixel area of ​​the display panel 30.

[0132] That is, the inspection device 10 and the like according to the present embodiment can estimate the current focus position of the imaging device 20 in the inspection image only through calculation processing without requiring dedicated hardware. In addition, from the performance of computers equipped with processors and the like in recent years, the inspection device 10 and the like according to the present embodiment can perform brightness compression on the inspection image captured by the imaging device 20, thereby compressing it into one dimension and performing Fourier transform processing quickly.

[0133] Therefore, according to the inspection device 10 and the like according to the present embodiment, it is possible to perform processing for rapid autofocusing without using dedicated hardware.

[0134] Here, the inspection device 10 and the like involved in this embodiment estimates that the peak position of the fundamental frequency among the one or more peak positions included in the spectrum intensity distribution characteristics is the peak position corresponding to the structure of the pixel area projected in the inspection image in a pixel unit. Then, the magnification of the imaging device 20 is calculated based on the estimated peak position of the fundamental frequency.

[0135] According to this, even if the inspection image captured by the imaging device 20 is out of focus and is out of focus, the current focus position can be estimated based on the spectrum intensity distribution characteristics, and thus the magnification can be calculated.

[0136] Furthermore, the inspection device 10 and the like according to the present embodiment may generate a spectrum intensity distribution feature by performing two Fourier transform processes on the one-dimensional brightness distribution feature obtained by compressing the brightness of the inspection image captured by the imaging device 20 into one dimension. This makes it easy to estimate the fundamental frequency based on the spectrum intensity distribution feature.

[0137] Furthermore, the magnification information may not be obtained based on the optical properties of the imaging device 20. More specifically, the magnification information may be information showing the relationship between the value of the fundamental frequency and the plurality of focal positions obtained by Fourier transforming the one-dimensional brightness distribution characteristics of the image of the pixel region of the display panel 30 captured at each of the plurality of focal positions of the imaging device 20. Here, the value of the fundamental frequency is taken as the magnification.

[0138] According to this, since the current focus position can be directly estimated using the magnification information based on the fundamental frequency of the spectrum intensity distribution feature generated by performing one or two Fourier transform processes, the current focus position can be estimated quickly.

[0139] Furthermore, the inspection device 10 or the like according to the present embodiment may further calculate the movement amount of the imaging device 20 required for focusing based on the estimated current focal position and magnification information, and adjust the position of the imaging device 20 using the calculated movement amount.

[0140] In this way, the current focus position and the movement amount of the imaging device 20 required for focusing are obtained only by performing calculation processing using the magnification information and the inspection image, so that the autofocus process can be performed quickly without dedicated hardware.

[0141] That is, according to the inspection device 10 and the like according to the present embodiment, it is possible to quickly perform autofocusing with high focus accuracy without using dedicated hardware.

[0142] In other words, the inspection device 10 and the like according to the present embodiment do not require dedicated AF hardware, and can quickly perform processing for autofocus (AF) by using the inspection image itself captured by the camera 20. Accordingly, it is possible to implement a fast AF processing having the advantages of high focus accuracy and no calibration required without the need for dedicated AF hardware.

[0143] The inspection device and inspection method, etc. involved in the present disclosure are described above based on the embodiments and modified examples, but the present disclosure is not limited to these embodiments and modified examples. Without departing from the scope of the present disclosure, various modifications that can be thought of by those skilled in the art are performed on the embodiments and modified examples, and the methods of combining some of the constituent elements in the embodiments and modified examples are all included in the scope of the present disclosure.

[0144] Furthermore, the following embodiments may also be included in the scope of one or more embodiments of the present disclosure.

[0145] (1) A part of the components constituting the above-mentioned inspection device may be a computer system consisting of a microprocessor, ROM, RAM, GPU, hard disk unit, display unit, keyboard, mouse, etc. A computer program is stored in the RAM or hard disk unit. The microprocessor realizes its function by operating according to the computer program. The computer program here is composed of a combination of multiple instruction codes indicating instructions to the computer in order to realize the prescribed function.

[0146] (2) A part of the components constituting the above-mentioned inspection device may be constituted by a system LSI (Large Scale Integration). System LSI is a super-multifunctional LSI manufactured by integrating multiple components on a single chip, and specifically is a computer system composed of a microprocessor, ROM, RAM, GPU, etc. A computer program is stored in the RAM. The microprocessor or the GPU operates according to the computer program, so that the system LSI realizes its functions.

[0147] (3) A part of the components constituting the above-mentioned inspection device may be constituted by an IC card or a single module that can be installed and removed from each device. The IC card or the module is a computer system composed of a microprocessor, ROM, RAM, GPU, etc. The IC card or the module may include the above-mentioned ultra-multifunctional LSI. The IC card or the module realizes its function by operating the microprocessor or the GPU according to the computer program. The IC card or the module may also be tamper-proof.

[0148] (4) Furthermore, a part of the components constituting the above-mentioned inspection device may be a configuration in which the computer program or the digital signal is recorded on a computer-readable recording medium, such as a floppy disk, a hard disk, a CD-ROM, an MO, a DVD, a DVD-ROM, a DVD-RAM, a BD (Blu-ray (registered trademark) Disc), a semiconductor memory, etc. Furthermore, the digital signal may be recorded on these recording media.

[0149] Furthermore, a part of the components constituting the above-mentioned inspection device may transmit the computer program or the digital signal via an electronic communication line, a wireless or wired communication line, a network represented by the Internet, data broadcasting, or the like.

[0150] (5) The present disclosure may be the above-mentioned methods, a computer program for realizing these methods by a computer, or a digital signal constituted by the computer program.

[0151] (6) Furthermore, the present disclosure may be a computer system including a microprocessor, a GPU, and a memory, wherein the memory stores the above-mentioned computer program, and the microprocessor or the GPU may operate according to the computer program.

[0152] (7) Furthermore, the program or the digital signal may be recorded on the recording medium and transmitted, or the program or the digital signal may be transmitted via the network or the like, thereby being executed as another independent computer system.

[0153] (8) Furthermore, part of the components constituting the above-mentioned inspection device may be executed in the cloud or in a server device.

[0154] (9) The above-mentioned embodiments and modifications may be combined.

[0155] Industrial Applicability

[0156] The present disclosure can be utilized in an inspection process for inspecting using an inspection image of a pixel region of a display panel, and can be used in an inspection method, an inspection device, a program, etc. that can quickly perform automatic focusing at low cost and with high focus accuracy when capturing the inspection image.

[0157] Description of Reference Numerals

[0158] 10 Inspection device

[0159] 20 Camera device

[0160] 21. Loading table

[0161] 22 Stage drive unit

[0162] 30 Display Panel

[0163] 61, 65 Inspection images

[0164] 62, 63, 66 One-dimensional brightness distribution characteristics

[0165] 63a, 63b, 66a, 66b Spectral intensity distribution characteristics

[0166] 101 Acquisition Department

[0167] 102 Generation Department

[0168] 103 Computing Department

[0169] 104 Estimation Department

[0170] 105 Focus adjustment unit

[0171] 1000 Computer

[0172] 1001 Input Device

[0173] 1002 Output device

[0174] 1003 CPU

[0175] 1004 Internal Storage

[0176] 1005 RAM

[0177] 1006 GPU

[0178] 1007 Reading Device

[0179] 1008 Transceiver

[0180] 1009 Bus

Claims

1. An inspection method is a method for inspecting a display panel performed by a computer, comprising the following steps: an acquisition step of acquiring a one-dimensional brightness distribution feature by applying image processing to the brightness of the inspection image of the pixel area of ​​the display panel captured by the camera device, which compresses the brightness into one-dimensional brightness, wherein the one-dimensional brightness is compressed with a vertical direction of the arrangement direction of a plurality of sub-pixels constituting each pixel as an axis, wherein each pixel is a pixel among a plurality of pixels constituted by a plurality of sub-pixels; A generating step, generating a spectrum intensity distribution feature by performing Fourier transform processing on the one-dimensional brightness distribution feature; A calculation step, in accordance with the plurality of pixels in the pixel region being formed in a periodic structure, calculating the magnification of the imaging device based on one or more peak positions included in the spectrum intensity distribution characteristics; as well as The estimating step estimates a current focus position, which is a focus position of the imaging device in the inspection image, based on magnification information indicating a relationship between a focus position and a magnification in the imaging device and the calculated magnification.

2. The inspection method according to claim 1, In the calculation step, The magnification of the imaging device is calculated based on the peak position of the fundamental frequency by estimating that the peak position of the fundamental frequency among the one or more peak positions corresponds to the structure of one pixel in the pixel region reflected in the inspection image.

3. The inspection method according to claim 2, In the generating step, the spectrum intensity distribution feature is generated by performing two Fourier transform processes on the one-dimensional brightness distribution feature.

4. The inspection method according to claim 2, Regarding the magnification information, when the value of the basic frequency obtained by Fourier transforming the one-dimensional brightness distribution characteristics of each of the multiple focus positions of the camera device is used as the magnification, the magnification information is information showing the relationship between the magnification at this time and the multiple focus positions, and the one-dimensional brightness distribution characteristics are the one-dimensional brightness distribution characteristics of the image of the pixel area of ​​the display panel photographed by the camera device.

5. The inspection method according to any one of claims 1 to 4, The inspection method further includes an adjustment step, in which the amount of movement of the camera device required for focusing is calculated based on the estimated current focus position and the magnification information, and the position of the camera device is adjusted using the movement amount.

6. An inspection device, which is an inspection device for a display panel, The inspection device comprises: an acquisition unit that acquires a one-dimensional brightness distribution feature by applying image processing to the brightness of the inspection image of the pixel area of ​​the display panel captured by the camera device, compressing it into one-dimensional brightness, wherein the one-dimensional brightness is compressed with a vertical direction of an arrangement direction of a plurality of sub-pixels constituting each pixel as an axis, wherein each pixel is a pixel among a plurality of pixels constituted by a plurality of sub-pixels; a generating unit, generating a spectrum intensity distribution feature by performing Fourier transform processing on the one-dimensional brightness distribution feature; a calculation unit that calculates the magnification of the imaging device based on one or more peak positions included in the spectrum intensity distribution characteristics, according to the fact that the plurality of pixels in the pixel region are formed in a periodic structure; as well as The estimation unit estimates a current focus position, which is a focus position of the imaging device in the inspection image, based on magnification information indicating a relationship between a focus position and a magnification in the imaging device and the calculated magnification.

7. A program for causing a computer to execute a method for inspecting a display panel, causing the computer to execute the following steps: an acquisition step of acquiring a one-dimensional brightness distribution feature by applying image processing to the brightness of the inspection image of the pixel area of ​​the display panel captured by the camera device, which compresses the brightness into one-dimensional brightness, wherein the one-dimensional brightness is compressed with a vertical direction of the arrangement direction of a plurality of sub-pixels constituting each pixel as an axis, wherein each pixel is a pixel among a plurality of pixels constituted by a plurality of sub-pixels; A generating step, generating a spectrum intensity distribution feature by performing Fourier transform processing on the one-dimensional brightness distribution feature; A calculation step, in accordance with the plurality of pixels in the pixel region being formed in a periodic structure, calculating the magnification of the imaging device based on one or more peak positions included in the spectrum intensity distribution characteristics; as well as The estimating step estimates a current focus position, which is a focus position of the imaging device in the inspection image, based on magnification information indicating a relationship between a focus position and a magnification in the imaging device and the calculated magnification.

Images