JP2012052931A - Inspection device, inspection method, program, and record medium - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide an inspection device, an inspection method, a program, and a record medium which facilitate accurate determination whether a defect of a display panel detected by an inspection device is due to a trouble of the inspection device or to a trouble in a manufacturing process.SOLUTION: A peak width feature amount calculation part 25 calculates a peak width feature amount and an average luminance for each of peak width feature amount calculation areas based on image data received from an imaging device 10. A device state determination part 27 regularly generates a peak width feature amount fluctuation pattern and an average luminance fluctuation pattern chronologically expressing the peak width feature amounts and the average luminance respectively for each model and each of the peak width feature amount calculation areas. Based on the generated peak width feature amount fluctuation pattern and the average luminance fluctuation pattern, the device state determination part 27 determines whether or not a trouble exists in an image processing inspection device or in a manufacturing process. A device maintenance instruction part 29 displays a determination result on a determination result display part 31.

Description

  The present invention relates to an inspection device, an inspection method, a program, and a recording medium for inspecting an information display device that displays information.

  In the inspection of an information display device, for example, a flat panel display such as a liquid crystal panel or a plasma display panel, in order to evaluate the inspection object stably, at high speed and with high accuracy, Development of an image processing inspection apparatus that automatically evaluates an inspection object is in progress. An imaging apparatus that supplies a captured image to such an image processing inspection apparatus normally includes a solid-state image sensor that functions as an area sensor and an optical system that forms an image of an inspection object on the solid-state image sensor. . The optical system consists of a lens and other optical elements, and adjusts the focus adjustment mechanism for adjusting the focal position of the lens, the work distance adjustment mechanism for adjusting the distance between the object to be inspected and the lens, and the inclination of the optical axis of the optical system. It is adjusted to an appropriate state by an adjusting mechanism such as an optical axis adjusting mechanism.

  However, the state of the optical system may be deteriorated by long-term use. Factors that deteriorate the state of the optical system are various, such as a shift of the adjustment mechanism, a positional shift of the entire optical system, and a change in illuminance due to deterioration of illumination. For this reason, it is not possible to appropriately evaluate the inspection object based on the captured image captured by the imaging device whose optical system state has deteriorated. In other words, in order to perform an appropriate evaluation, a method for confirming whether or not the apparatus state is appropriate is necessary, and in some cases, periodic calibration of the image processing inspection apparatus by readjustment of the optical system is necessary. It becomes.

  As a first conventional technique, there is a calibration method for a defect inspection apparatus disclosed in Patent Document 1. This defect inspection device calibration method measures the transmitted light intensity by uniformly illuminating the back of a standard sample having an aperture formed in a specific pattern, and based on the measured transmitted light intensity, the depth of focus of the measurement system. In addition, the sensitivity distribution according to the position of each sensor element in the measurement system is evaluated and calibrated.

  As a second prior art, there is an image quality inspection apparatus disclosed in Patent Document 2. This image quality inspection apparatus moves image data corresponding to all panel areas to be inspected by moving divided areas of a set size while scanning in the horizontal and vertical directions with a set movement width while overlapping each other. Is divided into a plurality of regions. Then, for each divided area, the defect strength is calculated from the defect contrast and the recognition limit contrast, and based on the calculated defect strength, it is determined whether or not the divided area is a defect. The recognition limit contrast is obtained using an MTF (Modulation Transfer Function) characteristic that is a sensitivity characteristic with respect to a spatial frequency. And by using tristimulus value parameters based on spectral luminance data measured with a spectral luminance meter that measures the tristimulus values of the display device to be inspected, defects that correspond to variations in light sources and imaging devices and changes over time Strength calculation is possible.

  As a third conventional technique, there is an imaging apparatus inspection apparatus disclosed in Patent Document 3. The inspection apparatus of the imaging apparatus captures a chart image on which stripe images at a plurality of positions having different distances from the imaging surface of the imaging apparatus are displayed in a state where the lens position of the imaging apparatus is constant. Then, a histogram of the luminance values of the images for each of the plurality of positions is generated, and the standard deviation value of the generated histogram is used as an evaluation value indicating the degree of focusing of each of the images for each of the plurality of positions. Further, this evaluation value is plotted corresponding to the subject distance, which is the distance from the imaging surface of the imaging device, a focusing evaluation graph is generated, and the performance of the imaging device is evaluated based on the generated focusing evaluation graph. .

  As a fourth conventional technique, there is a focusing method of a liquid crystal panel inspection apparatus disclosed in Patent Document 4. This focusing method of the liquid crystal panel inspection apparatus captures the entire area data including luminance data of N pixels by photographing the liquid crystal panel with an imaging apparatus. The entire area data is divided into M small area data. Then, for each of the small area data, the variance of the luminance data is calculated, and the variances of the M pieces of small area data are summed to obtain the total value as the evaluation amount. The above-described operation is repeated by changing the focusing condition of the imaging apparatus. The evaluation amount is acquired for each of a plurality of focusing conditions, and the focusing condition that maximizes the evaluation amount is determined as the optimum focusing condition.

JP 2004-28706 A JP 2009-47465 A JP 2005-345590 A JP 2010-8438 A

  However, in an inspection apparatus such as an image processing inspection apparatus according to the prior art, it is difficult to always grasp the state of the inspection apparatus. Therefore, the decision to calibrate using the test pattern or to adjust the optical system again is after the abnormality of the decision result has been confirmed in the process after the current process, and the product produced in the meantime This means that the inspection was performed in an uncertain optical system state. As a result, there is a possibility that the cost increases, such as a member loss due to an increase in the defect occurrence rate in the post-process and an increase in labor costs spent on confirmation work.

  When applying the first prior art to such a problem, it is necessary to periodically evaluate by a specific pattern, and in order to prevent loss in the subsequent process as much as possible, the “periodic” interval is set. It needs to be shortened. Since this work is manual, the shorter the “periodic” interval, the more labor costs will be expected, or the production efficiency will be reduced due to the production time being pressed into the work time.

  In the second prior art, the tristimulus value of the display device to be inspected is monitored by the spectral luminance meter, and the inspection target display device is inspected for defects. There is a problem of deterioration of the luminance meter itself and a problem that only color information and luminance such as tristimulus values measured by the spectral luminance meter can be monitored.

  The third conventional technique quantitatively grasps the performance of the imaging device, but cannot determine whether or not there is an abnormality in the manufacturing process, and also detects an abnormality in the transmittance of the display panel. There is a problem that can not be. The fourth conventional technique performs focusing of the liquid crystal panel inspection apparatus with high accuracy, but has the same problem as the third conventional technique.

  As a solution to these problems, a method of monitoring using an inspection object, for example, an inspection result of a display panel to be inspected can be considered. However, firstly, the display panel to be inspected has a problem that the display panel has brightness variations and it is difficult to use as an evaluation standard. Second, the display panel inspection result is poor. In the case of the occurrence of the problem, there is a problem that it is difficult to determine whether an abnormality has occurred due to a problem with the inspection apparatus or whether an abnormality has occurred due to a problem with the manufacturing process.

  An object of the present invention is to provide an inspection apparatus, an inspection method, and an inspection apparatus that can easily and accurately determine whether an abnormality of a display panel detected by an inspection apparatus is caused by an abnormality of the inspection apparatus or an abnormality of a manufacturing process. It is to provide a program and a recording medium.

The present invention is an inspection apparatus for inspecting an inspection object on which a display surface on which a plurality of pixels capable of gradation display are arranged is formed,
Imaging means for capturing an image of a predetermined display pattern displayed on the display surface of the inspection object, and generating image data representing the captured image;
Based on the image data generated by the imaging means, a feature quantity calculating means for generating a brightness distribution of the captured image and calculating a feature quantity representing a feature of the generated brightness distribution;
Average luminance calculating means for calculating an average luminance obtained by averaging the luminances of the captured images based on image data generated by the imaging means;
Storage means for storing the feature quantity calculated by the feature quantity calculation means and the average brightness calculated by the average brightness calculation means for each inspection object;
Based on the feature amount variation pattern representing the feature amount stored in the storage unit in time series and the average luminance variation pattern representing the average luminance stored in the storage unit in time series, by the self-inspection apparatus at predetermined time intervals. An inspection apparatus comprising: determination means for determining whether the detected abnormality of the inspection object is caused by the self-inspection apparatus and whether the abnormality is caused by a manufacturing process for manufacturing the inspection object; It is.

Further, in the present invention, the feature amount calculating means calculates a feature amount of an image for each of a plurality of predetermined regions among image regions indicated by the image data,
The average luminance calculating means calculates an average luminance of the image for each of the plurality of predetermined regions,
The storage means stores a feature amount and an average luminance for each of the plurality of predetermined regions,
The determination means is based on the feature amount variation pattern representing the feature amount for each of the plurality of predetermined regions in time series and the average luminance variation pattern representing the average luminance for each of the plurality of predetermined regions in time series. For each of a plurality of predetermined regions, it is determined whether there is an abnormality in the self-inspection apparatus and whether there is an abnormality in the manufacturing process.

  In the invention, it is preferable that the predetermined display pattern is a distribution in which a luminance distribution is composed of only two luminance pixels.

In the invention, it is preferable that the feature amount is a standard deviation of luminance.
According to the present invention, the feature amount is a value obtained by dividing a standard deviation of luminance by an average luminance.

  According to the present invention, the determination means has an abnormality in the inspection object based on at least one inspection result among a plurality of inspection results by the self-inspection apparatus in addition to the feature amount variation pattern and the average luminance variation pattern. It is characterized by determining whether or not there is an abnormality in the self-inspection apparatus.

In addition, the present invention is an inspection method executed by an inspection apparatus that inspects an inspection object on which a display surface on which a plurality of pixels capable of gradation display are arranged has an imaging unit and a storage unit that capture an image. There,
An imaging step of capturing an image of a predetermined display pattern displayed on a display surface formed on the inspection object by an imaging unit, and generating image data representing the captured image;
A feature amount calculating step of generating a luminance distribution of the captured image based on the image data generated in the imaging step, and calculating a feature amount representing a feature of the generated luminance distribution;
Based on the image data generated in the imaging step, an average luminance calculation step for calculating an average luminance obtained by averaging the luminances of the captured images;
For each inspection object, a storage step for storing in the storage means the feature amount calculated in the feature amount calculation step and the average luminance calculated in the average luminance calculation step;
Based on the feature amount variation pattern representing the feature amount stored in the storage step in time series and the average luminance variation pattern representing the average luminance stored in the storage step in time series, by the self-inspection apparatus at predetermined time intervals. And a determination step for determining whether the detected abnormality of the inspection object is caused by the self-inspection apparatus and whether the abnormality is caused by a manufacturing process for manufacturing the inspection object. It is.

The present invention further includes a computer included in an inspection apparatus that inspects an inspection object on which a display surface on which a plurality of pixels capable of gradation display are arranged has an imaging unit that captures an image, a storage unit, and a computer. In addition,
An imaging step of capturing an image of a predetermined display pattern displayed on a display surface formed on the inspection object by an imaging unit, and generating image data representing the captured image;
A feature amount calculating step of generating a luminance distribution of the captured image based on the image data generated in the imaging step, and calculating a feature amount representing a feature of the generated luminance distribution;
Based on the image data generated in the imaging step, an average luminance calculation step for calculating an average luminance obtained by averaging the luminances of the captured images;
For each inspection object, a storage step for storing in the storage means the feature amount calculated in the feature amount calculation step and the average luminance calculated in the average luminance calculation step;
Based on the feature amount variation pattern representing the feature amount stored in the storage step in time series and the average luminance variation pattern representing the average luminance stored in the storage step in time series, by the self-inspection apparatus at predetermined time intervals. This is a program for executing a determination step for determining whether or not the detected abnormality of the inspection object is caused by the self-inspection apparatus and whether or not the abnormality is caused by a manufacturing process for manufacturing the inspection object.

  The present invention is also a computer-readable recording medium on which the program is recorded.

  According to the present invention, when inspecting an inspection object on which a display surface on which a plurality of pixels capable of gradation display are arranged is formed, the image pickup means displays a predetermined display pattern displayed on the display surface of the inspection object. Then, image data representing the captured image is generated. The feature amount calculation unit generates a luminance distribution of the captured image based on the image data generated by the imaging unit, and calculates a feature amount representing the feature of the generated luminance distribution. The average luminance calculating unit calculates an average luminance obtained by averaging the luminances of the captured images based on the image data generated by the imaging unit. The storage unit stores the feature amount calculated by the feature amount calculation unit and the average luminance calculated by the average luminance calculation unit for each inspection object. Then, the determining means determines a predetermined time interval based on the feature quantity variation pattern representing the feature quantity stored in the storage means in time series and the average brightness fluctuation pattern representing the average brightness stored in the storage means in time series. Thus, it is determined whether the abnormality of the inspection object detected by the self-inspection apparatus is due to the self-inspection apparatus and whether it is due to the manufacturing process for manufacturing the inspection object.

  Therefore, it is possible to easily and accurately determine whether the abnormality of the display panel is caused by the abnormality of the inspection apparatus or the abnormality of the manufacturing process without adding a special display pattern or an external device. In addition, the state of the inspection device and the manufacturing process can be continuously and automatically monitored without any manual operation, which can contribute to the improvement of the manufacturing process management capability.

  According to the invention, the feature amount calculating means calculates an image feature amount for each of a plurality of predetermined regions of the image region indicated by the image data. The average luminance calculating means calculates an average luminance of the image for each of the plurality of predetermined areas. The storage means stores a feature value and average luminance for each of the plurality of predetermined regions. The determination means is based on a feature amount variation pattern that represents the feature amount for each of the plurality of predetermined regions in time series, and an average luminance variation pattern that represents the average luminance for each of the plurality of predetermined regions in time series. For each of the plurality of predetermined areas, it is determined whether there is an abnormality in the self-inspection apparatus and whether there is an abnormality in the manufacturing process.

  Therefore, compared with the case where the entire display surface of the display panel is evaluated over a wide area, the influence of variations such as luminance unevenness within the display surface of the display panel is reduced, and the accuracy of evaluation of the state of the inspection apparatus is improved. In addition, it is possible to determine the state of the inspection apparatus at a plurality of locations on the display surface of the display panel, as compared with the case where the evaluation is performed only on one region of the display surface of the display panel. For example, if the optical axis of the imaging device that is the imaging means is tilted with respect to the display surface of the display panel, even if the focal point of the lens is suitable at some parts of the display surface, Focus may be out of conformity. Even in such a case, since the state of the inspection apparatus can be individually determined at a plurality of locations on the entire display surface of the display panel, the inclination of the optical axis of the imaging apparatus can be detected.

  Further, according to the present invention, since the predetermined display pattern is a distribution in which the luminance distribution is composed of only two luminance pixels, the predetermined display pattern may be a simple display pattern such as a vertical stripe pattern having a binary luminance such as black and white or a checkered pattern. Can be inspected.

  Further, according to the present invention, since the feature amount is a standard deviation of luminance, it is possible to determine an abnormality of the inspection apparatus that affects the peak width feature amount such as a focus abnormality of the imaging apparatus.

  Further, according to the present invention, since the feature amount is a value obtained by dividing the standard deviation of luminance by the average luminance, the abnormality of the inspection device that affects the peak width feature amount, such as the focus abnormality of the imaging device, and the backlight Both the abnormality of the inspection apparatus that affects the average luminance such as abnormality can be determined. Further, by dividing the standard deviation by the average luminance and normalizing it, it is possible to reduce the influence of variations in individual display panels caused by the manufacturing process reflected in the peak width feature amount.

  Further, according to the invention, the determination means abnormally detects the inspection object based on at least one inspection result among a plurality of inspection results by the self-inspection apparatus in addition to the feature amount variation pattern and the average luminance variation pattern. Since it is determined whether or not there is an abnormality in the self-inspection apparatus, it can be determined with higher accuracy.

  Further, according to the present invention, when inspecting an inspection object on which a display surface on which a plurality of pixels capable of gradation display are arranged has an imaging means and a storage means for imaging an image, An image of a predetermined display pattern displayed on the display surface formed on the inspection object is captured by the imaging unit, and image data representing the captured image is generated. In the feature amount calculating step, a luminance distribution of the captured image is generated based on the image data generated in the imaging step, and a feature amount representing a feature of the generated luminance distribution is calculated. In the average luminance calculation step, an average luminance obtained by averaging the luminances of the captured images is calculated based on the image data generated in the imaging step. In the storage step, for each inspection object, the feature amount calculated in the feature amount calculation step and the average luminance calculated in the average luminance calculation step are stored in the storage unit. In the determination step, a predetermined time interval is determined based on the feature amount variation pattern representing the feature amount stored in the storage step in time series and the average luminance variation pattern representing the average luminance stored in the storage step in time series. Thus, it is determined whether the abnormality of the inspection object detected by the self-inspection apparatus is due to the self-inspection apparatus and whether it is due to the manufacturing process for manufacturing the inspection object.

  Therefore, it is possible to easily and accurately determine whether the abnormality of the display panel is caused by the abnormality of the inspection apparatus or the abnormality of the manufacturing process without adding a special display pattern or an external device. In addition, the state of the inspection device and the manufacturing process can be continuously and automatically monitored without any manual operation, which can contribute to the improvement of the manufacturing process management capability.

  Further, according to the present invention, the inspection apparatus includes an imaging unit that captures an image, a storage unit, and a computer, and inspects an inspection object on which a display surface on which a plurality of pixels capable of gradation display are arranged is formed. An image of a predetermined display pattern displayed on the display surface formed on the inspection object is captured by an image capturing means, and image data representing the captured image is generated, and an image generated in the imaging process Based on image data, a brightness distribution of the captured image is generated, a feature amount calculating step for calculating a feature amount representing a feature of the generated brightness distribution, and the imaging based on the image data generated in the imaging step An average luminance calculation step of calculating an average luminance obtained by averaging the luminances of the obtained images, and a feature amount calculated in the feature amount calculation step and an average luminance calculation step for each inspection object Based on a storage step of storing the average luminance in the storage means, a feature amount variation pattern that represents the feature amount stored in the storage step in time series, and an average luminance variation pattern that represents the average luminance stored in the storage step in time series And determining whether the abnormality of the inspection object detected by the self-inspection apparatus is caused by the self-inspection apparatus and the manufacturing process for manufacturing the inspection object at predetermined time intervals. It can be provided as a program for executing the determination step.

  The present invention can also be provided as a computer-readable recording medium on which the program is recorded.

It is a figure which shows typically the structure of the image processing inspection apparatus 1 which is one Embodiment of this invention. 2 is a block diagram illustrating a functional configuration of the image processing inspection apparatus 1. FIG. It is a figure which shows the example of the enlarged image in a peak width feature-value calculation area and a selection area. FIG. 10 is a diagram illustrating an example of a histogram variation due to the resolution capability of the imaging apparatus 10. It is a figure which shows the example of case 1 of the peak width feature-value fluctuation pattern for every model, and an average luminance fluctuation pattern. It is a figure which shows the example of case 2 of the peak width feature-value fluctuation pattern and average brightness | luminance fluctuation pattern for every model. It is a figure which shows the example of the case 3 of the peak width feature-value fluctuation pattern and average brightness | luminance fluctuation pattern for every model. It is a figure which shows the example of case 4 of the peak width feature-value fluctuation pattern and average brightness | luminance fluctuation pattern for every model. It is a figure which shows the example of the peak width feature-value fluctuation | variation pattern and average luminance fluctuation | variation pattern for every selection area about one model. It is a flowchart which shows the process sequence of the determination process which the image processing test | inspection apparatus 1 performs.

  FIG. 1 is a diagram schematically showing a configuration of an image processing inspection apparatus 1 according to an embodiment of the present invention. An image processing inspection apparatus 1 that is an inspection apparatus is an apparatus that inspects a display panel 2 that is an inspection object. The inspection method according to the present invention is executed by the image processing inspection apparatus 1. The image processing inspection apparatus 1 includes an imaging device 10, a control device 20, and a display device 30.

  The imaging device 10 that is an imaging means captures an image of a predetermined display pattern displayed on the display surface of the display panel 2, and the control device 20 controls the display panel 2 based on the captured image captured by the imaging device 10. Inspecting whether there is a defect and, based on the history of the inspection result, whether the detected abnormality of the display panel 2 is caused by the abnormality of the image processing inspection apparatus 1 or the abnormality of the manufacturing process. The inspection result and the determination result are displayed on the display device 30. The main function of the image processing inspection apparatus 1 is to inspect the display panel 2. As an accompanying function, the image processing inspection apparatus 1 determines whether the image processing inspection apparatus 1 has an abnormality and whether the manufacturing process has an abnormality. To do. The present invention relates to this accompanying function.

  The display panel 2 is constituted by a liquid crystal panel, for example. The display panel 2 has a display surface on which a plurality of pixels capable of gradation display are arranged. When the display panel 2 is a three-primary-color liquid crystal panel that uses a plurality of colors, for example, three primary colors of red (hereinafter referred to as “R”), green (hereinafter referred to as “G”), and blue (hereinafter referred to as “B”), R A monochrome display unit, a G monochrome display unit, and a B monochrome display unit. Hereinafter, a set of pixels including one R pixel, one G pixel, and one B pixel is referred to as a “picture element”. An image pickup device 12 (to be described later) formed of a charge coupled device (abbreviated as CCD) of the image pickup apparatus 10 has one unit as one pixel, and one pixel is an image pickup unit of RGB single color.

  The display panel 2 displays an image of a predetermined display pattern at the time of inspection. The predetermined display pattern is a periodic arrangement pattern arranged so that the luminance of each pixel changes periodically, for example, a vertical stripe pattern or a checkered pattern. The predetermined display pattern may be stored in the display panel 2 and displayed on the display panel 2 itself, or a predetermined display pattern may be transmitted from another device, for example, the control device 20, and the display panel 2 may be controlled by the control device. 20 may be received and displayed. As the predetermined display pattern, a display pattern used for inspecting the display panel 2 may be used in combination, or a dedicated display pattern different from the display pattern used for inspecting the display panel 2 may be used. The display pattern used for inspecting the display panel 2 is preferably used in combination.

  The imaging device 10 is configured by a camera using, for example, a CCD, and includes an optical system and a solid-state imaging device. The optical system is composed of, for example, an optical element such as the lens 11 and its adjustment mechanism, and forms an image displayed on the display surface of the display panel 2 on the light receiving unit of the solid-state imaging element. The solid-state imaging device is configured by an imaging device 12 such as an area sensor type CCD image sensor or a field effect and a CMOS (Complementary Metal Oxide Semiconductor) image sensor and an adjustment mechanism thereof, and an image formed on the light receiving unit is imaged. Convert to signal.

  The lens 11 and the image pickup device 12 constituting the optical system are attached to the housing wall of the image pickup apparatus 10 via respective adjustment mechanisms. The display panel 2 is placed so that the display surface of the display panel 2 faces the imaging device 10. The imaging device 10 captures an image of a predetermined display pattern displayed on the display surface of the opposing display panel 2. The imaging device 10 converts the image signal from the imaging device 12 into image data representing a captured image, and sends the converted image data to the control device 20.

  The control device 20 is configured by a computer such as a personal computer or a workstation, and includes a control unit 21 and an image memory 22. The control unit 21 includes, for example, a central processing unit (abbreviated as CPU) (not shown) and a storage device (not shown). A CPU (not shown) executes programs stored in a storage device (not shown), thereby realizing each function described later and controlling the imaging device 10 and the display device 30. The storage device (not shown) is configured by, for example, a semiconductor memory, and stores a program executed by a CPU (not shown) and information necessary for the CPU (not shown) to perform processing. In a storage device (not shown), information is written and read by a CPU (not shown).

  The image memory 22 is constituted by a semiconductor memory, for example, and stores image data. Image data stored in the image memory 22 is written and read by a CPU (not shown).

The control device 20 calculates the peak width feature amount P based on the image data received from the imaging device 10. The peak width feature amount P is a parameter calculated according to the resolution capability, and is calculated using the standard deviation σ and the average luminance I _ave of the luminance distribution of the photographed image indicated by the image data received from the imaging device 10. Specifically, the peak width feature amount P is calculated by Expression (1).
P = σ / I _ave (1)

That is, the peak width feature amount P is normalized by dividing the standard deviation σ that varies depending on the resolution capability by the average luminance I _ave . Details of the standard deviation σ and the average luminance I _ave will be described later.

Controller 20 at time intervals predetermined, for each of a plurality of areas included in the area of the captured image, calculates the peak width feature amount P and the average luminance I _ave, calculated peak width feature amount P and the average luminance I _ave Is stored in a storage device (not shown). The control device 20 then _detects the abnormality of the image processing inspection apparatus 1 and the manufacturing process based on the peak width feature amount variation pattern and the average luminance variation pattern that represent the stored peak width feature amount P and average luminance I _ave in time series. Determine whether there is any abnormality.

  The display device 30 includes, for example, a liquid crystal display (abbreviated as LCD) or a cathode ray tube (abbreviated as CRT). The display device 30 displays the inspection result and the determination result received from the control device 20.

  In this way, the image processing inspection apparatus 1 determines whether there is an abnormality in the image processing inspection apparatus 1 and an abnormality in the manufacturing process by monitoring the inspection result history while inspecting the display panel 2. Then, the image processing inspection apparatus 1 notifies the operator of the determination result, prompts the adjustment or calibration of the image processing inspection apparatus 1 and the manufacturing apparatus used in the manufacturing process, or identifies the next maintenance item and provides feedback to the design. Is possible.

  FIG. 2 is a block diagram illustrating a functional configuration of the image processing inspection apparatus 1. The control device 20 includes an image data storage unit 23, a peak width feature amount calculation area setting unit 24, a peak width feature amount calculation unit 25, a peak width feature amount storage unit 26, a device state determination unit 27, a determination information storage unit 28, and a device. A maintenance instruction unit 29 is included.

  The peak width feature amount calculation area setting unit 24, the peak width feature amount calculation unit 25, the device state determination unit 27, and the device maintenance instruction unit 29 are functions realized by the control unit 21, that is, a CPU (not shown) stores in a storage device (not shown). This is a function realized by executing a stored program. The image data storage unit 23 is an image memory 22, and the peak width feature amount storage unit 26 and the determination information storage unit 28 are storage areas included in a storage image not shown.

  The image data storage unit 23 is a storage unit for storing and storing image data, model information, and time information, and includes an image memory 22. When receiving the image data from the imaging device 10, the control unit 21 stores the image data in the image data storage unit 23 in association with the received image data, the model information, and the time information.

  The model information includes, for example, a model name and a panel ID (Identification) number. The model name is model identification information for identifying the model of the display panel 2. The panel ID number is panel identification information for identifying each display panel 2. The model information may be acquired from a process management system that manages the model information of the display panel 2 that is an inspection object independently of the image processing inspection apparatus 1 or is printed on the display panel 2. The model information may be captured by an imaging device and recognized from the captured image, or may be input from an operation unit (not shown). The time information is, for example, date and time. The image processing inspection apparatus 1 refers to a timing unit (not shown) provided in the self-image processing inspection apparatus 1 and acquires the date and time when the image data is received from the imaging apparatus 10, and uses the acquired date and time as time information.

  The peak width feature amount calculation area setting unit 24 presets a plurality of regions included in the region of the captured image indicated by the image data as a peak width feature amount calculation area that is a region for calculating the peak width feature amount P. . In the peak width feature amount calculation area, a plurality of regions are set in order to grasp the variation depending on the position in the display surface of the display panel 2, the posture of the optical system of the imaging device 10, and the like. An area ID number is assigned to each peak width feature amount calculation area. The area ID number is area identification information for identifying each peak width feature amount calculation area.

  FIG. 3 is a diagram illustrating an example of enlarged images in the peak width feature amount calculation area and the selection area. FIG. 3A shows an example of a peak width feature amount calculation area set by the peak width feature amount calculation area setting unit 24. FIG. 3B is an example of an enlarged image obtained by enlarging a captured image of a selection area selected from the peak width feature amount calculation area, for example, the peak width feature amount calculation area 614.

  As shown in FIG. 3A, the peak width feature amount calculation area setting unit 24 captures an optical system such as the lens 11 and covers the entire display surface of the display panel 2 as shown in FIG. A total of five peak width feature quantity calculation areas, ie, a peak width feature quantity calculation area 613 at the center of the area 61 and peak width feature quantity calculation areas 611, 612, 614, and 615 at the four corners of the imaging area 61 are set in advance. Yes. The imaging area 61 is set to a range in which a range that is slightly larger than the area of the display surface 62 of the display panel 2 can be captured.

The enlarged image shown in FIG. 3B is an enlarged image of the peak width feature amount calculation area 614. Based on the captured image of each peak width feature amount calculation area, the peak width feature amount P and average luminance I _{ave of} each peak width feature amount calculation area are calculated.

FIG. 4 is a diagram illustrating an example of a histogram change due to the resolution capability of the imaging apparatus 10. The peak width feature amount calculator 25 calculates the peak width feature amount P and the average luminance I _ave for each peak width feature amount calculation area set by the peak width feature amount calculation area setting unit 24. The peak width feature amount calculation unit 25 is a feature amount calculation unit and an average luminance calculation unit.

  FIG. 4A is an image of a periodic pattern 41 which is a predetermined display pattern. The periodic pattern 41 of the image shown in FIG. 4A is a periodic stripe pattern of vertical stripes in which white portions 411 and black portions 412 are alternately arranged in a predetermined cycle. The ideal state is that the image of the periodic pattern 41 shown in FIG. 4A is captured as it is by the imaging device 10 to become a captured image, but in reality, variation or deterioration of the optical system of the imaging device 10 or Due to discretization by each light receiving element of the image pickup element 12 of the image pickup apparatus 10, an image of the periodic pattern 42 shown in FIG. The focused state is a state where the focus of the optical system is in alignment with the display surface of the display panel 2. In the image of the periodic pattern 42 shown in FIG. 4C, an intermediate color portion 423 in which white and black are mixed is generated at the boundary portion between the white portion 421 and the black portion 422. FIG. 4E is an image of the periodic pattern 43 when the optical system of the imaging apparatus 10 is out of focus and in a non-focus state. The ratio of the white portion and the black portion is extremely reduced, and most of the portions are intermediate color portions. The out-of-focus state is a state where the optical system is not focused on the display surface of the display panel 2.

FIG. 4B is a histogram 51 representing the luminance distribution of the image of the periodic pattern 41 shown in FIG. FIG. 4D is a histogram 52 representing the luminance distribution of the image of the periodic pattern 42 shown in FIG. FIG. 4F is a histogram 53 representing the luminance distribution of the image of the periodic pattern 43 shown in FIG. In any of the histograms, the vertical axis represents the number of pixels (pix), and the horizontal axis represents the luminance (cd / m ² ). The histograms 51 to 53 shown in FIGS. 4B, 4 </ b> D, and 4 </ b> F measure the luminance of the captured image captured by each pixel for each pixel of the image sensor 12, and the measured luminance of each pixel. The distribution is calculated as the number of pixels for each luminance.

  In the histogram 51 shown in FIG. 4B, the luminance of each pixel is composed of only two luminances, the luminance of the pixel of the white portion 411 and the luminance of the pixel of the black portion 412, and two peaks 511, 512 are included. Has been generated. The histogram 51 indicates that the white portion 411 and the black portion 412 of the periodic pattern 41 are completely separated, and the resolution capability is high.

  The histogram 52 shown in FIG. 4D shows that the white portion 421 and the black portion 422 are not completely separated and the resolving power is lower than the histogram 51 in the ideal state. ing. The histogram 53 shown in FIG. 4F indicates that the proportion of the intermediate color is higher than that of the histogram 52, so that the separation is further reduced and the resolution capability is further reduced.

The peak width feature amount calculation unit 25 first calculates an average luminance I _ave for one peak width feature amount calculation area. The average luminance I _ave is a value obtained by averaging the luminance of each pixel in the peak width feature amount calculation area, where the luminance of each pixel is I _i and the number of pixels in the peak width feature amount calculation area is n. The average luminance I _ave is calculated by the equation (2).
I _ave = (I ₁ + I ₂ +... + I _n ) / n (2)

  Next, the peak width feature amount calculation unit 25 calculates the standard deviation σ with respect to the peak width feature amount calculation area using Equation (3).

That is, the standard deviation σ is a value corresponding to the difference between the luminance I _i and the average luminance I _{ave in} each pixel, and represents a variation in luminance for each pixel. Therefore, in an ideal state like the image of the periodic pattern 41 shown in FIG. 4A, the standard deviation σ becomes a large value, and the standard deviation σ becomes a smaller value as the out-of-focus state progresses.

In the equation (3), the standard deviation σ has the same unit dimension as the luminance, and the standard deviation σ varies depending on the magnitude of the absolute value of the difference between the luminance I _i and the average luminance I _{ave of} each pixel. It shows that In other words, when the luminance changes depending on the state of the light source of the display panel 2, the value of the standard deviation σ varies even when the display panel 2 is not optically deteriorated. It may be difficult to accurately evaluate In order to avoid the influence due to the change in the luminance of the light source of the display panel 2, a value obtained by dividing the standard deviation σ by the average luminance I _ave is used as the evaluation value. Specifically, the peak width feature amount P, which is an evaluation value, is calculated by the equation (1).

The peak width feature amount storage unit 26 serving as a storage unit is a storage unit for storing and storing the peak width feature amount P and the average luminance I _ave , and is a storage area provided in a storage image device (not shown). The peak width feature quantity calculation unit 25 stores the calculated peak width feature quantity P and average luminance I _ave in the peak width feature quantity storage unit 26 in association with the corresponding area ID number, model information, and time information. The peak width feature amount P and the average luminance I _ave are inspection results for each display panel 2 that is an inspection target, and are stored in the peak width feature amount storage unit 26 and stored as a history of inspection results.

The peak width feature amount calculation unit 25 calculates the peak width feature amount P of each peak width feature amount calculation area based on the image data stored in the image data storage unit 23, but the image data has a large data amount. It is difficult to simultaneously store image data for a large number of display panels 2 in the image data storage unit 23. Therefore, the peak width feature amount calculation unit 25 periodically calculates the peak width feature amount P and the average luminance I _ave in order to reduce the amount of data stored in the image data storage unit 23, and calculates the calculated peak width feature amount P. And the average luminance I _ave are stored in the peak width feature amount storage unit 26, and the image data in which the peak width feature amount P and the average luminance I _ave are calculated are deleted from the image data stored in the image data storage unit 23. Thus, the amount of data that can be stored in the image data storage unit 23 is increased.

  Here, periodically means, for example, every time each display panel 2 is inspected or every time a predetermined monitoring time elapses. The predetermined monitoring time is a time that is set to a value less than the image storage period, for example, by determining an image storage period that is the maximum period for storing image data in the image data storage unit 23.

The apparatus state determination unit 27 serving as a determination unit periodically includes a peak width feature amount variation pattern and an average representing the peak width feature amount P and the average luminance I _ave stored in the peak width feature amount calculation unit 25 in time series. A luminance variation pattern is generated for each model name and for each peak width feature amount calculation area, and the apparatus state is determined based on the generated peak width feature amount variation pattern and average luminance variation pattern. The apparatus state is the state of the image processing inspection apparatus 1 and the manufacturing process. The state of the manufacturing process includes the state of the manufacturing apparatus used in the manufacturing process. The determination of the apparatus state is determination of whether or not there is an abnormality in the image processing inspection apparatus 1 and whether or not there is an abnormality in the manufacturing process, and includes specifying an abnormality cause for maintenance or the like. The term “regular” here means at the predetermined monitoring interval, but it is also possible to make irregular determinations by an operator instructing from an operation unit (not shown).

  FIG. 5 is a diagram illustrating an example of Case 1 of a peak width feature amount variation pattern and an average luminance variation pattern for each model. FIG. 6 is a diagram illustrating an example of Case 2 of a peak width feature amount variation pattern and an average luminance variation pattern for each model. FIG. 7 is a diagram illustrating an example of Case 3 of the peak width feature amount variation pattern and the average luminance variation pattern for each model. FIG. 8 is a diagram illustrating an example of Case 4 of the peak width feature amount variation pattern and the average luminance variation pattern for each model. 5 to 8 show four typical examples as cases 1 to 4 which are considered to be abnormal in the apparatus state.

5 to 8 show the peak width feature amount variation pattern in the upper stage and the average luminance variation pattern in the lower stage for the three model names “model A”, “model B”, and “model C”, respectively. . The vertical axis of the peak width feature amount variation pattern is the peak width feature amount P, and the horizontal axis is time. The vertical axis of the average luminance fluctuation pattern is average luminance I _ave , and the horizontal axis is time.

  5A, FIG. 6A, FIG. 7A, and FIG. 8A are a peak width feature amount variation pattern and an average luminance variation pattern for the model of the model name “model A”. 5 (b), FIG. 6 (b), FIG. 7 (b), and FIG. 8 (b) are a peak width feature amount variation pattern and an average luminance variation pattern for the model of the model name “model B”. (C), FIG. 6 (c), FIG. 7 (c), and FIG. 8 (c) are a peak width feature amount variation pattern and an average luminance variation pattern for the model of the model name “model C”.

  In the example of case 1 shown in FIG. 5, the peak width feature amount variation pattern of the model name “model A” shown in FIG. 5A increases only near time t1. The average brightness variation pattern does not vary greatly in any model. In this case, since the peak width feature amount is temporarily increased only with a specific model, the image processing inspection for inspecting the models of the model names “model A”, “model B”, and “model C” in common The possibility that an abnormality has occurred in the device 1 is low. In addition, since the peak width feature amount is temporarily increased only in the model name “model A”, there is an abnormality in the processing width of the opening of the display panel 2 of the model name “model A”. There is a possibility that it has occurred, and there is a high possibility that an abnormality has occurred in the manufacturing process of the model with the model name “model A”. Therefore, the apparatus state determination unit 27 does not need to perform maintenance on the image processing inspection apparatus 1 and determines that an abnormality has occurred in the manufacturing process of the model having the model name “model A”. The opening is a portion of the liquid crystal panel of the display panel 2 through which light from a backlight that illuminates the display panel 2 from behind, for example, a color filter is applied.

  Abnormality is determined in advance by setting a fluctuation amount threshold value and quantitatively determining the threshold value. Here, the setting of the threshold value may be appropriately determined according to the inspection accuracy as the management target and the level of the manufacturing process abnormality. For example, when there is a problem that the defect detection rate decreases due to an apparatus abnormality, and the management target of inspection accuracy is to maintain a defect detection rate of 90% or more, the feature amount when the defect detection rate is 90% is set. What is necessary is just to set as a threshold value. Here, in order to set the threshold value, it is necessary to know the feature amount when the defect detection rate is 90%. As the method, the feature amount in the device state where the defect detection rate is 90% is actually measured. And a method of estimating by calculating a correlation between a defect non-detection rate and a feature amount from past defect undetection rate and feature amount history data.

  The example of the case 2 shown in FIG. 6 includes the model of the model name “model A” shown in FIG. 6A, the model of the model name “model B” shown in FIG. 6B, and FIG. ) All peak width feature amount variation patterns of the model name “model C” shown in FIG. 3) increase near time t2, and continue to increase after time t2. The average brightness variation pattern does not vary greatly in any model. In this case, since the peak width feature amount has increased after a certain time and has continued to increase in all models, an abnormality has occurred in the optical system of the image processing inspection apparatus 1 that inspects all models in common. There is a possibility. The same applies to all models in which the peak width feature value decreases after a certain time and continues to decrease after that time. Therefore, the apparatus state determination unit 27 needs to perform maintenance of the image processing inspection apparatus 1, particularly the optical system, and determines that there is no abnormality in the manufacturing process.

  In the example of case 3 shown in FIG. 7, the average luminance variation pattern of the model name “model A” shown in FIG. 7A increases only near time t3. The peak width feature amount variation pattern does not vary greatly in any model. In this case, since the average luminance is temporarily increased only with a specific model, the image processing inspection apparatus 1 that inspects the models of the model names “model A”, “model B”, and “model C” in common. It is unlikely that an abnormality has occurred. In addition, since the average luminance is temporarily increased only in the model name “model A” of the manufacturing process, there is a possibility that an abnormality has occurred in the transmittance of the color filter of the display panel 2 in the manufacturing process. There is a high possibility that an abnormality has occurred in the manufacturing process of the color filter of the model name “model A”. Therefore, the apparatus state determination unit 27 does not need to perform maintenance on the image processing inspection apparatus 1 and determines that an abnormality has occurred in the manufacturing process of the model having the model name “model A”.

  The example of the case 4 shown in FIG. 8 includes the model of the model name “model A” shown in FIG. 8A, the model of the model name “model B” shown in FIG. 8B, and FIG. The average brightness variation pattern of the model name “model C” shown in FIG. 4) increases near time t4, and continues to increase after time t4. The peak width feature amount variation pattern does not vary greatly in any model. In this case, in all models, the average luminance increases after a certain time, and the increased state continues. Therefore, a lighting failure caused by the contact portion of the display panel 2 and an image that illuminates the display panel 2 from behind. An abnormality of a backlight (not shown) included in the processing inspection apparatus 1 can be considered.

  The contact portion is a terminal portion formed on the display panel 2. In order to light the display panel 2, it is necessary to apply a voltage to the display panel 2. The terminal portion is a portion in contact with an external electrode for applying this voltage to the display panel 2. The terminal portion is provided in a non-display area of the display panel 2, and wiring from the terminal portion to each pixel on the display surface is drawn out. The external electrode is composed of, for example, a contact needle, and the contact needle is pressed against the contact portion, and a voltage of a driving signal is applied from the contact needle to the contact portion. If an electrical contact failure occurs due to a broken, dirty, or misaligned contact needle, lighting failure due to the contact portion is caused. Hereinafter, “lighting failure due to the contact portion” is referred to as “contact failure”, and “backlight abnormality” is referred to as “backlight abnormality”.

  In the case of a backlight abnormality, even if an abnormality occurs in a part of the backlight, the light in the part of the periphery where the abnormality occurs is part of the light in which the abnormality occurs. Therefore, the light intensity continuously increases or decreases at the boundary between the portion where the luminance is reduced and the portion where the luminance is normal. In general, in the case of backlight anomalies, the luminance at the location where there is an abnormality decreases overall in a much wider range than the peak width feature amount detection area, so the peak width feature amount does not change much and the average Only the brightness is reduced.

  On the other hand, in the case of a contact failure, only the luminance of the contact defective portion is lowered, and the luminance is not changed at all other portions. Therefore, only the luminance of the pixel causing the contact failure is shifted to the low luminance side. For this reason, when the contact failure is mild, the luminance of a part of the pixels constituting the peak of the luminance distribution shifts to the low luminance side to the extent that it is not completely separated from the peak, so that the peak width increases and the average luminance is increased. Simultaneously with the decrease, the peak width feature amount changes. Therefore, when only the average luminance changes without changing the peak width feature amount, it can be said that the possibility of backlight abnormality is high.

  In this case, there is a high possibility that the optical system of the image processing inspection apparatus 1, in particular, a backlight (not shown) included in the image processing inspection apparatus 1 is abnormal. Therefore, the apparatus state determination unit 27 needs to perform maintenance of the image processing inspection apparatus 1, particularly the backlight, and determines that there is no abnormality in the manufacturing process.

  As described above, since the apparatus state determination unit 27 determines based on the variation tendency of the peak width feature amount variation pattern and the average luminance variation pattern across a plurality of models, it is detected that there is an abnormality in the inspection of the display panel 2. Whether the cause of the error is due to an abnormality in the image processing inspection apparatus 1 or an abnormality in the manufacturing process can be determined. It is possible to identify items that need to be subjected to and processes that should be reviewed with emphasis on the manufacturing process.

FIG. 9 is a diagram illustrating an example of a peak width feature amount variation pattern and an average luminance variation pattern for each selection area for one model. 9A shows the peak width feature quantity calculation area 611, FIG. 9B shows the peak width feature quantity calculation area 612, and FIG. 9C shows the peak width feature quantity calculation area 613. FIG. 9D shows the peak width feature amount calculation area 614, and FIG. 9E shows the peak width feature amount calculation area 615, with the peak width feature amount variation pattern on the top and the average brightness variation pattern on the bottom. Yes. The vertical axis of the peak width feature amount variation pattern is the peak width feature amount P, and the horizontal axis is time. The vertical axis of the average luminance fluctuation pattern is average luminance I _ave , and the horizontal axis is time.

  The peak width feature amount variation pattern in the peak width feature amount calculation area 614 shown in FIG. 9D rises near time t5, maintains a rise after time t5, and the average luminance variation pattern also rises near time t5. However, after time t5, there is a slight fluctuation, but the elevated state is maintained. The peak width feature amount variation pattern and the average luminance variation pattern in the peak width feature amount calculation areas 611 to 613 and 615 shown in FIGS. 9A to 9C and FIG. There is no significant change in the quantity calculation area. In this case, the fluctuation of the peak width feature amount variation pattern indicates a variation in resolution, and the average luminance variation pattern also varies. Therefore, the periodic pattern itself of the captured image in the specific peak width feature amount calculation area It is possible that an abnormality occurred.

  Possible causes include the possibility of some reflection on the display panel 2 due to light leakage from the surrounding environment of the display panel 2 due to carelessness of the operator, or an abnormality of some contact parts. There is a possibility that a lighting failure occurs. Therefore, it is necessary for the apparatus state determination unit 27 to perform maintenance on the image processing inspection apparatus 1, particularly the contact unit, or review whether there is light leakage, and determines that there is no abnormality in the manufacturing process.

  If fluctuations appearing in the peak width feature amount and the average luminance are significant, a large change also appears in the inspection result of the display panel 2, so that it is possible to detect the presence / absence of an abnormality only from the inspection result. However, the fluctuations appearing in the peak width feature amount and the average luminance are not significant, and if the fluctuations are small, no large change is seen in the inspection result, so it is difficult to detect the presence or absence of abnormality from the inspection result alone. . However, according to the present embodiment, since the fluctuation is monitored in time series using the peak width feature amount variation pattern and the average luminance variation pattern, the variation appearing in the peak width feature amount and the average luminance is not significant, and the variation is small. Even in some cases, it is highly possible that the presence or absence of an abnormality can be detected.

  The determination information storage unit 28 is a storage unit for storing and storing the determination result determined by the device state determination unit 27, and is a storage area provided in a storage image not shown. The device state determination unit 27 stores the determination result in the determination information storage unit 28.

  The device maintenance instruction unit 29 sends information corresponding to the determination result stored in the determination information storage unit 28 to the display device 30 for display. If the determination result indicates that the device state is normal, the device maintenance instruction unit 29 sends information indicating that there is no problem to the display device 30 for display. Further, the apparatus maintenance instruction unit 29 displays alert information when the determination result indicates that the apparatus state is abnormal, that is, that the image processing inspection apparatus 1 is abnormal or the manufacturing process is abnormal. Then, it is sent and displayed on the display device 30. The alert information is information for notifying the operator that maintenance of the image processing inspection apparatus 1 or a review of the manufacturing process is necessary.

  The display device 30 includes a determination result display unit 31. The determination result display unit 31 displays information received from the device maintenance instruction unit 29 of the control device 20.

  As described above, the image processing inspection apparatus 1 monitors the abnormality of the image processing inspection apparatus 1 and the manufacturing process more accurately and more precisely because the image width inspection amount 1 and the average luminance are combined and monitored in combination. The operator can be notified of the detailed maintenance guidelines for the image processing inspection apparatus 1 and the detailed review guidelines for the manufacturing process.

  FIG. 10 is a flowchart illustrating a processing procedure of determination processing executed by the image processing inspection apparatus 1. When the image processing inspection apparatus 1 is turned on and becomes operable, and the display panel 2 as the inspection object is placed facing the imaging apparatus 10, the process proceeds to step A1.

  In step A1, which is an imaging process, the control unit 21 acquires image data. Specifically, the control unit 21 instructs the imaging device 10 to send the image data of the display panel 2. When instructed by the control unit 21 to send image data of the display panel 2, the imaging device 10 captures an image of a predetermined display pattern displayed on the display surface of the display panel 2, and captures the captured image. The representing image data is sent to the control device 20. The control unit 21 receives the image data sent from the imaging device 10 and stores the received image data in the image data storage unit 23 for storage. The control unit 21 stores the model information of the received image data on the display panel 2 and the time information when the image data is received in the image data storage unit 23 in association with the image data.

  In step A2, the peak width feature amount calculation area setting unit 24 sets a plurality of regions within the region of the captured image indicated by the image data as a peak width feature amount calculation area that is a region for calculating the peak width feature amount. When the same region is always used as the peak width feature amount calculation area, the process proceeds to step A3 without executing this step after the second time.

In step A <b> 3, the peak width feature amount calculation unit 25 calculates the peak width feature amount P and the average luminance I _ave for each peak width feature amount calculation area set by the peak width feature amount calculation area setting unit 24. Step A3 is a feature amount calculation step and an average luminance calculation step.

In step A4, which is a storage process, the peak width feature amount calculation unit 25 stores the calculated peak width feature amount P and the average luminance I _{ave in association} with the corresponding area ID number, model information, and time information, and stores the peak width feature amount. The data is stored in the unit 26 and saved.

In step A5, device state determination unit 27 represents peak width feature amount P and average luminance I _ave in time series. Specifically, the device state determination unit 27 periodically includes a peak width feature amount variation pattern representing the peak width feature amount P and the average luminance I _ave stored in the peak width feature amount calculation unit 25 in time series, and An average luminance variation pattern is generated for each model name and for each peak width feature amount calculation area.

  In step A6, the device state determination unit 27 determines whether or not the feature amount is normal. The device state determination unit 27 determines that the feature amount is normal when neither the peak width feature amount variation pattern nor the average luminance variation pattern generated in step A5 has a large variation, and proceeds to step A7. When any of the peak width feature amount variation pattern and the average luminance variation pattern generated in step A5 has a large variation, it is determined that the feature amount is not normal, and the process proceeds to step A9. Step A5 and step A6 are determination steps.

  In step A7, the device state determination unit 27 stores a determination result indicating that the device state is normal in the determination information storage unit 28 and stores it. The apparatus state is the state of the image processing inspection apparatus 1 and the manufacturing process. In step A8, since the determination result stored in the determination information storage unit 28 indicates that the apparatus state is normal, the apparatus maintenance instruction unit 29 displays information indicating that there is no problem in the determination result display unit 31. And the determination process ends. The information indicating that there is no problem is, for example, a message that “the image processing inspection apparatus 1 and the manufacturing process are normal”.

  In step A9, the apparatus state determination unit 27 analyzes the feature amount and identifies the cause of the abnormality. Specifically, the apparatus state determination unit 27 analyzes the peak width feature amount variation pattern and the average luminance variation pattern generated for each model name and for each peak width feature amount calculation area, and identifies the cause of the abnormality. For example, the analysis as shown in FIGS. 5 to 9 is performed to identify which part of the image processing inspection apparatus 1 is abnormal, and which process of the manufacturing process and which manufacturing apparatus are abnormal. When the analysis and identification are completed, the device state determination unit 27 stores and stores the determination result and the analysis result indicating that the device state is abnormal in the determination information storage unit 28.

  In step A10, the apparatus maintenance instruction unit 29 displays alert information for prompting implementation of apparatus maintenance, etc., because the determination result stored in the determination information storage unit 28 indicates that the apparatus state is abnormal. Displayed on the unit 31, and the determination process is terminated. The alert information that prompts the execution of the apparatus maintenance is, for example, a message “Please detect an abnormal luminance value and perform maintenance of the backlight.”

In the above-described embodiment, the peak width feature amount P is used as the feature amount. However, when it is not necessary to consider that the luminance changes depending on the state of the light source of the display panel 2, it is necessary to divide by the average luminance I _ave. The standard deviation σ may be used as the feature amount. In this case, the standard deviation σ may be used instead of the peak width feature amount P described above, and the standard deviation variation pattern may be used instead of the peak width feature amount variation pattern. The standard deviation variation pattern is a pattern representing the standard deviation σ in time series.

  In the above-described embodiment, the apparatus state is determined based on the peak width feature quantity and the average brightness. In addition to the peak width feature quantity and the average brightness, other parameters relating to the inspection apparatus or the manufacturing process, For example, the apparatus state may be determined based on the inspection result by the image processing inspection apparatus 1. The inspection result by the image processing inspection apparatus 1 includes the number of line defects, area luminance, variance, luminance itself, maximum value, minimum value, period pattern area, period pattern interval frequency, and the like.

  Hereinafter, an example in which the number of line defects that is an inspection result of the display panel 2 by the image processing inspection apparatus 1 is used as another parameter will be described. The number of line defects refers to the number of line defects that are one type of defect in a flat panel display, and the line defect is a defect that occurs continuously over a plurality of pixels in the vertical or horizontal direction. In case 4 shown in FIG. 8, when the average luminance decreases in all models, two factors of contact failure and backlight abnormality can be considered, but as described above, depending on whether or not the peak width feature amount has changed. It is possible to determine which abnormality is present.

  However, when the contact failure is severe, the pixel in which the contact failure has occurred is not completely lit. In this case, the luminance of a part of the pixels constituting the lighting peak of the luminance distribution is greatly shifted to the low luminance side and completely overlaps with the non-lighting peak. The lighting peak is a peak 511 shown in FIG. 4B, and the non-lighting peak is a peak 512 shown in FIG. 4B, for example. Since the peak width feature amount is a feature amount calculated from the peak width of the luminance distribution with two peaks of lighting and non-lighting, in the case of extreme contact failure where a part of the lighting peak moves to the non-lighting peak In this case, only the height of the lighting peak decreases and the height of the non-lighting peak increases, and the peak width does not change. For this reason, when judging only from the peak width feature amount and the average luminance, there is a possibility that a contact failure and a backlight abnormality are erroneously judged.

  In such a case, if the number of line defects that is the inspection result of the image processing inspection apparatus 1 is used, an extreme contact failure can be detected as a line defect. However, in the case of a backlight abnormality, even if a part of the backlight fails, the peripheral light compensates for the part of the failed light, so the brightness fluctuation is relatively mild, and line defects Is rarely detected.

  Therefore, in addition to the peak width feature amount and the average luminance, by adding the number of line defects, which is the inspection result of the image processing inspection apparatus 1, to the feature amount, all cases as in the example of case 4 shown in FIG. For example, if the average brightness decreases on the model, if the number of line defects is large, it is determined that the contact is defective, and if the number of line defects is small, if it is determined that the backlight is abnormal, it is a case of severe contact failure. However, the cause of the abnormality can be identified with higher accuracy.

  In the embodiment described above, the program executed by the CPU of the control unit 21 is stored in a storage device (not shown) of the control unit 21, but the program is stored in a storage device (not shown) of the control unit 21. The present invention is not limited to this configuration, and is recorded on a computer-readable recording medium such as the CPU of the control unit 21 and is read from the recording medium and stored in a storage device (not shown) of the control unit 21 during execution. May be. The recording medium may be a recording medium that can be read by providing a program reading device as an external storage device (not shown) and inserting the recording medium therein, or may be a storage device of another device. .

  Any recording medium may be used as long as the stored program is accessed from a computer and executed. Alternatively, any recording medium can be used as long as the program is read, the read program is stored in a storage device (not shown) of the control unit 21, and the program is executed. Furthermore, it may be downloaded from another device via a communication network and stored in a storage device (not shown) of the control unit 21. The download program is stored in advance in a storage device (not shown) of the control unit 21 or is installed in the storage unit 14 from another recording medium.

The recording medium configured to be separable from the main body is, for example, a tape-based recording medium such as a magnetic tape / cassette tape, a magnetic disk such as a flexible disk / hard disk, or a CD-ROM (Compact Disk Read Only Memory) / MO (Magneto Optical). disk) / MD (Mini Disc) / DVD (Digital Versatile Disk) and other optical disk recording media, IC (Integrated Circuit) cards (including memory cards) / optical cards and other card recording media, or masks ROM / EPROM (Erasable Programmable Read Only Memory) / EEPROM (Electrically Erasable Programmable Read Only)
Memory) / a recording medium that carries a fixed program including a semiconductor memory such as a flash ROM. Therefore, the present invention can be provided as a computer-readable recording medium recording a program for causing a computer such as the CPU of the control unit 21 to execute each step of the inspection method executed by the image processing inspection apparatus 1. .

  Thus, when inspecting the display panel 2 on which the display surface on which a plurality of pixels capable of gradation display are arranged is formed, the imaging device 10 has a predetermined display pattern displayed on the display surface of the display panel 2. An image is captured, and image data representing the captured image is generated. The peak width feature amount calculation unit 25 generates a luminance distribution of the captured image based on the image data generated by the imaging device 10, and calculates a feature amount representing the feature of the generated luminance distribution. Based on the image data generated by the imaging device 10, the peak width feature amount calculation unit 25 calculates an average luminance obtained by averaging the luminances of the captured images. For each display panel 2, the peak width feature amount storage unit 26 stores the feature amount calculated by the peak width feature amount calculation unit 25 and the average luminance calculated by the peak width feature amount calculation unit 25. Then, the device state determination unit 27 displays the feature amount variation pattern representing the feature amount stored in the peak width feature amount storage unit 26 in time series, and the average luminance stored in the peak width feature amount storage unit 26 in time series. Based on the expressed average luminance variation pattern, whether or not the abnormality of the display panel 2 detected by the self-image processing inspection apparatus 1 is caused by the self-image processing inspection apparatus 1 and the display panel 2 are manufactured at predetermined time intervals. It is determined whether or not it is caused by the manufacturing process.

  Therefore, it is possible to easily and accurately determine whether the abnormality of the display panel 2 is caused by the abnormality of the image processing inspection apparatus 1 or the abnormality of the manufacturing process without adding a special display pattern or an external device. it can. In addition, the state of the image processing inspection apparatus 1 and the manufacturing process can be continuously and automatically monitored without any manual operation, which can contribute to the improvement of the management capability of the manufacturing process.

  Further, the peak width feature amount calculation unit 25 calculates the feature amount of the image for each of a plurality of predetermined regions in the image region indicated by the image data. The peak width feature amount calculation unit 25 calculates the average luminance of the image for each of the plurality of predetermined regions. The peak width feature amount storage unit 26 stores a feature amount and average luminance for each of the plurality of predetermined regions. Then, the apparatus state determination unit 27 converts the feature quantity for each of the plurality of predetermined areas into a feature quantity variation pattern that represents the time series, and the average brightness variation pattern that represents the average brightness of each of the plurality of predetermined areas with a time series. Based on the plurality of predetermined areas, it is determined whether there is an abnormality in the self-image processing inspection apparatus 1 and whether there is an abnormality in the manufacturing process.

  Therefore, as compared with the case where the evaluation is performed over a wide area of the entire display surface of the display panel 2, the influence of variations such as luminance unevenness in the display surface of the display panel 2 is reduced, and the state of the image processing inspection apparatus 1 is evaluated. It is possible to determine the state of the image processing inspection apparatus 1 at a plurality of locations on the display surface of the display panel 2 as compared with the case where the accuracy is improved and the evaluation is performed only on one region of the display surface of the display panel 2. Become. For example, when the optical axis of the imaging device 10 is tilted with respect to the display surface of the display panel 2, even if the focus of the lens is suitable at a part of the display surface, the focus of the lens is different at a different part. May be non-conforming. Even in such a case, since the state of the image processing inspection apparatus 1 can be individually determined at a plurality of locations on the entire display surface of the display panel 2, the inclination of the optical axis of the imaging apparatus 10 can be detected.

  Further, since the predetermined display pattern is a distribution in which the luminance distribution is composed of only two luminance pixels, it can be inspected by a simple display pattern such as a vertical stripe pattern or a checkered pattern in which the luminance is binary such as black and white. .

  Further, since the feature amount is a standard deviation of luminance, it is possible to determine an abnormality of the image processing inspection apparatus 1 that affects a peak width feature amount such as a focus abnormality of the imaging device 10.

  Further, since the feature amount is a value obtained by dividing the standard deviation of the luminance by the average luminance, the abnormality of the image processing inspection apparatus 1 that affects the peak width feature amount such as the focus abnormality of the imaging device 10 and the backlight abnormality. Thus, it is possible to determine both the abnormality of the image processing inspection apparatus 1 that affects the average luminance. Further, by dividing the standard deviation by the average luminance and normalizing it, it is possible to reduce the influence of the variation in the individual display panels 2 due to the manufacturing process reflected in the peak width feature amount.

  Furthermore, the apparatus state determination unit 27 detects an abnormality in the display panel 2 based on at least one inspection result among a plurality of inspection results by the self-image processing inspection apparatus 1 in addition to the feature amount variation pattern and the average luminance variation pattern. Since it is determined whether or not there is an abnormality in the self-image processing inspection apparatus 1, it can be determined with higher accuracy.

  Furthermore, when inspecting the display panel 2 that includes the imaging device 10 that captures an image and the peak width feature amount storage unit 26 and on which a display surface on which a plurality of pixels capable of gradation display are arranged is illustrated in FIG. In step A1 shown, an image of a predetermined display pattern displayed on the display surface formed on the display panel 2 is captured by the imaging device 10, and image data representing the captured image is generated. In step A3 shown in FIG. 10, a luminance distribution of the captured image is generated based on the image data generated in step A1 shown in FIG. 10, and a feature amount representing a feature of the generated luminance distribution is calculated. . In step A3 shown in FIG. 10, an average luminance obtained by averaging the luminances of the captured images is calculated based on the image data generated in step A1 shown in FIG. In step A4 shown in FIG. 10, for each display panel 2, the feature amount calculated in step A3 shown in FIG. 10 and the average luminance calculated in step A3 shown in FIG. To remember. In step A5 and step A6, the feature amount variation pattern representing the feature amount stored in step A4 shown in FIG. 10 in time series and the average luminance stored in step A4 shown in FIG. 10 in time series. Based on the expressed average luminance variation pattern, whether or not the abnormality of the display panel 2 detected by the self-image processing inspection apparatus 1 is caused by the self-image processing inspection apparatus 1 and the display panel 2 are manufactured at predetermined time intervals. It is determined whether or not it is caused by the manufacturing process.

  Therefore, it is possible to easily and accurately determine whether the abnormality of the display panel is caused by the abnormality of the image processing inspection apparatus 1 or the abnormality of the manufacturing process without adding a special display pattern or an external device. . In addition, the state of the image processing inspection apparatus 1 and the manufacturing process can be continuously and automatically monitored without any manual operation, which can contribute to the improvement of the management capability of the manufacturing process.

  Further, the display panel 2 having the image pickup apparatus 10 for picking up an image, the CPU of the peak width feature amount storage unit 26 and the control unit 21 and having a display surface on which a plurality of pixels capable of gradation display are arranged is inspected. The image of the predetermined display pattern displayed on the display surface formed on the display panel 2 is picked up by the image pickup device 10 on the CPU of the control unit 21 included in the image processing inspection apparatus 1 to perform image data representing the picked up image 10 is generated based on the step A1 shown in FIG. 10 and the image data generated in step A1 shown in FIG. 10, and the feature amount representing the feature of the generated brightness distribution is generated. Based on the image data generated in step A3 shown in FIG. 10 and step A1 shown in FIG. 10, the average luminance obtained by averaging the luminances of the captured images is calculated. 10 for each display panel 2 and the feature quantity calculated in step A3 shown in FIG. 10 and the average brightness calculated in step A3 shown in FIG. The step A4 shown in FIG. 10 to be stored, the feature quantity variation pattern representing the feature quantity stored in step A4 shown in FIG. 10 in time series, and the average luminance stored in step A4 shown in FIG. Based on the average luminance variation pattern expressed in the series, whether or not the abnormality of the display panel 2 detected by the self-image processing inspection apparatus 1 at a predetermined time interval is caused by the self-image processing inspection apparatus 1, and whether the display panel 2 is It can be provided as a program for causing Step A5 and Step A6 to be determined whether or not it is caused by the manufacturing process to be manufactured.

  Further, it can be provided as a computer-readable recording medium in which the program is recorded.

DESCRIPTION OF SYMBOLS 1 Image processing test | inspection apparatus 2 Display panel 10 Imaging device 11 Lens 12 Imaging element 20 Control device 21 Control part 22 Image memory 23 Image data storage part 24 Peak width feature-value calculation area setting part 25 Peak width feature-value calculation part 26 Peak width feature Quantity storage unit 27 Device state determination unit 28 Determination information storage unit 29 Device maintenance instruction unit 30 Display device 61 Panel display surface 62 Imaging area

Claims (9)

An inspection apparatus for inspecting an inspection object on which a display surface on which a plurality of pixels capable of gradation display are arranged is formed,
Imaging means for capturing an image of a predetermined display pattern displayed on the display surface of the inspection object, and generating image data representing the captured image;
Based on the image data generated by the imaging means, a feature quantity calculating means for generating a brightness distribution of the captured image and calculating a feature quantity representing a feature of the generated brightness distribution;
Average luminance calculating means for calculating an average luminance obtained by averaging the luminances of the captured images based on image data generated by the imaging means;
Storage means for storing the feature quantity calculated by the feature quantity calculation means and the average brightness calculated by the average brightness calculation means for each inspection object;
Based on the feature amount variation pattern representing the feature amount stored in the storage unit in time series and the average luminance variation pattern representing the average luminance stored in the storage unit in time series, by the self-inspection apparatus at predetermined time intervals. An inspection apparatus comprising: determination means for determining whether the detected abnormality of the inspection object is caused by the self-inspection apparatus and whether the abnormality is caused by a manufacturing process for manufacturing the inspection object; . The feature amount calculating means calculates a feature amount of an image for each of a plurality of predetermined regions among image regions indicated by the image data,
The average luminance calculating means calculates an average luminance of the image for each of the plurality of predetermined regions,
The storage means stores a feature amount and an average luminance for each of the plurality of predetermined regions,
The determination means is based on the feature amount variation pattern representing the feature amount for each of the plurality of predetermined regions in time series and the average luminance variation pattern representing the average luminance for each of the plurality of predetermined regions in time series. 2. The inspection apparatus according to claim 1, wherein for each of a plurality of predetermined areas, it is determined whether there is an abnormality in the self-inspection apparatus and whether there is an abnormality in the manufacturing process.   The inspection apparatus according to claim 1, wherein the predetermined display pattern is a distribution in which a luminance distribution includes only two luminance pixels.   The inspection apparatus according to claim 1, wherein the feature amount is a standard deviation of luminance.   The inspection apparatus according to claim 1, wherein the feature amount is a value obtained by dividing a standard deviation of luminance by an average luminance.   The determination means determines whether there is an abnormality in the inspection object based on at least one inspection result among a plurality of inspection results by the self-inspection device, in addition to the feature amount variation pattern and the average luminance variation pattern. 6. The inspection apparatus according to claim 1, wherein it is determined whether or not there is an abnormality in the inspection apparatus. An inspection method executed by an inspection apparatus that inspects an inspection object on which a display surface on which a plurality of pixels capable of gradation display are arranged has an imaging unit and a storage unit that capture an image,
An imaging step of capturing an image of a predetermined display pattern displayed on a display surface formed on the inspection object by an imaging unit, and generating image data representing the captured image;
A feature amount calculating step of generating a luminance distribution of the captured image based on the image data generated in the imaging step, and calculating a feature amount representing a feature of the generated luminance distribution;
Based on the image data generated in the imaging step, an average luminance calculation step for calculating an average luminance obtained by averaging the luminances of the captured images;
For each inspection object, a storage step for storing in the storage means the feature amount calculated in the feature amount calculation step and the average luminance calculated in the average luminance calculation step;
Based on the feature amount variation pattern representing the feature amount stored in the storage step in time series and the average luminance variation pattern representing the average luminance stored in the storage step in time series, by the self-inspection apparatus at predetermined time intervals. And a determination step for determining whether the detected abnormality of the inspection object is caused by the self-inspection apparatus and whether the abnormality is caused by a manufacturing process for manufacturing the inspection object. . A computer included in an inspection apparatus that inspects an inspection object on which a display surface on which a plurality of pixels capable of gradation display are arranged has an imaging unit that captures an image, a storage unit, and a computer.
An imaging step of capturing an image of a predetermined display pattern displayed on a display surface formed on the inspection object by an imaging unit, and generating image data representing the captured image;
A feature amount calculating step of generating a luminance distribution of the captured image based on the image data generated in the imaging step, and calculating a feature amount representing a feature of the generated luminance distribution;
Based on the image data generated in the imaging step, an average luminance calculation step for calculating an average luminance obtained by averaging the luminances of the captured images;
For each inspection object, a storage step for storing in the storage means the feature amount calculated in the feature amount calculation step and the average luminance calculated in the average luminance calculation step;
Based on the feature amount variation pattern representing the feature amount stored in the storage step in time series and the average luminance variation pattern representing the average luminance stored in the storage step in time series, by the self-inspection apparatus at predetermined time intervals. A program for executing a determination step of determining whether or not an abnormality of a detected inspection object is caused by a self-inspection apparatus and whether or not the abnormality is caused by a manufacturing process for manufacturing the inspection object.   A computer-readable recording medium on which the program according to claim 8 is recorded.