JP2008139027A - Inspection device, inspection method, image inspection system, manufacturing method of color filter and inspection program - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide an inspection device capable of determining existence of periodicity of unevenness (line unevenness) generating on the surface of the display member such as the color filter being the inspection object. <P>SOLUTION: The inspection device of this invention for inspecting the display member on the image data obtained by photographing the light irradiated display member of the inspection object is provided with: a one-dimensional projection process circuit 110 for one-dimensional processing to the optical direction as the projecting direction to the light distribution information in the photographed image data; and a period analysis process circuit 120 for performing the period analysis of the light distribution information which is one-dimensionally processed by the one-dimensional projection process circuit 110. Thereby, from the results of the periodic analysis the inspection device is capable of determining the period of light distribution in a projection direction in the photographed image. <P>COPYRIGHT: (C)2008,JPO&INPIT

Description

  The present invention relates to an inspection apparatus for inspecting a display member such as a color filter.

  In recent years, display devices such as televisions and monitors have been made thinner and larger, and their demand has increased. Along with this, higher quality display performance is required more than ever.

  Among the components constituting the display device, the color filter for displaying color is one of the important components that influence the display quality. For this reason, the quality required for the color filter has become higher.

  In addition, since the color filter has a high manufacturing cost, it is required to improve the yield of the color filter and reduce the manufacturing cost per sheet.

  Recently, a method for forming a color filter by an ink jet method has attracted attention. In this forming method, the ink is formed by ejecting R (red), G (green), and B (blue) ink from the nozzles of the inkjet head to each picture element. The characteristics of the ink jet method are that the number of steps is small and the waste of ink is small, so that the process can be shortened and the cost can be reduced.

  However, in the case of forming a color filter in the ink jet system, stripe unevenness is particularly likely to occur. As a result, display quality may deteriorate or defective products may appear.

As a technique for inspecting the stripe unevenness, for example, the technique described in Patent Document 1 irradiates light at a predetermined inclination angle, images the film surface irradiated with the light, analyzes the captured image information, and analyzes each undulation. Differences in brightness between them are calculated, and unevenness is detected by estimating the difference in film thickness between the undulations on the film surface.
JP 2006-184125 A (published July 13, 2006)

  By the way, among the uneven stripes on the color filter, due to the human visual characteristics, the uneven stripes generated with periodicity are particularly noticeable, and therefore, uneven stripes with periodicity are not preferable in terms of the quality of the display device.

  For this reason, it is extremely important in the color filter inspection process to determine whether or not the observed uneven stripes have periodicity. In addition, if it is known that the stripe has periodicity, the cause of the stripe unevenness can be easily identified, and when the color filter is manufactured, the cause of the stripe unevenness is fed back to improve the quality.

  However, although the color filter inspection apparatus disclosed in Patent Document 1 can detect the stripe unevenness on the color filter, it does not detect the periodicity of the detected stripe unevenness. For this reason, the cause of the occurrence of uneven stripes cannot be specified, and when producing a color filter, the cause of the occurrence of uneven stripes cannot be fed back, so that it is difficult to improve the quality.

  The present invention has been made in view of the above-described problems, and its purpose is to determine the presence or absence of periodicity of unevenness (straight irregularities) generated on the surface of a display member such as a color filter that is an object to be inspected. Is to realize a simple inspection apparatus.

  In order to solve the above-described problem, an inspection apparatus according to the present invention inspects a display member based on captured image data obtained by imaging an inspection symmetry plane irradiated with light on the display member. The one-dimensional projection processing means for performing one-dimensional projection processing with respect to the light distribution information included in the captured image data with the arbitrary direction as the projection direction, and the light subjected to the one-dimensional projection processing by the one-dimensional projection processing means It is characterized by comprising period analysis processing means for performing period analysis of distribution information.

  Further, in order to solve the above problems, the inspection method according to the present invention inspects the display member based on captured image data obtained by imaging the inspection symmetry plane irradiated with light of the display member. In the inspection method, a first step of performing one-dimensional projection processing with respect to light distribution information included in the captured image data with a given direction as a projection direction, and the one-dimensional projection processing obtained by the first step And a second step of performing periodic analysis of light distribution information later.

  According to the above configuration, the light distribution information in the projection direction in the captured image can be obtained by performing the one-dimensional projection processing on the two-dimensional light distribution information in the captured image data by the one-dimensional projection processing means. Then, by performing periodic analysis of light distribution information in the projection direction in the captured image by the periodic analysis processing means, it is possible to determine the period of light distribution in the projection direction in the captured image from the periodic analysis result.

  Accordingly, if the direction of occurrence of uneven stripes on the surface of the display member is set as the above projection direction, it is possible to determine the presence or absence of periodic stripe irregularities.

  For example, in the case where the display member is a color filter, it is possible to identify a non-uniform stripe having a periodicity among the non-uniform stripes generated on the surface of the color filter, thereby eliminating the non-uniform stripe having the generated periodicity. Thus, a high-quality color filter can be obtained by changing the manufacturing process.

  The period analysis processing means may perform a Fourier transform on the light distribution information.

  According to the above configuration, the periodic analysis processing unit can obtain a periodic function of the light distribution information by performing Fourier transform on the light distribution information subjected to the one-dimensional projection processing by the one-dimensional projection processing unit. .

  If the obtained periodic function is graphed, for example, the operator can easily determine the presence or absence of periodic irregularities on the surface of the display member visually.

  Further, since the periodic function is obtained using Fourier transform, the period of the stripe irregularity can be obtained from this periodic function.

  Thereby, when manufacturing a display member, it becomes possible to identify the cause of the occurrence of stripe unevenness by feeding back the cycle of stripe unevenness. As a result, a display member with high quality can be provided.

  The inspection apparatus having the above-described configuration further includes filtering processing means for performing filtering processing on the light distribution information subjected to the one-dimensional projection processing by the one-dimensional projection processing means using a filter of an arbitrary size, and the periodic analysis processing means includes The period analysis of the light distribution information filtered by the filtering processing means may be performed.

  In the inspection method having the above-described configuration, the light distribution information after the one-dimensional projection processing obtained by the first step is arbitrarily enlarged between the first step and the second step. A filtering process step for performing a filtering process using the filter may be provided, and the second step may perform periodic analysis of the light distribution information after the filtering process obtained by the filtering process step.

  According to the above configuration, the light distribution information subjected to the one-dimensional projection processing by the filtering processing unit is subjected to filtering processing by a filter of an arbitrary size, so that the analysis unit in the subsequent stage has a width larger than the filter size. It is possible to suppress the period of uneven stripes and extract the period of uneven stripes having a width smaller than the filter size.

  In other words, by changing the filter size in the filtering processing circuit, it is possible to extract the period of uneven stripes of various widths, so that the period of uneven stripes of the required width can be emphasized, and as a result, the period of uneven stripes Judgment of the presence or absence of sex can be made easily.

  The filtering process in the filtering process circuit is preferably a morphology process.

  The filtering process in the filtering process circuit is preferably a smoothing process.

  The filtering processing circuit includes a smoothing processing circuit that performs smoothing processing on the light distribution information that has been subjected to the one-dimensional projection processing by the one-dimensional projection processing means, and light that has been smoothed by the smoothing processing circuit. A morphology processing circuit for performing a morphology process on the distribution information, and outputting the light distribution information subjected to the morphology process by the morphology processing circuit to the periodic analysis processing means.

  Further, the filtering processing circuit includes a morphology processing circuit that performs a morphology process on the light distribution information that has been one-dimensionally projected by the one-dimensional projection processing unit, and a light distribution information that has undergone a morphology process by the morphology processing circuit. And a smoothing processing circuit for performing smoothing processing, and output the light distribution information smoothed by the smoothing processing circuit to the periodic analysis processing means.

  According to the above-described configuration, the light distribution information subjected to the one-dimensional projection processing by the one-dimensional projection processing means is subjected to the two types of filtering processing, which are different from the smoothing processing and the morphology processing, and cannot be filtered on the one hand. Or, even if it is a period of a stripe with a width that could not be emphasized, it can be compensated by the other. As a result, it is possible to easily determine the presence or absence of periodic irregularities and to specify the period of uneven stripes.

  The inspection apparatus can be applied to an imaging inspection system as described below.

  That is, the imaging inspection system of the present invention images an illumination device that irradiates light on the front surface or the back surface of a display member, and an inspection symmetry plane that is irradiated with light from the display member in a state where light is irradiated by the illumination device. And an inspection apparatus having the above-described configuration for inspecting the display member based on captured image data captured by the imaging apparatus.

  Further, the color filter manufacturing method of the present invention is a color filter manufacturing method for manufacturing a color filter by a color filter manufacturing apparatus in order to solve the above-described problems, and results of periodic analysis by the above-described inspection method, Only the color filter determined to be non-defective is used for the manufacturing process after the inspection process in the color filter manufacturing apparatus.

  According to the above configuration, in the inspection process included in the color filter manufacturing process, only the color filter determined to be a non-defective product as a result of periodic analysis (the color filter determined to have no periodicity in stripes) is the inspection process. Since it is used for the subsequent manufacturing process of the color filter, the color filter having the periodicity of the stripes does not go through the processes after the inspection process. Therefore, it is not necessary to produce a defective color filter wastefully, so that the yield of the color filter can be improved and the manufacturing cost of the color filter can be reduced.

  In order to solve the above problems, a color filter manufacturing method of the present invention is a color filter manufacturing method for manufacturing a color filter by a color filter manufacturing apparatus. As a result of periodic analysis by the inspection method described above, defective products are obtained. When a color filter determined to be is generated, information indicating that a defective product has occurred is transmitted to the color filter manufacturing apparatus.

  According to the above configuration, in the inspection process included in the color filter manufacturing process, as a result of periodic analysis, a color filter determined to be a defective product (a color filter determined to have periodicity in stripes) occurred. This information is transmitted to the color filter manufacturing apparatus, so that it is possible to take measures such as stopping the color filter manufacturing line on the color filter manufacturing apparatus side. Therefore, it is not necessary to produce a defective color filter wastefully, so that the yield of the color filter can be improved and the manufacturing cost of the color filter can be reduced.

  As described above, the inspection apparatus according to the present invention is the inspection apparatus that inspects the display member based on the captured image data obtained by imaging the inspection symmetry plane irradiated with light from the display member. One-dimensional projection processing means for performing one-dimensional projection processing with respect to the light distribution information included in the captured image data with an arbitrary direction as the projection direction, and light distribution information subjected to the one-dimensional projection processing by the one-dimensional projection processing means. By providing the cycle analysis processing means for performing cycle analysis, there is an effect that the cycle of the light distribution in the projection direction in the captured image can be determined from the cycle analysis result.

  The embodiment of the present invention will be described as follows.

  In the present invention, the display member refers to a member that is used in an image display device and transmits or reflects light or both.

  In this embodiment, a color filter formed by an inkjet method is described as an example of the display member.

  In the following description, a color filter refers to a filter that causes a display device to perform color display by passing light of a specific wavelength. The color filter is formed by discharging a liquid material by an ink jet method onto a glass substrate on which a black matrix is formed. Furthermore, a glass substrate on which a black matrix and a color filter are formed is referred to as a color filter substrate.

[Embodiment 1]
FIG. 2 shows an outline of an imaging inspection system 300 which is an inspection apparatus of the present invention.

  As shown in FIG. 2, the imaging inspection system 300 inspects a color filter substrate 330 that is an object to be inspected, and an illumination device that irradiates light onto the surface (color filter forming surface) of the color filter substrate 330. (Irradiation means) 310, a camera (detection means) 320 that images reflected light from the color filter substrate 330, and a stage 340 on which the color filter substrate 330 is placed.

  The camera (detection unit) 320 includes an output unit that outputs a captured image to the image analysis apparatus (inspection apparatus) 100. Information output from the camera 320 is captured image information including luminance distribution information on the surface of the color filter substrate 330. The luminance distribution information is information indicating a distribution state of luminance values in a predetermined area unit of the color filter substrate 330, for example, a pixel unit.

  Information analyzed by the image analysis device 100 is output to the result output device 400 as unevenness period information described later. Details of the image analysis apparatus 100 will be described later.

  The result output device 400 outputs data that can be confirmed by the operator based on the inputted unevenness period information, for example, graphed data as result data. The output result will be described later.

  The color filter substrate 330 is formed as follows.

  FIG. 3 is a diagram showing a part of the manufacturing process (manufacturing method) of the color filter substrate 330 and a discharging process of the liquid material of the color filter by the ink jet method. The head unit 230 moves in the scanning direction (backward or frontward in the drawing) with respect to the glass substrate 220 on which the black matrix 210 is formed, and the inkjet nozzle 240 scans the liquid material on the glass substrate 220 between the black matrices 210. Discharge sequentially in the direction. When the ejection in the scanning direction is completed, the head unit 230 moves a predetermined distance in a direction orthogonal to the scanning direction (left and right direction in the drawing), and then again in the scanning direction (front or back direction in the drawing). The inkjet nozzle 240 sequentially discharges the liquid material in the scanning direction. By repeating the above operation by the head unit 230, a color filter is formed on the color filter substrate 330.

  At this time, when the discharge amount of the liquid material varies for each nozzle 240 of the head unit 230 for some reason, the color filter is unevenly spaced at the nozzle interval.

  Further, when one nozzle is clogged for some reason, stripes occur in the color filter at intervals of the head unit 230. Specifically, stripes are generated in the scanning direction in units of the number of arrangement of the head unit 230 in the direction orthogonal to the scanning direction of the nozzles 240, for example, in FIG.

  As described above, when the color filter substrate 330 is formed by the ink jet method, uneven stripes having various periods are generated according to the generation cause.

  Such a stripe unevenness is clarified by imaging with the camera 320 which is the imaging means shown in FIG.

  FIG. 4 is a view showing an example of an image obtained by imaging the color filter substrate 330 in a planar shape (two-dimensional) with the camera 320. Here, the stripe unevenness generated when the head unit 230 is used is shown, and in the captured image, the direction parallel to the stripe uneven direction is the Y direction, and the direction perpendicular to the stripe uneven direction is the X direction. . Here, the uneven stripe refers to unevenness that is recognized as a plurality of stripe-shaped unevenness on the color filter forming surface of the color filter substrate 330 due to the difference in film thickness. Accordingly, the “straight line direction” refers to the longitudinal direction of the formed stripe.

  In the present invention, the image analysis device 100 that is an inspection device uses the two-dimensional luminance distribution information (light distribution information) extracted from the planar captured image of the color filter substrate 330 that is the object to be inspected to the surface of the color filter substrate 330. Information for determining the periodicity of stripes occurring in the formed color filter is provided.

  FIG. 1 is a schematic block diagram of an image analysis apparatus 100 that is an inspection apparatus according to the present embodiment.

  As described above, the image analysis apparatus 100 has a function of analyzing the captured image information obtained by the imaging inspection system 300 and outputting it to the result output apparatus 400 as unevenness period information.

  As shown in FIG. 1, the image analysis apparatus 100 includes a one-dimensional projection processing circuit (one-dimensional projection processing means) 110 that converts input two-dimensional luminance distribution information into one-dimensional luminance distribution information, and one-dimensional projection processing. A cycle analysis processing circuit (cycle analysis processing means) 120 for performing cycle analysis of the one-dimensional luminance distribution information converted by the circuit 110, and a CPU 150 for sending control signals including various commands to these processing circuits. I have.

  Specifically, in the image analysis apparatus 100, first, the one-dimensional projection processing circuit 110 acquires captured image information from the imaging inspection system 300 according to an instruction from the CPU 150.

  The one-dimensional projection processing circuit 110 converts the two-dimensional luminance distribution information included in the acquired captured image information into one-dimensional luminance distribution information. Details of the one-dimensional projection processing by the one-dimensional projection processing circuit 110 will be described later. Further, in accordance with an instruction from the CPU 150, the one-dimensional projection processing circuit 110 outputs the one-dimensional projection processing result to the subsequent cycle analysis processing circuit 120.

  The periodic analysis processing circuit 120 performs Fourier transform on the input one-dimensional luminance distribution information and analyzes the periodicity of the one-dimensional luminance distribution information. Details of the cycle analysis processing by the cycle analysis processing circuit 120 will be described later. Further, in accordance with an instruction from the CPU 150, the cycle analysis processing circuit 120 outputs the Fourier analysis processing result to the subsequent result output device 400 as unevenness cycle information.

  The result output device 400 outputs the input unevenness period information in a form that is easy for humans to recognize, for example, a graph. The operator looks at this output result and determines whether or not the stripes having periodicity are present in the color filter formed on the surface of the color filter substrate 330. Therefore, the result output from the result output device 400 may be in any form as long as it can be determined by the operator.

  The reflected light from the imaging inspection system 300 has a larger amount of reflected light in a portion where the thickness of the picture element of the color filter substrate 330 is relatively larger than the other area, and the thickness of the picture element of the color filter substrate 330 is different from the other area. The amount of reflected light is smaller in a portion that is relatively smaller than. This difference in the amount of reflected light is recognized as unevenness.

  Due to the above-described causes, generally, the film thickness difference due to the ink jet method often occurs in a line in the scanning direction of the head unit 230, and when the film thickness difference occurs in a line, the camera (detecting means) 320. A streak is observed in the image data picked up by.

  In addition, as described above, since unevenness that occurs periodically among the unevenness that occurs on the color filter substrate 330 is conspicuous from the relationship of human visual characteristics, it is determined whether or not there is periodic unevenness. Is important for quality improvement.

  Below, the process for determining the presence or absence of periodic irregularities by the image analysis apparatus 100 having the above-described configuration will be described.

  First, the one-dimensional projection processing by the one-dimensional projection processing circuit 110 will be described.

  FIG. 4 is a diagram illustrating an example of an image captured by the camera 320 serving as an imaging unit. Note that the one-dimensional projection processing circuit 110 performs one-dimensional projection processing with respect to the light distribution information included in the image data (for example, FIG. 4) captured by the camera 320, with an arbitrary direction as the projection direction. ing. Here, the projection direction is defined as a direction in which luminance values are added along the above-described streak direction (direction in which one-dimensional projection processing is performed). In the present embodiment, as shown in FIG. 4, the Y direction parallel to the striped direction is set in the captured image.

  Therefore, in the one-dimensional projection processing according to the present embodiment, the above-mentioned arbitrary direction is set as the Y direction, the luminance values are averaged in the Y direction with respect to the image shown in FIG. 4, and the two-dimensional luminance distribution information is obtained. Make one dimension.

Here, the luminance distribution information of the captured image is represented as p _xy . x and y are coordinate values in the X direction and the Y direction, respectively. Using this, the luminance distribution information to be one-dimensionalized is obtained by calculating equation (1).

  Here, N is the number of data in the Y direction.

  FIG. 5 is a graph of the one-dimensional luminance distribution information obtained by the equation (1). The vertical axis is the luminance value, and the horizontal axis is the position of the X coordinate. The unit of the horizontal axis is a pixel (pix).

  The one-dimensional luminance distribution information obtained in this way is Fourier transformed by the subsequent period analysis processing circuit 120.

  In this embodiment, as an example of the one-dimensional projection process, a method of taking an average value of luminance values is used. However, the one-dimensional projection process is particularly suitable if it can convert two-dimensional data to one dimension. It is not limited. For example, a method of integrating the luminance value in the Y direction may be used, or a method of adding and adding weights in the Y direction may be used.

  Next, the cycle analysis process performed by the cycle analysis processing circuit 120 will be described.

  The Fourier transform performed in the period analysis processing circuit 120 is performed using Expression (2).

  The frequency distribution can be obtained by performing Fourier transform using the above equation (2). Furthermore, if the inverse of the frequency is taken, the result can be a function of the period.

  FIG. 6 is a graph showing the result of Fourier transform of the data one-dimensionally projected by the one-dimensional projection processing circuit 110 (graph shown in FIG. 5) as it is. The vertical axis indicates the intensity of the spectrum. The horizontal axis takes the reciprocal of the frequency, converts it to a period, and displays the logarithm. The unit of the period is a pixel (pix).

In this graph, since there is a portion A (a spectrum due to stripe unevenness having a T ₂ Pix period) where a remarkable spectrum is observed, it can be seen that stripe unevenness is generated with periodicity. As described above, by performing the Fourier transform, data (uneven period information) indicating the presence or absence of periodicity of the uneven stripes occurring in the color filter substrate 330 can be obtained.

  Here, the unevenness period information is output in the form of a graph or the like that can be recognized by the operator in the result output device 400, so that the operator can determine the presence or absence of periodic irregularities.

  In addition, you may make it determine automatically the presence or absence of the periodicity of a stripe unevenness from the relationship between the spectrum and period which are contained in nonuniformity period information instead of the visual determination by an operator as mentioned above.

  For example, the determination of the presence or absence of periodic irregularities of the stripes, that is, the determination of whether or not a noticeable spectrum is observed, is performed by reading the stored criterion information and comparing it with the detected spectrum. It is possible to automatically determine the presence or absence of periodicity. This criterion information is registered in the criterion database. For example, the determination reference database may be provided in the result output device 400 of the imaging inspection system 300 or may be provided separately.

  Specifically, as the determination reference information, for example, the moving average of FIG. 6 is taken, and the vicinity of the moving average value (for example, a value obtained by multiplying the moving average value by 1.2 is the upper limit value, and the moving average value is 0.8. There is a method of automatically determining the presence or absence of stripe irregularity by determining whether or not there is a spectrum value that is out of this range. Further, the presence / absence of stripe irregularity may be determined by various other methods.

  In addition, as described above, uneven stripes having various periods are generated according to the cause of occurrence, so information including the width and period of the uneven stripe predicted in advance is associated with the cause of occurrence of uneven stripes, and the determination criterion database. In other words, the cause of the stripe unevenness may be specified from the width and cycle of stripe unevenness included in the detected uneven period information and the registered information.

  For example, as the information to be registered in the determination criterion database, a neighborhood value range including a stripe unevenness period associated with the cause of occurrence of stripe unevenness and a range in the vicinity thereof is used. Then, it is confirmed in order with respect to the registered period whether or not the period included in the unevenness period information is included in the vicinity value range of the period registered in the determination reference database, and registered. Judgment is made based on whether or not it is included in the vicinity value range of the cycle. At this time, if it is determined that the period of the stripe unevenness included in the detected uneven period information is included in the neighborhood value range of a registered period, the cause of occurrence of stripe unevenness of the period can be specified. .

  Here, the reason why the period is set to be expanded to the neighborhood value range is that an error may occur due to the positional deviation of the head unit or other causes, and the range is set in consideration of the error. For example, the neighborhood value range is determined from dimensional error values, operation error values, and experience values of mechanisms such as a head, a nozzle, and a scanning stage. Furthermore, information regarding the width of the stripe unevenness may be added to the determination reference database for determination.

  As described above, it is possible to feed back the determination result to the production process by determining the presence or absence of the periodicity of the stripes.

Furthermore, since the remarkable spectrum is generated in the vicinity of T ₂ pixels, it can be seen that the period of the uneven streaks is about T ₂ pixels. In this way, it is possible to obtain the period of the stripe unevenness by Fourier transform.

  As described above, in general, in the ink jet system, uneven stripes with different periods are observed depending on the cause of the occurrence of uneven stripes.

  Therefore, not only the presence / absence of periodicity of stripes but also the period can be obtained, the cause of the occurrence of stripes can be known and fed back to the production process.

  In this case, as a determination result, in addition to the information indicating the presence or absence of the stripe unevenness, information for specifying the cause of the stripe unevenness described above may be included.

  Hereinafter, an example in which the uneven period information of the color filter on the color filter substrate 330 is fed back to the production process (manufacturing process) of the color filter substrate 330 will be described.

  In the following description, it is assumed that the step of executing the above-described color filter inspection method (hereinafter referred to as a color filter inspection step) is included in a series of manufacturing steps of the color filter substrate 330. For example, in the three manufacturing processes (steps S1 to S3) of the color filter substrate shown in FIG. 7, when considering step S2 indicating the color filter inspection process as a reference, step S1 is a previous process, and step S3 is Next step.

  As shown in FIG. 7, step S1, which is the preceding process, includes a black matrix manufacturing process and a color filter manufacturing process.

  In the black matrix manufacturing process, a negative acrylic photosensitive resin liquid in which fine carbon particles are dispersed by spin coating is applied on a glass substrate, followed by drying to form a black photosensitive resin layer. Then, after exposing a black photosensitive resin layer through a photomask, it develops and forms a black matrix (BM). For example, as shown in FIG. 3, a black matrix 210 is formed on a glass substrate 220. At this time, an opening for use in the color filter manufacturing process, which is the next process, that is, an opening for receiving ink ejected from each nozzle 240 of the head unit 230 (corresponding to each color filter) is formed. Thus, the black matrix 210 is formed.

  In the color filter manufacturing process, as described above, the head unit 230 moves in the scanning direction (backward or frontward in the drawing) with respect to the glass substrate 220 on which the black matrix 210 is formed. Inkjet nozzles 240 sequentially discharge liquid materials on the glass substrate 220 in the scanning direction to form color filters on the glass substrate 220. Note that the black matrix 210 may be formed by inkjet or roller transfer. Moreover, you may perform a surface processing process as needed.

  After the previous process of step S1 is completed, a color filter inspection process is executed (step S2). In this color filter inspection process, the irregularity information of the color filter is detected, and the non-defective product of the color filter is determined from the detection result.

  Here, in the non-uniformity period information, in addition to the information indicating the presence or absence of the stripe unevenness, the information for specifying the cause of the stripe unevenness, the spectrum value in the period in the case of having the stripe unevenness Is included at least.

  For example, in an apparatus for producing a color filter (color filter manufacturing apparatus), when the unevenness period information sent from the image analysis apparatus 100 that is the inspection apparatus includes the fact that a periodicity of uneven stripes exists, By comparing the information included in the unevenness period information with the inspection standard information created and stored in advance, the processing of the color filter that is the work to be inspected (including the processes after the inspection process) is changed according to the comparison result. To do. The inspection standard information may be registered in the above-described determination standard database, or may be registered in another database. If necessary, the inspection standard information may be registered in any database that can be read by the color filter manufacturing apparatus. It may be.

  Changing the processing of the color filter means, for example, that the color filter substrate on which the color filter determined that the spectrum value included in the unevenness period information is not less than the first predetermined value included in the inspection reference information is formed. The color filter substrate on which the color filter determined to be less than the first predetermined value and greater than or equal to the second predetermined value is discarded based on the inspected object processing change information created and stored in advance to the rework process It is to convey. The color filter substrate on which the color filter determined that the spectrum value included in the unevenness period information is less than the second predetermined value is determined to be a non-defective product, and is executed in the next inspection step. It is transported to the manufacturing process.

  The color filter transported to the above rework process is a color filter that is determined to be in a recoverable state, and is transported to the rework process together with rework information including the location information of the abnormal part obtained in the color filter inspection process. After the repair process in this rework process, it is transported again to the inspection process and inspected. The rework process is included in the black matrix manufacturing process and the color filter manufacturing process in step S1 of the color filter substrate manufacturing process. In the rework process, there are a case of local repair that repairs only the abnormal part and a case of full repair of the color filter substrate, and a case that only the color filter is repaired and a case that the black matrix and the color filter are repaired. There are cases.

  Further, in the color filter inspection process in step S2, the spectrum value and the like when it is determined as being for disposal or rework process is fed back to the previous process S1. In the case of feedback to the color filter manufacturing process, the color filter manufacturing process changes the manufacturing conditions in the color filter manufacturing process (for example, adjustment of ink discharge amount, head unit Change the moving speed, etc.) and manufacture the color filter. Further, in the color filter inspection process in step S2, if it is determined that unevenness due to the inappropriate width of the black matrix has occurred, the black matrix manufacturing conditions are compared with the black matrix manufacturing process. A change (adjustment of the formation position of a photomask for forming a black matrix, etc.) is instructed. In the black matrix manufacturing process, the manufacturing conditions are changed according to the instructed contents, and the black matrix is manufactured. In addition, the determination of the change of the manufacturing condition by the spectral value and the judgment reference database may be performed on the pre-manufacturing process side or on the color filter inspection process side, and an instruction to change the manufacturing condition is transmitted to the pre-manufacturing process. May be.

  The color filter substrate on which the color filter determined to be a non-defective product after the inspection is completed as described above is transported to the next step (step S3). Even if it is determined that the product is non-defective, if it is close to the limit value of the non-defective product, an instruction to change the manufacturing conditions is executed so that the next process is executed under the manufacturing conditions that take the color filter inspection results into consideration. May do.

  In step S3, a counter electrode made of a transparent electrode such as ITO is formed by sputtering, and then a columnar spacer (not shown) for defining a cell gap of a liquid crystal panel, for example, is applied with an acrylic photosensitive resin liquid. It is formed by exposure, development and curing with a photomask.

  Thus, the color filter substrate 330 is formed.

  Thus, since the color filter after the inspection can be processed according to the inspection result based on the unevenness period information which is the inspection result obtained in the color filter inspection process, the color filter finally obtained The yield rate can be improved.

  Moreover, even if there is periodicity of stripes, it is determined whether or not restoration is possible depending on the degree of occurrence of stripes (the magnitude of the spectrum value). Not all of the filters are defective, but among the color filters having the unevenness of the stripes, only the color filters having the non-repairable stripes are judged to be defective and discarded. As a result, wasteful disposal of the color filter can be eliminated, so that the yield of the color filter can be improved and the manufacturing cost can be reduced.

  Thereby, the time taken for manufacturing the color filter can be shortened in total.

  The processing change of the color filter that is the work to be inspected may be performed for a single color filter, for all the color filters of the lot to which it belongs, or for all color filters of the same model number. Also good.

  For a color filter determined to be a defective product, marking or the like may be performed at a predetermined position on the color filter substrate or an abnormality occurrence region of the color filter.

  In this case, the color filter determined to be a defective product is not discarded in the manufacturing process but is used by the operator to identify the cause of the defective product.

  In addition, inspection values obtained in the inspection process of a plurality of color filters (or a plurality of locations in the color filter) are stored in an inspection value database (for example, installed in an inspection apparatus) and are registered in advance in a determination reference database. When the conditions applicable to the conditions described in the inspection standard information are met, the described manufacturing process and manufacturing process conditions may be changed.

  For example, the number and occurrence frequency of color filters in which the spectrum value included in the unevenness period information is greater than or equal to a certain reference value (the first predetermined value or the second predetermined value described above) are counted, and the predetermined number or predetermined frequency is exceeded. In this case, based on the manufacturing process change information for changing the manufacturing process according to the inspection result, the manufacturing method is changed by feeding back to the manufacturing process before the process causing the defect.

  As a change in the manufacturing method, for example, the manufacturing conditions of the manufacturing apparatus are changed, a check inspection for the necessity of maintenance of the manufacturing apparatus is started, the manufacturing apparatus is stopped, or the parts causing the occurrence are cleaned. Or exchange.

  Further, the manufacturing method may be changed by transmitting the inspection value to the manufacturing process after the inspection process.

  For example, for a color filter of a lot that belongs to a predetermined number or more of color filters having an inspection value (spectrum value) that exceeds a certain standard, the manufacturing conditions of the next manufacturing process are set in a direction in which a high inspection value is relaxed, for example, the final The luminance value may be changed according to the manufacturing process change information so that the luminance value falls within the range of the final inspection standard.

  In this embodiment, Fourier transform is used for the period analysis process as an example of the period analysis process. However, the period analysis process is not particularly limited as long as it can check the presence of periodicity. Absent.

  In the present embodiment, the display member surface is irradiated with light and the analysis is performed based on the reflected light distribution. However, the analysis may be performed based on the transmitted light distribution.

  Even when the transmitted light distribution is used, the image processing procedure may be the same as the image processing procedure using the reflected light distribution.

  For example, it is conceivable to perform the above-described periodic analysis based on the transmitted light distribution obtained by irradiating the back surface of the display member (color filter) with light and transmitting the light to the front surface which is the color filter forming surface.

  In this case, the illumination device is arranged on the color filter non-formation side (the back side of the display member), and the camera is arranged on the color filter formation side (the front side of the display member). The camera arrangement angle is preferably set to an angle at which unevenness is likely to appear on the color filter forming surface. For example, as in the case of reflection, it is desirable that the irradiation angle with respect to the back surface of the substrate and the emission angle of the transmitted light with respect to the substrate are different from those of the straight transmitted light. Specifically, the lighting device is arranged in the normal direction of the substrate and the camera is arranged at an angle inclined from the normal line of the substrate, or the lighting device is arranged at an angle inclined from the normal line of the substrate, and the camera is arranged in the substrate direction. It is conceivable to arrange them at an angle that is inclined with respect to the normal line direction or the direction of straight transmitted light.

  In the first embodiment, the period analysis process is directly performed on the data subjected to the one-dimensional projection process. However, the filtering process (morphology process) may be performed before the period analysis process is performed.

  In this specification, the filtering process refers to a process of extracting or suppressing unevenness having a certain periodic width with respect to information obtained by one-dimensional projection of light distribution information (luminance distribution information).

  In the following second embodiment, a case where a morphology process is used as an example of a filtering process will be described, and in the third embodiment, a case where a smoothing process is used as an example of a filtering process will be described. In the fourth embodiment, a case in which both morphology processing and smoothing processing are used will be described.

[Embodiment 2]
Another embodiment of the present invention will be described as follows. In the present embodiment, the same processing circuit as the processing circuit described in the first embodiment is given the same name and the same member number, and the description thereof is omitted.

  FIG. 8 is a schematic block diagram of the image analysis apparatus 102 according to the present embodiment. Here, the difference from the image analysis apparatus 100 shown in FIG. 1 of the first embodiment is that a morphology processing circuit 130 is provided after the one-dimensional projection processing circuit 110.

  That is, in the image analysis device 102, the one-dimensional luminance distribution information subjected to the one-dimensional projection processing by the one-dimensional projection processing circuit 110 is filtered by the morphology processing circuit 130, and then the periodic analysis processing is performed by the periodic analysis processing circuit 120. Is called.

  It is assumed that the morphology processing circuit 130 is also controlled by a control signal from the CPU 150 in the same manner as other processing circuits.

  Here, the morphology processing in the morphology processing circuit 130 will be described.

  FIGS. 9A and 9B are schematic diagrams for explaining the morphology processing used in the present embodiment.

  There are two types of morphology processing in the present embodiment: black morphology processing and white morphology processing.

  The black morphology process is a process that suppresses a recess having a width larger than a certain width (filter size) (straightness with a lower luminance value than the surrounding luminance), and the white morphology process is wider than a certain width (filter size). This is a process for suppressing large convex portions (straight unevenness having a higher luminance value than the surrounding luminance).

  The black morphology process performs a maximization process on the one-dimensional data (indicated by a solid line in FIG. 9A) to obtain the maximum luminance value in the filtering region while scanning in the x direction. Then, a maximum value distribution (indicated by a broken line in FIG. 9A) is obtained, and a minimum value processing for obtaining the minimum value of the luminance value in the filtering region is performed while scanning the maximum value distribution in the x direction. Processing for obtaining a minimum value distribution (indicated by a thick line in FIG. 9A), obtaining a difference between the one-dimensional data and the minimum value distribution, and obtaining a morphology distribution (indicated by a solid line in FIG. 9B) It is.

  Specifically, it can be obtained by solving the following equation (3). Here, f is a constant input to determine the filter size, and 2f + 1 is the filter size.

  However, Min [] and Max [] in the expression (3) are operators represented by the following expressions (4) and (5). Minf [] is an operator that selects the minimum value of the number sequence in [], and Maxf [] is an operator that selects the maximum value of the number sequence in [].

  As a result of the black morphology processing, it is possible to extract a concave portion having a width smaller than the filter size (2f + 1).

  The white morphology process is the reverse of the black morphology process and is represented by the following equation (6). In this case, it is possible to extract a convex portion smaller than the filter size (2f + 1).

  FIG. 10 is a flowchart showing the flow of processing of the inspection method in the present embodiment. In this flowchart, the processing in the one-dimensional projection processing circuit 110 is omitted, and the processing flow in the morphology processing circuit 130 and the period analysis processing circuit 120 is shown. The following procedure is performed for each of the white morphology processing and the black morphology processing.

  First, N = 1 is set (step S1). Here, N is a specific integer.

  Next, it is determined whether f = 2N and 2f + 1 is smaller than MAX (step S2). Here, MAX is a specific integer such as 128, 256, 512, or 1024.

  In step S2, if 2f + 1 is smaller than MAX, the filter size is set to 2f + 1, and the morphology process is performed on the luminance distribution information subjected to the one-dimensional projection process (step S3).

  Further, Fourier transformation is performed on the result of the morphology process (step S4).

  Subsequently, the result obtained by the Fourier transform is output to the result output device 400 (step S5).

  Finally, N = N + 1 is set, and the process returns to step S2 (step S6).

  Steps S3 to S6 are repeated until it is determined that 2f + 1 indicating the filter size is equal to or greater than MAX. That is, when it is determined that 2f + 1 is equal to or greater than MAX, the process of the flowchart illustrated in FIG. 10 ends.

  In this way, by comparing the obtained results, it becomes easier to inspect the stripe unevenness period. This will be described below.

Here, the result when the filter size in the white morphology processing is f ₁ pixel and the result when the filter size is f ₂ pixels larger than f ₁ will be described below.

  FIG. 11 is a graph showing the result of performing the morphology process with the filter size set to f1 pixel. The vertical axis is contrast, the horizontal axis is the position of the X coordinate as in the graph of the one-dimensional projection processing result, and the unit is pixel (pix).

  FIG. 12 is a graph showing a result when further Fourier transform is performed from the result of performing the morphology processing shown in FIG. Here, like the Fourier transform result shown in the first embodiment, the vertical axis indicates the spectrum intensity. The horizontal axis takes the reciprocal of the frequency, converts it to a period, and displays the logarithm. The unit of the period is a pixel (pix).

  From the graph shown in FIG. 12, as a result of suppressing the non-uniform stripe having a width larger than the filter size f1 by the morphology process, the spectrum B due to the non-uniform stripe having a period of T1 pixels (a non-uniform stripe having a relatively small width) is output with particular emphasis. I understand that.

In the graph shown in FIG. 12, although the period is the spectrum is observed to a small period of the pixel B1 around than T ₁ pixel, which is the result of the Fourier transform, due to the width of the T ₁ pixel, the period T A harmonic of ₁ appears, indicating that it contributes to the certainty of determining the existence of the spectrum of the fundamental period.

  By performing the morphology process in this way, it becomes easy to inspect the period of unevenness that occurs with a specific period.

13, the filter size as f ₂ pixels, and shows similar to FIG. 11 the results of morphology processing.

  FIG. 14 shows the result when Fourier transform is performed as in FIG.

From the graph shown in FIG. 14, it can be seen that what period of T ₂ pixel A is particularly emphasized.

In the graph shown in FIG. 14, but the period is T _2/2 pixels A1, T _2/3-pixel A2 spectrum also around is observed, which is the result of the Fourier transform, due to the width of the T ₂ pixels It has appeared harmonics of period T ₂ have shown that contributes to the reliability of the determination of the presence of the spectrum of the fundamental period.

Thus, the processing result by comparing a period and a streak streaks and period of T ₁ pixel T ₂ pixels, it can be seen that a mixture.

  In the first embodiment, the period analysis is performed as it is on the data subjected to the one-dimensional projection process. However, as shown in FIG. 6, when a large number of stripes having different periods are mixed, the one-dimensional projection is performed. If the data is subjected to Fourier analysis as it is, it is observed in a state where a plurality of spectra are mixed due to a plurality of stripes having different periods.

  However, as in this embodiment, by performing the morphology process before performing the Fourier transform, in the Fourier transform, when uneven stripes having a plurality of widths are generated at different periods, it is caused by the uneven stripes having a specific width. Since only the spectrum to be emphasized can be observed, it is possible to easily inspect the period of the stripes.

  Furthermore, as described above, by changing the filter size of the morphology processing and repeating the morphology processing and the Fourier transform, various cycles can be extracted according to the processing size of the morphology processing, and the stripes having a specific cycle can be extracted. The spectrum becomes easier to inspect.

[Embodiment 3]
Another embodiment of the present invention will be described as follows. In the present embodiment, the same processing circuit as the processing circuit described in the first embodiment is given the same name and the same member number, and the description thereof is omitted.

  FIG. 15 is a schematic block diagram of the image analysis apparatus 103 according to the present embodiment. Here, the difference from the image analysis apparatus 100 shown in FIG. 1 of the first embodiment is that a smoothing processing circuit 140 is provided after the one-dimensional projection processing circuit 110.

  That is, in the image analysis apparatus 103, the one-dimensional luminance distribution information subjected to the one-dimensional projection processing by the one-dimensional projection processing circuit 110 is filtered by the smoothing processing circuit 140, and then the periodic analysis processing is performed by the periodic analysis processing circuit 120. Done.

  Note that the smoothing processing circuit 140 is also controlled by a control signal from the CPU 150 in the same manner as other processing circuits.

  Here, the smoothing processing in the smoothing processing circuit 140 will be described.

  The smoothing process is a process for obtaining an average value distribution by performing an averaging process for obtaining an average value in a predetermined region while scanning in the x direction with respect to the one-dimensional data.

  Specifically, it can be obtained by solving the following equation (7).

  Here, AV [] is expressed by the following formula (8). AV [] is an operator that selects an average value of a number sequence in [].

  However, as in the case of morphology processing, f is a constant input for determining the filter size, and 2f + 1 is the filter size.

  The smoothing process suppresses uneven stripes having a width equal to or smaller than the filter size (2f + 1), so that the uneven stripe period can be easily obtained.

Figure 16 is a filter size showed the result of the smoothing process of the f ₃ pixels for one-dimensional projection result shown in FIG. The vertical axis represents the luminance value, the horizontal axis represents the position of the X coordinate as in the graph of the one-dimensional projection processing result, and the unit is a pixel (pix).

Thus, the width of the streaks is suppressed streak unevenness of less than f ₃ pixels, easily inspect the period of streaks having a width of more than f ₃ pixels.

  Further, FIG. 17 shows the result of Fourier transform performed on the smoothing processing result by the period analysis processing circuit 120. The vertical axis indicates the intensity of the spectrum. The horizontal axis takes the reciprocal of the frequency, converts it to a period, and displays the logarithm. The unit of the period is a pixel (pix).

  Compared with FIG. 6 of the first embodiment, it can be seen that the spectrum due to the stripe unevenness whose period is T1 pixel observed in FIG. 6 is suppressed in FIG.

Thus, when the filter size is subjected to smoothing process f ₃ pixels, it is possible to suppress the spectrum by uneven streaks occurring in a width smaller than f ₃ pixels (Pix), easy to inspect the period of irregularities Become.

  Also in this case, as in the second embodiment, various cycles are extracted according to the filter size of the smoothing process by changing the filter size of the smoothing process and repeating the smoothing process and the Fourier transform. This makes it easy to inspect the spectrum of stripes having a specific period.

  In this embodiment, as an example of the smoothing process, a method of simply obtaining an average value is used. However, the present invention is not limited to this as long as it is a process that suppresses uneven stripes having a width smaller than a certain width. Absent. For example, smoothing may be performed using local weights, or an approximate curve may be drawn using a polynomial.

[Embodiment 4]
Another embodiment of the present invention will be described as follows. In the present embodiment, the same processing circuit as the processing circuit described in the first to third embodiments is given the same name and the same member number, and the description thereof is omitted.

  FIG. 18 is a schematic block diagram of the image analysis apparatus 104 according to the present embodiment. Here, the difference from the image analysis apparatus 100 shown in FIG. 1 of the first embodiment is that a morphology processing circuit 130 and a smoothing processing circuit 140 are provided after the one-dimensional projection processing circuit 110. Is a point.

  That is, in the image analysis apparatus 104, the one-dimensional luminance distribution information subjected to the one-dimensional projection processing by the one-dimensional projection processing circuit 110 is filtered by the morphology processing circuit 130 and the smoothing processing circuit 140, and then the periodic analysis processing circuit 120. The period analysis process is performed by.

  Note that the morphology processing circuit 130 and the smoothing processing circuit 140 are also controlled by a control signal from the CPU 150 in the same manner as other processing circuits.

  As described above, in the present embodiment, by performing both the filtering processing (morphology processing and smoothing processing) performed in Embodiment 2 and Embodiment 3, respectively, the periodicity of the stripe irregularity and its accuracy can be further improved. The period can be determined.

  In the present embodiment, a case will be described in which after the smoothing processing by the smoothing processing circuit 140, the morphology processing by the morphology processing circuit 130 is performed on the smoothing processing result.

  FIG. 19 shows the result of performing the morphology process shown in the second embodiment on the data (the data shown in the graph of FIG. 16 of the third embodiment) subjected to the smoothing process described above. is there. The vertical axis is contrast, the horizontal axis is the position of the X coordinate as in the graph of the one-dimensional projection processing result, and the unit is pixel (pix).

  Further, FIG. 20 shows a result obtained by performing a Fourier transform by the period analysis processing circuit 120 on the morphology processing result. The vertical axis indicates the intensity of the spectrum. The horizontal axis takes the reciprocal of the frequency, converts it to a period, and displays the logarithm. The unit of the period is a pixel (pix).

  Comparing the graph shown in FIG. 20 with the graph shown in FIG. 15, the graph shown in FIG. 20 emphasizes the spectrum due to the stripe unevenness near the T2 pixel. This is thought to be because other portions were emphasized as a result of suppressing the spectrum due to the stripe unevenness generated with a width smaller than the filter size by the smoothing process. This is a peculiar effect by combining smoothing processing and morphology processing, and this makes it possible to obtain the period of the stripe unevenness with higher accuracy.

  Further, when the graph shown in FIG. 20 is compared with the graph shown in FIG. 15, the graph shown in FIG. 20 suppresses the spectrum due to the stripe unevenness near the T1 pixel. This is considered to be an effect that the spectrum due to the stripe unevenness generated with a width smaller than the filtering size (f3 pixel (Pix)) is suppressed by the smoothing process. As a result, the stripe unevenness period can be obtained with higher accuracy.

  Thus, by performing both the morphology process and the smoothing process, it becomes easier to inspect the period of unevenness.

  Further, in the present embodiment, as in the second and third embodiments, the smoothing process, the morphology process, and the Fourier transform are repeated by changing the filter size of the smoothing process and the morphology process, Depending on the filter size, various periods can be extracted, and the spectrum of a stripe with a specific period can be easily inspected.

  As described above, in the first to fourth embodiments, the morphology process and the smoothing process are used as an example of the filtering process. However, a fixed period is used for information obtained by one-dimensional projection of the light distribution information. If it is the process which extracts or suppresses the unevenness | corrugation of a width | variety, it will not specifically limit to this.

  In the first to fourth embodiments, the color filter created by the ink jet method is used as the object to be inspected. However, the present invention is not limited to this, and the present invention is applicable to color filters created by other manufacturing methods. Can be implemented.

  For example, in the case of a pigment dispersion method in which photolithography is performed for each color, a pixel having a defective color may become uneven, or the surface of the color filter may be damaged due to some reason. The present invention can be implemented.

  Further, in each of the above-described embodiments, an inspection was performed for striped unevenness in the color filter. However, if the unevenness appears on the one-dimensional projection data, the present invention is implemented even if the unevenness is not necessarily a streaky shape. be able to.

  In each of the above-described embodiments, the color filter is used as the object to be inspected. However, the color filter is not particularly limited as long as it is a display member that is used in an image display device and transmits or reflects light or both. For example, a surface glass or a back glass used for a display may be used as an object to be inspected, and a diffusion plate in a backlight unit may be used as an object to be inspected. It can also be applied to inspection of reflectors and screens that project images.

  The present invention is not limited to the above-described embodiments, and various modifications can be made within the scope of the claims.

  Finally, each block of the image analysis apparatuses 100 to 103, in particular, the one-dimensional projection processing circuit 110, the periodic analysis processing circuit 120, the morphology processing circuit 130, and the smoothing processing circuit 140 may be configured by hardware logic, You may implement | achieve by software using CPU as follows.

  That is, the image analysis apparatus 100 includes a central processing unit (CPU) that executes instructions of a control program that realizes each function, a read only memory (ROM) that stores the program, and a random access memory (RAM) that expands the program. And a storage device (recording medium) such as a memory for storing the program and various data. An object of the present invention is a recording medium in which program codes (execution format program, intermediate code program, source program) of a control program of the image analysis apparatus 100, which is software that realizes the above-described functions, are recorded so as to be readable by a computer. This can also be achieved by supplying the image analysis apparatus 100 and reading and executing the program code recorded on the recording medium by the computer (or CPU or MPU).

  Examples of the recording medium include tapes such as magnetic tapes and cassette tapes, magnetic disks such as floppy (registered trademark) disks / hard disks, and disks including optical disks such as CD-ROM / MO / MD / DVD / CD-R. Card system such as IC card, IC card (including memory card) / optical card, or semiconductor memory system such as mask ROM / EPROM / EEPROM / flash ROM.

  Further, the image analysis apparatus 100 may be configured to be connectable to a communication network, and the program code may be supplied via the communication network. The communication network is not particularly limited. For example, the Internet, intranet, extranet, LAN, ISDN, VAN, CATV communication network, virtual private network, telephone line network, mobile communication network, satellite communication. A net or the like is available. Also, the transmission medium constituting the communication network is not particularly limited. For example, even in the case of wired such as IEEE 1394, USB, power line carrier, cable TV line, telephone line, ADSL line, etc., infrared rays such as IrDA and remote control, Bluetooth ( (Registered trademark), 802.11 wireless, HDR, mobile phone network, satellite line, terrestrial digital network, and the like can also be used. The present invention can also be realized in the form of a computer data signal embedded in a carrier wave in which the program code is embodied by electronic transmission.

  The present invention can be applied to any member as long as it has a problem of periodicity of unevenness generated on a surface capable of transmitting or reflecting light.

BRIEF DESCRIPTION OF THE DRAWINGS FIG. 1 illustrates an embodiment of the present invention and is a block diagram illustrating a main configuration of an image analysis apparatus. It is the figure which showed the outline of the imaging inspection apparatus using the image analysis apparatus shown in FIG. It is the figure which showed the manufacturing process of the color filter as a to-be-inspected object. It is the figure which showed the image which imaged the color filter with the imaging device of the imaging inspection apparatus shown in FIG. It is a graph which shows the result of having performed the one-dimensional projection process from the two-dimensional luminance distribution information obtained from the image shown in FIG. It is the graph which showed the result of having performed the Fourier transform with respect to the data of the graph shown in FIG. It is a flowchart which shows the flow of a process of the manufacturing process of a color filter substrate. FIG. 29, showing another embodiment of the present invention, is a block diagram illustrating a main configuration of an image analysis device. (A) and (b) are the graphs which showed the mode of the morphology process by the morphology processing circuit of the image analysis apparatus shown in FIG. It is the flowchart which showed the flow of the inspection method using the image analysis apparatus shown in FIG. FIG. 9 is a graph showing a result of performing a morphology process with a filter size of f1 pixels on the result of the one-dimensional projection process in the image analysis apparatus shown in FIG. 8. It is the graph which showed the result of having performed the Fourier transform with respect to the data of the graph of FIG. 9 is a graph showing a result of performing a morphology process with a filter size of f2 pixels on the result of the one-dimensional projection process in the image analysis apparatus shown in FIG. 8. It is the graph which showed the result of having performed the Fourier transform with respect to the data of the graph of FIG. FIG. 32, showing still another embodiment of the present invention, is a block diagram illustrating a main configuration of an image analysis device. 16 is a graph showing a result of performing a smoothing process with a filter size of f3 pixels on the result of the one-dimensional projection process in the image analysis apparatus shown in FIG. 15. It is the graph which showed the result of having performed the Fourier transform with respect to the data of the graph of FIG. FIG. 32, showing still another embodiment of the present invention, is a block diagram illustrating a main configuration of an image analysis device. FIG. 17 is a graph showing a result of performing morphology processing on the data of the graph of FIG. 16 with a filter size of f2 pixels. It is the graph which showed the result of having performed the Fourier transform with respect to the data of the graph of FIG.

Explanation of symbols

100 Image analysis equipment (inspection equipment)
102 Image analysis device (inspection device)
103 Image analysis equipment (inspection equipment)
104 Image analysis equipment (inspection equipment)
110 One-dimensional projection processing circuit (one-dimensional projection processing means)
120 period analysis processing circuit (period analysis processing means)
130 Morphology Processing Circuit 140 Smoothing Processing Circuit 150 CPU (Central Processing Circuit)
210 Black matrix 220 Color filter substrate 230 Head unit 240 Nozzle 300 Imaging inspection system 310 Illumination device (irradiation means)
320 Camera (detection means)
330 Color Filter 340 Stage

Claims (14)

In the inspection apparatus for inspecting the display member based on the captured image data obtained by imaging the inspection symmetry plane irradiated with light of the display member,
One-dimensional projection processing means for performing one-dimensional projection processing with an arbitrary direction as a projection direction for the light distribution information included in the captured image data;
An inspection apparatus comprising: periodic analysis processing means for performing periodic analysis of light distribution information subjected to one-dimensional projection processing by the one-dimensional projection processing means.   The inspection apparatus according to claim 1, wherein the period analysis processing unit performs a Fourier transform on the light distribution information. Filtering processing means for filtering the light distribution information subjected to the one-dimensional projection processing by the one-dimensional projection processing means with a filter of an arbitrary size,
The inspection apparatus according to claim 1, wherein the periodic analysis processing unit performs periodic analysis of the light distribution information filtered by the filtering processing unit.   The inspection apparatus according to claim 3, wherein the filtering process in the filtering processing unit is a morphology process.   4. The inspection apparatus according to claim 3, wherein the filtering processing in the filtering processing means is smoothing processing. The filtering processing means includes:
A smoothing processing circuit for performing a smoothing process on the light distribution information subjected to the one-dimensional projection processing by the one-dimensional projection processing means;
A morphology processing circuit that performs morphology processing on the light distribution information smoothed by the smoothing processing circuit,
The inspection apparatus according to claim 3, wherein the light distribution information subjected to morphology processing by the morphology processing circuit is output to the period analysis processing means. The filtering processing means includes:
A morphology processing circuit for performing morphology processing on the light distribution information subjected to the one-dimensional projection processing by the one-dimensional projection processing means;
A smoothing processing circuit for performing a smoothing process on the light distribution information subjected to the morphology processing by the morphology processing circuit,
The inspection apparatus according to claim 3, wherein the light distribution information smoothed by the smoothing circuit is output to the period analysis processing means.   The inspection apparatus according to claim 1, wherein the display member is a color filter. An illuminating device that irradiates light onto the inspection symmetry plane of the display member;
An imaging device that images the inspection target surface of the display member in a state where light is irradiated by the illumination device;
An imaging inspection system comprising: the inspection apparatus according to claim 1, wherein the display member is inspected based on captured image data captured by the imaging apparatus. In the inspection method for inspecting the display member based on the captured image data obtained by imaging the inspection symmetry plane irradiated with light of the display member,
A first step of performing one-dimensional projection processing with an arbitrary direction as a projection direction for the light distribution information included in the captured image data;
And a second step of performing a periodic analysis of the light distribution information after the one-dimensional projection processing obtained by the first step. Between the first step and the second step,
There is provided a filtering process step of filtering the light distribution information after the one-dimensional projection process obtained by the first step with a filter of an arbitrary size,
The second step is
The inspection method according to claim 10, wherein a period analysis of the light distribution information after the filtering process obtained by the filtering process step is performed. A color filter manufacturing method for manufacturing a color filter by a color filter manufacturing apparatus,
An inspection process for executing the inspection method according to claim 10 or 11,
A method for producing a color filter, characterized in that only a color filter determined to be a non-defective product as a result of periodic analysis in the inspection method process is used in a manufacturing process after the inspection process in the color filter manufacturing apparatus. A color filter manufacturing method for manufacturing a color filter by a color filter manufacturing apparatus,
An inspection process for executing the inspection method according to claim 10 or 11,
When a color filter determined to be defective as a result of periodic analysis by the inspection process occurs, information indicating that a defective product has occurred is transmitted to the color filter manufacturing apparatus. Manufacturing method.   The inspection program for functioning a computer as each means of the inspection apparatus of any one of Claims 1-8.

Images