JP4440007B2 - Image evaluation method for plasma display panel - Google Patents

Description

  The present invention relates to an image evaluation method for evaluating an image displayed on a plasma display panel.

  The plasma display panel is configured such that a front substrate and a rear substrate are arranged to face each other so that a discharge space is formed therebetween, a peripheral portion is sealed, and a rare gas is sealed in the discharge space. A plurality of display electrodes composed of scan electrodes and sustain electrodes are formed on the front substrate, and a plurality of address electrodes are formed on the rear substrate in a direction orthogonal to the display electrodes. A discharge cell which is a unit light emitting region is formed in the part. In this plasma display panel, a predetermined voltage is applied to the display electrode and the address electrode to generate a discharge selectively in each discharge cell, and the phosphor layer formed in each discharge cell emits light by discharge, An image is displayed.

When manufacturing such a plasma display panel, it is necessary to evaluate the performance of the panel. For example, Patent Document 1 discloses a method for evaluating the performance of a plasma display panel.
JP 11-86731 A

  A plasma display panel is desired to have a uniform display image with no variation in luminance. However, in the actual display image, luminance unevenness occurs because the difference in emission luminance between discharge cells becomes large due to factors such as significant variations in the discharge start voltage in each discharge cell constituting the plasma display panel. If a person views the display image at this time, the display image feels rough. The luminance unevenness referred to here is luminance unevenness caused by a luminance difference for each discharge cell (brightness unevenness in units of discharge cells), and is luminance unevenness generated within a minute range. Such uneven brightness needs to be evaluated in the panel inspection process.

  However, in the actual inspection, there is no method for quantitatively evaluating and inspecting the luminance unevenness of the discharge cell unit, and the inspection of the luminance unevenness of the discharge cell unit has to be performed by the visual evaluation of the inspector. However, the inspection by visual inspection by the inspector is a sensory inspection in which human senses affect the inspection, and the evaluation value may differ depending on the inspector. Also, the evaluation value may vary depending on the physical condition of the inspector, and it is difficult to always perform evaluation based on the same standard.

  The present invention has been made to solve such a problem, and an object of the present invention is to enable appropriate evaluation and inspection of luminance unevenness in discharge cell units generated in a plasma display panel.

  In order to achieve the above object, the present invention captures an image of a plasma display panel by an imaging means, performs an isolated point removal process on the captured image, and an image on which the isolated point removal process has been performed. A step of performing a peripheral comparison process in which an amount based on a difference between the image data of the target pixel and the image data of the peripheral pixels is used as the image data of the target pixel; and the target pixel is applied to the image subjected to the peripheral comparison process. Performing a maximum value filtering process using the maximum value of the image data in the pixels in the vicinity area of the target pixel as the image data of the target pixel; Performing a minimum value filtering process using the minimum value of the image data in the pixel as the image data of the target pixel, and performing the minimum value filtering process A plasma display panel image evaluation method comprising: performing binarization processing on an image; and evaluating a plasma display panel image using the binarized image. is there.

  ADVANTAGE OF THE INVENTION According to this invention, the evaluation about the brightness nonuniformity of the discharge cell unit which can generate | occur | produce in a plasma display panel can be performed quantitatively, and the appropriate evaluation and test | inspection about the brightness nonuniformity can be performed.

  According to a first aspect of the present invention, there is provided an image evaluation method for a plasma display panel having a plurality of discharge cells between a pair of substrates and displaying an image by generating a discharge in each discharge cell. The image of the plasma display panel is captured by the step of performing isolated point removal processing on the captured image, and the image data of the target pixel and the surrounding pixel image data for the image subjected to the isolated point removal processing And a step of performing a peripheral comparison process using the amount based on the difference as the image data of the target pixel, and a maximum value of image data in pixels in the vicinity region of the target pixel with respect to the image subjected to the peripheral comparison process A maximum value filtering process using the target pixel image data as a target pixel image data, and for the image subjected to the maximum value filtering process, Performing a minimum value filtering process using the minimum value of the image data in the pixels in the side region as the image data of the target pixel; and performing a binarization process on the image subjected to the minimum value filter process; And a step of evaluating an image of the plasma display panel using the image subjected to the binarization processing.

  The invention described in claim 2 is characterized in that, in the invention described in claim 1, the maximum value filter processing and the minimum value filter processing are each performed a plurality of times.

  The invention described in claim 3 is the invention described in claim 1, characterized in that the number of pixels existing between the target pixel and the peripheral pixels in the peripheral comparison processing is 10 pixels or less.

  Hereinafter, an embodiment of the present invention will be described with reference to the drawings.

  First, the structure of the plasma display panel will be described with reference to FIG. As shown in FIG. 1, the front panel 1 is formed from a dielectric glass so as to form a plurality of display electrode pairs composed of scan electrodes 3 and sustain electrodes 4 on a glass front substrate 2 and to cover the display electrode pairs. The dielectric layer 5 is formed, and the protective layer 6 made of magnesium oxide (MgO) is formed on the dielectric layer 5.

  On the other hand, the back panel 7 disposed opposite to the front panel 1 has a plurality of address electrodes 9 formed on a glass back substrate 8, and a dielectric layer 10 is formed so as to cover the address electrodes 9. A plurality of partition walls 11 parallel to the address electrodes 9 are formed on the body layer 10, and phosphor layers that emit light of red (R), green (G), and blue (B) colors between the adjacent partition walls 11. 12 is formed. The address electrode 9 is located between the adjacent partition walls 11.

  The front substrate 2 and the rear substrate 8 which are a pair of substrates are opposed to each other so that the scan electrodes 3 and the sustain electrodes 4 and the address electrodes 9 are orthogonal to each other, and a peripheral portion of these substrates is a sealing member (not shown). It is sealed using. A discharge gas made of neon and xenon is sealed in a discharge space formed between the front substrate 2 and the rear substrate 8, and a discharge cell is formed at the three-dimensional intersection of the scan electrode 3, the sustain electrode 4 and the address electrode 9. It is formed. That is, a plurality of discharge cells are provided between a pair of substrates. This discharge cell is a unit light emitting region for displaying an image, and one pixel is formed by three adjacent discharge cells formed with phosphor layers 12 that emit light in R, G, and B colors.

  In this plasma display panel, an image is displayed by generating a discharge in each discharge cell. That is, a discharge cell to be displayed is selected by sequentially applying a scan pulse to the scan electrode 3 and applying an address pulse to the address electrode 9 based on the image data, and then alternately maintained on the scan electrode 3 and the sustain electrode 4. By applying a pulse, a sustain discharge is generated in the selected discharge cell. As a result, ultraviolet rays are generated in the discharge cells in which the sustain discharge has occurred, and visible light of each color is emitted from the phosphor layer 12 excited by the ultraviolet rays, and image display is performed.

  Next, a method for evaluating luminance unevenness in units of discharge cells when performing panel inspection on such a plasma display panel will be described. FIG. 2 is an overall configuration diagram of a system that quantitatively evaluates luminance unevenness in units of discharge cells in an embodiment of the present invention.

  As shown in FIG. 2, the plasma display panel 13 to be inspected is mounted on the panel holding unit 14 and driven by the drive circuit 15. The power supply 16 supplies power to the drive circuit 15, and the signal generator 17 supplies signals to the drive circuit 15, and the power supply 16 and the signal generator 17 are controlled by the control device 18. Further, a camera 19 such as a CCD camera as an imaging means captures an image displayed on the plasma display panel 13 and outputs it as digital image data having intensity data of R, G and B for each pixel of the camera 19. To do. Here, it is desirable that the camera 19 has a resolution that allows the pixels of the camera 19 to measure at least one pixel with respect to one pixel of the plasma display panel 13. The image memory 20 as image storage means temporarily stores an image of the plasma display panel 13 captured by the camera 19 as image data. The image processing unit 21 is configured mainly with a CPU, for example, and performs various processes using the image data stored in the image memory 20 and outputs an evaluation result.

  FIG. 3 is a flowchart of image evaluation in this embodiment. Steps 1 to 8 are sequentially performed, and an evaluation result is output. Using this evaluation method, the quality of the panel can be determined in the panel inspection process when the plasma display panel 13 is manufactured. Hereinafter, each step will be described.

  First, in step 1, an image corresponding to a signal from the signal generator 17 is displayed on the plasma display panel 13 installed in the panel holding unit 14. Then, an image displayed on the plasma display panel 13 is picked up using the camera 19, and digital image data R (red data), G (red data), which are intensity data of red, green, and blue in each pixel of the camera 19, respectively. Green data) and B (blue data) are stored in the image memory 20. Here, the image displayed on the plasma display panel 13 is, for example, displayed in white by lighting all the discharge cells.

  Next, in step 2, luminance conversion processing is performed on the image data stored in the image memory 20. In the luminance conversion processing, image data Y representing the luminance of each pixel is obtained by converting the image data R, G, and B of each pixel in the captured image using, for example, Equation 1 below. If the image data stored in the image memory 20 is data representing the luminance of each pixel, step 2 may be omitted.

  In the next step 3, isolated point removal processing is performed on the image having the image data Y obtained in step 2. It is desirable to use one of the two methods shown in FIG. 4 or 5 for the isolated point removal processing. 4 and 5, the input image is an image before the isolated point removal process is performed, and the numerical values in the drawings are the values of the image data Y for a part of the pixels, that is, the image data f (x, y) of the input image. Represents the value of. Here, x and y specify the position of the pixel, and the horizontal direction is x and the vertical direction is y. The output image is an image after the isolated point removal process is performed on the input image, and the numerical values in the figure are the values of the image data for the target pixel, that is, the image data F (x, y) of the output image. Represents a value. Here, the target pixel is a pixel to be subjected to isolated point removal processing, and a pixel to be subjected to each processing in step 4 and subsequent steps is referred to as a target pixel.

  As shown in FIG. 4, the first method of the isolated point removal process is an intermediate value filter process in which the image data in the target pixel of the input image is replaced with the intermediate value of the image data in the pixels in the vicinity region. In the example of FIG. 4, the target pixel and eight pixels surrounding the target pixel are employed as the pixels in the vicinity region. That is, although the x-direction filter size and the y-direction filter size are both 3, this value can be changed as appropriate. Then, the value of the image data F (x, y) after the intermediate value filter processing in the target pixel is arranged in the order of the size of the image data f (x, y) in the target pixel and the surrounding eight pixels in the input image. It is the value (19) that comes to the center.

  As shown in FIG. 5, the second method of the isolated point removal process is a smoothing filter process that replaces the image data in the target pixel of the input image with the average value of the image data in the pixels in the vicinity region. In FIG. 5, as in the case of FIG. 4, the target pixel and eight pixels surrounding the target pixel are adopted as the pixels in the vicinity region, but can be changed as appropriate. Then, the value of the image data F (x, y) after the smoothing filter processing in the target pixel is the average value (24) of the image data f (x, y) in the target pixel and the surrounding eight pixels in the input image. It has become.

  These intermediate value filter processing and smoothing filter processing are both isolated point removal processing for the purpose of removing isolated points and removing and suppressing noise in the image.

  In the next step 4, peripheral comparison processing is performed on the image that has undergone isolated point removal processing in step 3. As the peripheral comparison process, a primary differentiation process for comparing the image data of the target pixel of the input image with the image data of the pixel existing in the two directions, or a secondary differentiation process for comparing with the image data of the pixel existing in the four directions. Can be used. Hereinafter, the peripheral comparison process will be described with reference to FIGS. 6 and 7. In each figure, the image data of the input image at the pixel specified by x and y is f (x, y), and the image data of the output image Is F (x, y).

  As shown in FIG. 6, the first-order differentiation process is f (x, y) for image data of a certain target pixel, f (x + 1, y) for image data of a pixel located to the right of the target pixel, Assuming that the image data of the pixel located immediately below is f (x, y + 1), for example, the absolute value of G (x, y) obtained by the following equation 2 is the image data F (x, y) It is. That is, as the peripheral pixels, two pixels located right next to and below the target pixel are selected, and the sum of the differences between the image data of the target pixel and the image data of the peripheral pixels is set in the target pixel. This is image data of the output image.

And when calculating the data example of the input image shown in FIG.
G (x, y) = 2 × 11−30−5 = −13
Thus, the image data F (x, y) of the output image at the target pixel is 13.

  In addition, as shown in FIG. 7, the second-order differentiation process is performed by using f (x, y) for image data of a certain target pixel, and f (x−1, y) for image data of a pixel located to the left of the target pixel. ), The image data of the pixel located right next to the target pixel is f (x + 1, y), the image data of the pixel located next to the target pixel is f (x, y−1), and next to the lower side of the target pixel. Assuming that the image data of the pixel located is f (x, y + 1), for example, the absolute value of G (x, y) obtained by Equation 3 shown below is the image data F (x, y). That is, four pixels located on the left side, right side, top side, and bottom side of the target pixel are selected as the peripheral pixels, and the sum of the differences between the image data of the target pixel and the image data of the peripheral pixels is large. This is the image data of the output image at the target pixel.

And when calculating the data example of the input image shown in FIG.
G (x, y) = 4 × 11−51−30−55−5 = −97
Therefore, the image data F (x, y) of the output image at the target pixel is 97.

  As described above, in the peripheral comparison process, the amount based on the difference between the image data of the target pixel and the image data of the peripheral pixel is used as the image data of the target pixel. When such peripheral comparison processing is performed, if the luminance of the target pixel is significantly different from the luminance of the peripheral pixels, the image data of the output image at the target pixel becomes a large value. In other words, in the output image when the peripheral comparison process is performed, pixels having a large luminance difference with the surrounding pixels have large image data, and pixels having a small luminance difference with the peripheral pixels have small image data. is doing. For this reason, it can be determined that luminance unevenness occurs in units of discharge cells in the pixel having large image data and in the vicinity thereof.

  In the above description, as an example when the peripheral comparison process is performed, the target pixel and the peripheral pixel are adjacent to each other. However, for example, a pixel located three pixels to the right of the target pixel or a pixel located five pixels above. The peripheral comparison processing may be performed using the image data of the target pixel and the image data of the peripheral pixel, with the pixel to be processed as the peripheral pixel. However, since the detection target is uneven luminance in units of discharge cells, it is desirable that the number of pixels existing between the target pixel and the peripheral pixels is 10 pixels or less.

  Here, with respect to the image obtained by performing the peripheral comparison process in step 4, a certain threshold value is set, and a binarization process of extracting pixels whose image data is equal to or higher than the threshold value is performed. An example when the result is represented in an image is shown in FIG. In FIG. 10, a region represented by a black dot is a region where pixels whose image data is equal to or greater than a threshold value exist, that is, a region where a pixel having a large luminance difference from surrounding pixels exists. At this stage, as can be seen from FIG. 10, the extracted regions are scattered, and therefore it is difficult to accurately evaluate the luminance unevenness in units of discharge cells. Therefore, in the present embodiment, the maximum value filtering process in step 5 and the minimum value filtering process in step 6 are performed so that the extracted regions are grouped so that the luminance unevenness in units of discharge cells can be accurately evaluated. .

  In step 5 following step 4, the maximum value filtering process is performed once or a plurality of times on the image subjected to the peripheral comparison process in step 4. The maximum value filtering process is a process for replacing the image data in the target pixel of the input image with the maximum value of the image data in the pixels in the vicinity region. In the maximum value filter processing shown in FIG. 8, the target pixel and eight pixels surrounding the target pixel are adopted as the pixels in the vicinity region. That is, both the x-direction filter size and the y-direction filter size are set to 3. The image data F (x, y) of the output image at the target pixel is the maximum value (55) of the image data f (x, y) at the pixels in the vicinity region in the input image.

  According to this maximum value filter processing, if there is a pixel having large image data in the vicinity area, even if the image data of the target pixel is small, it is converted to the maximum image data in the vicinity area. Even in a peripheral region of a pixel having large image data, the output image has large image data. For this reason, scattered pixels having large image data in the input image are grouped, and a predetermined region is gathered to some extent in the output image.

  In the next step 6, the minimum value filtering process is performed once or a plurality of times on the image subjected to the maximum value filtering process in step 5. The minimum value filtering process is a process of replacing the image data in the target pixel of the input image with the minimum value of the image data in the pixels in the vicinity region. In the minimum value filter processing shown in FIG. 9, the target pixel and eight pixels surrounding the target pixel are adopted as the pixels in the vicinity region. That is, both the x-direction filter size and the y-direction filter size are set to 3. The image data F (x, y) of the output image at the target pixel is the minimum value (3) of the image data f (x, y) at the pixels in the vicinity region in the input image.

  By the maximum value filtering process in step 5, pixels having large image data are scattered to form a predetermined area, and the outer peripheral portion of the predetermined area is It is wider than the line surrounding the existing pixel group. Therefore, by performing minimum value filter processing, the predetermined area is narrowed to become an appropriate area.

  If the maximum value filtering process and the minimum value filtering process are performed too many times, proper image evaluation cannot be performed. Therefore, the number of performing these processes is appropriately set so that proper image evaluation can be performed. For example, by performing the maximum value filtering process and the minimum value filtering process about 2 to 3 times, it was possible to evaluate the luminance unevenness in units of discharge cells.

  In the above-described maximum value filter processing and minimum value filter processing, the x-direction filter size and the y-direction filter size are both 3, but these values can be changed as appropriate.

  In the next step 7, a binarization process is performed in which a certain threshold value is set for the image that has been subjected to the minimum value filter process in step 6, and pixels whose image data is equal to or greater than the threshold value are extracted. An example of the output image after the series of processing from Step 1 to Step 7 is performed is shown in FIG. In FIG. 11, a detection unit A and a detection unit B are regions where pixels having image data equal to or greater than the threshold value exist.

  Next, in step 8, determination processing is performed to determine the luminance unevenness in units of discharge cells of the plasma display panel 13 using the detection units A and B extracted in step 7. As the determination index used in this determination process, the detection unit area, the total detection unit difference sum, the detection unit average difference sum, and the like are used. Here, when a plurality of detection units are detected (two in the case of FIG. 11), the detection unit area, the detection unit total difference sum, and the detection unit average difference sum are defined for each detection unit. Although the detection unit A will be described below, the detection unit B is defined in the same manner.

The detection unit area is the total number of pixels included in the detection unit A. The total detection unit difference is the sum of image data for all pixels of the detection unit A in the output image at the end of step 6. The detection unit average difference sum is an average value for the image data of all the pixels of the detection unit A in the output image at the end of step 6.
The sum of the detection part average difference = the total difference of the detection part / the area of the detection part. By using any one of these determination indexes or a combination of a plurality of determination indexes, it is possible to inspect the luminance unevenness of the discharge cell unit of the plasma display panel quantitatively and accurately. For example, a predetermined determination reference value is determined for each of the detection unit area, the detection unit total difference sum, and the detection unit average difference sum that are determination indexes, and the detection unit area, the detection unit total difference sum, and the detection unit average difference sum If any one of them is larger than the determination reference value, the luminance unevenness in discharge cell units is large, and it is determined that the panel is defective. Can be judged.

  As described above, according to the present invention, it is possible to quantitatively evaluate luminance unevenness in discharge cell units that can occur in a plasma display panel, which is useful for inspection of plasma display panels.

The perspective view which shows a part of plasma display panel in one embodiment of this invention 1 is an overall configuration diagram of a system for evaluating brightness unevenness in units of discharge cells according to an embodiment of the present invention. The flowchart explaining the flow of the image evaluation in one embodiment of this invention Explanatory drawing of intermediate value filter processing Illustration of smoothing filter processing Explanatory drawing of first derivative processing Explanatory drawing of the secondary differentiation process Explanatory drawing of maximum value filter processing Illustration of minimum value filter processing The figure which shows an image when the image after a periphery comparison process is binarized The figure which shows an image when the image after a minimum value filter process is binarized

Explanation of symbols

2 Front substrate 8 Back substrate 13 Plasma display panel 19 Camera 20 Image memory 21 Image processing unit

Claims (3)

In an image evaluation method for a plasma display panel that has a plurality of discharge cells between a pair of substrates and displays an image by generating a discharge in each discharge cell, the image of the plasma display panel is picked up by an image pickup means and picked up A step of performing isolated point removal processing on the image, and an amount based on the difference between the image data of the target pixel and the image data of the surrounding pixels with respect to the image subjected to the isolated point removal processing. A step of performing a peripheral comparison process as data, and a maximum value filter having a maximum value of image data in pixels in a region near the target pixel as the image data of the target pixel with respect to the image subjected to the peripheral comparison process Processing step, and image data at pixels in the vicinity region of the target pixel is applied to the image subjected to the maximum value filter processing. Performing a minimum value filter process using the minimum value as the image data of the target pixel, performing a binarization process on the image subjected to the minimum value filter process, and performing the binarization process And a step of evaluating an image of the plasma display panel using the obtained image. 2. The plasma display panel image evaluation method according to claim 1, wherein the maximum value filtering process and the minimum value filtering process are each performed a plurality of times. 2. The plasma display panel image evaluation method according to claim 1, wherein the number of pixels existing between the target pixel and the peripheral pixels in the peripheral comparison processing is 10 pixels or less.

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