KR101940762B1 - Automatic Inspection Apparatus For Display Module And Inspecting Method Of Image Quality Using The Same - Google Patents

Abstract

The present invention includes a first step of calculating an average brightness and a brightness variance for each region of an image of a display module and determining whether the average brightness and the brightness variance satisfy the first and second reference ranges, respectively; A second step of calculating a blurring region width of an edge of a pattern included in the image and determining whether the blurring region width satisfies a third reference range; Generating a grid removal image and a filter application image from the image, generating a difference image from the grid removal image and the filter application image, calculating a noise level of the difference image, and if the noise level satisfies a fourth reference range And a third step of judging whether or not the image quality is good.

Description

Technical Field [0001] The present invention relates to an automatic inspection apparatus for a display module and an image quality inspection method using the same.

The present invention relates to an image quality inspection method, and more particularly, to an automatic inspection apparatus for a display module which inspects image quality quantitatively and automatically checks whether or not a display module is defective, and an image quality inspection method using the same.

A liquid crystal display device, which is one of the flat panel display devices, includes two substrates each having a pixel electrode and a common electrode formed thereon and spaced apart from each other, and a liquid crystal layer formed between the two substrates, Thereby changing the transmittance of the liquid crystal layer to display an image.

Such a liquid crystal display device is manufactured through a TFT process, a CF process, a cell process, and a module process.

In the TFT process, a gate wiring, a data line, a thin film transistor (TFT), a pixel electrode, and the like are formed over a mother substrate, which is also called a bare substrate or a long substrate, A black matrix, a color filter (CF), a common electrode, and the like are formed.

In the cell process, an orientation film is formed on the first mother substrate that has undergone the TFT process and the second mother substrate that has undergone the CF process, and the orientation film is formed by rubbing or the like, and then a seal pattern, The first and second mother substrates are cut by cells, and liquid crystal is injected to complete the liquid crystal panel.

In the module process, a polarizing plate is attached to both surfaces of a liquid crystal panel, and then a driving unit such as a driving integrated circuit is connected, and the liquid crystal panel and the backlight unit are modularized through a top frame, a main frame and a bottom frame to complete a liquid crystal display .

In the module process during the manufacturing process of such a liquid crystal display device, before the liquid crystal display device is completed, the liquid crystal panel to which the backlight unit is coupled, or the liquid crystal panel such as the liquid crystal panel to which the backlight unit and the driving integrated circuit are coupled Proceed with inspection.

The defect inspection of the liquid crystal module is carried out in the automatic inspection equipment. The automatic inspection equipment analyzes the photographed image through a computer or the like to check whether the liquid crystal module is defective such as lighting failure, appearance defect, It is intended to replace the existing visual inspection with the unmanned automated inspection.

However, since the automatic inspection apparatus analyzes the photographed image to determine whether it is defective, the defective detection power of the automatic inspection equipment can be determined according to the quality of the image itself.

Therefore, it is necessary to inspect the quality of the image taken by the automatic inspection equipment before proceeding to the defect inspection on the liquid crystal module in the automatic inspection equipment, and to secure the detection capability of a certain level or more.

The image quality inspection of such automatic inspection equipment is performed visually when the setup of the automatic inspection equipment is completed, or when the deterioration of the automatic inspection equipment is detected during the defect inspection for the liquid crystal module.

The image quality inspection of the automatic inspection equipment by the naked eye takes too much time and causes the problem that the inspection can not proceed in real time.

For example, an average of 60 minutes or more is required per automatic inspection apparatus. Accordingly, when the defect inspection for the liquid crystal module is not performed, the image quality inspection can not proceed in real time. Which causes a decrease in productivity.

In addition, the qualitative results of the image quality inspection of the automatic inspection equipment by the naked eye cause a problem of not providing a common judgment criterion.

For example, the judgment of the inspection result may vary depending on the inspector, and it is judged that the inspection result is defective only when the inspection result is the worst, or when the inspection result is the best, the inspection result is judged to be good, which causes a decrease in the yield of the liquid crystal display device .

Such an automatic inspection apparatus can be used for defect inspection of a display module such as an organic light emitting diode module or a plasma module other than a liquid crystal module. Even in this case, the image quality inspection causes the same problem.

SUMMARY OF THE INVENTION The present invention has been made in order to solve such a problem, and it is an object of the present invention to provide a digital image processing apparatus and a digital image processing method, And an image quality inspection method using the same.

It is another object of the present invention to provide an image quality inspection method using an automatic inspection apparatus for a display module, which can improve the productivity and yield of a display device by real-time image quality inspection and qualitative inspection result.

According to an aspect of the present invention, there is provided an image display apparatus including: a display module for calculating an average brightness and a brightness deviation for each region of an image of a display module, determining whether the average brightness and the brightness deviation satisfy the first and second reference ranges, ; A second step of calculating a blurring region width of an edge of a pattern included in the image and determining whether the blurring region width satisfies a third reference range; Generating a grid removal image and a filter application image from the image, generating a difference image from the grid removal image and the filter application image, calculating a noise level of the difference image, and if the noise level satisfies a fourth reference range And a third step of judging whether or not the image quality is good.

The first step may include dividing the image into a plurality of pixels of the camera, calculating an average value of the gradation areas of the plurality of pixels as the average brightness, And calculating a deviation value for each direction of the gradation of the pixel row or the pixel column among the plurality of pixels by the brightness deviation.

The second step includes setting the position of the start point of the edge to a coordinate (X), setting the fluctuation spreading region width (S) to 1 and setting the gradation of the coordinate (X) A fourth step of determining whether the gray level of the gray level is lower than the gray level of the second gray level; A fifth step of determining whether the grayscale of the coordinate (X) is lower than the grayscale of the normal region; And a sixth step of, when the grayscale of the coordinate (X) is the grayscale of the coordinate (X + 1) or the grayscale of the steady region, determining the swingspeed region width (S) .

In the second step, when the grayscale of the coordinate (X) is lower than the grayscale of the coordinate (X + 1) and the grayscale of the steady region, the fluctuation spreading region width (S) and the coordinate , And repeating the fourth and fifth steps.

In addition, the third step may include: removing the grid from the image to generate the grid removal image; Removing the noise from the grid removal image using a noise filter to generate the filter application image; Subtracting the filtered application image from the grid removal image to generate the difference image; And setting the standard deviation of the gradation of the difference image to the noise level.

The image quality inspection method may further include calculating a rotation angle of the pattern included in the image and determining whether the rotation angle satisfies a fifth reference range.

According to another aspect of the present invention, there is provided a display device comprising: a stage on which a display module is placed; A camera disposed on the stage and generating an image by photographing the display module; Calculating an average brightness and a brightness deviation for each direction of the image, calculating a blurring region width of an edge of a pattern included in the image, generating a grid removal image and a filter application image from the image, And a control unit for generating a difference image from the filter application image and calculating a noise level of the difference image.

Here, the average brightness may be an average value of a plurality of pixels of the plurality of pixels of the camera, and the brightness deviation may be a deviation value of each of the plurality of pixels,

The blurring region width may be the number of pixels from the starting point having a gradation lower than the surrounding to the point having the gradation that is maintained or increased.

The noise level may be a standard deviation of the gradation of the difference image.

The present invention has an effect of realizing image quality inspection in real time and securing a qualitative inspection result by processing images of an automatic inspection equipment for a display module and digitalizing them and deriving inspection results based thereon.

The present invention has the effect of improving the productivity and yield of a display device by real-time image quality inspection and qualitative inspection result.

BRIEF DESCRIPTION OF THE DRAWINGS FIG. 1 is a view showing an automatic inspection equipment for a display module according to an embodiment of the present invention. FIG.
2 is a flowchart showing an image quality inspection method using an automatic inspection apparatus for a display module according to an embodiment of the present invention.
3 is a flowchart illustrating a method of checking brightness in an image quality inspection method using an automatic inspection apparatus for a display module according to an exemplary embodiment of the present invention.
4A to 4D are diagrams for explaining a brightness inspection method among image quality inspection methods using an automatic inspection apparatus for a display module according to an embodiment of the present invention.
5 is a flowchart showing a focus inspection method among image quality inspection methods using an automatic inspection equipment for a display module according to an embodiment of the present invention.
6A and 6B are views for explaining a focus inspection method in an image quality inspection method using an automatic inspection apparatus for a display module according to an embodiment of the present invention.
7 is a flowchart illustrating a noise checking method in an image quality checking method using an automatic testing equipment for a display module according to an embodiment of the present invention.
8A to 8D are diagrams for explaining a noise inspection method in an image quality inspection method using an automatic inspection equipment for a display module according to an embodiment of the present invention.

Hereinafter, an image quality inspection method using an automatic inspection apparatus for a display module according to the present invention will be described with reference to the accompanying drawings.

FIG. 1 is a view illustrating an automatic inspection apparatus for a display module according to an embodiment of the present invention, and FIG. 2 is a flowchart illustrating an image quality inspection method using an automatic inspection apparatus for a display module according to an embodiment of the present invention.

1, an automatic test equipment 10 for a display module according to an embodiment of the present invention includes a stage 20 on which a display module 40 is placed, And a camera module 30 for taking an image of the camera 40 and producing an image.

The camera module 30 includes a lens 32, a charge-coupled device (CCD) camera 34 for photographing an image of the display module 40 incident through the lens 32, And a control unit 36 for analyzing the image to determine whether the image quality and the display module are defective or not. The display unit 40 may be provided with a plurality of image sensing units.

Although not shown, the display module 40 includes a plurality of pixel regions corresponding to red, green, and blue, a black matrix region corresponding between the plurality of pixel regions, and a non-display region corresponding to an edge of the display module 40 And an image displayed by the display module 40 may include a plurality of patterns for image quality inspection such as a focus pattern.

Here, the display module 40 may be a flat panel display module such as a liquid crystal module, an organic light emitting diode module, or a plasma module.

2, when the display module 40 is placed on the stage (20 in Fig. 1) of the automatic inspection equipment (10 in Fig. 1) for inspecting the display module (40 in Fig. 1) , The automatic inspection equipment 10 starts checking the image quality of the display module 40. [

The automatic inspection equipment 10 photographs the display module 40 to produce a plurality of images, and then performs brightness checking on each of the plurality of images (ST110).

The brightness checking of the image includes a calculating step and an adequacy determining step for the average brightness for a specific area of each image and a calculating step and an appropriateness determining step for the brightness deviation with respect to a specific direction of each image, The average brightness and the brightness deviation are calculated using the gray level of a plurality of pixels as basic data, and the average brightness and brightness deviation are calculated based on the reference range And if it is determined that the average brightness and the brightness deviation are within the respective reference ranges, the next step is performed.

The specific steps and criteria for such a brightness check will be described later.

Thereafter, the automatic inspection equipment 10 performs a focus test on each of the plurality of images (st210).

The focus inspection of the image includes the calculation of the blurring area width of an edge of a specific pattern such as the focus pattern of each image and the determination of appropriateness, ), Calculates the blurring region width by using the grayscale of a plurality of pixels as basic data, compares the calculated blurring region width with the reference range, and determines the suitability. If it is determined that the blurring region width is within the reference range , A subsequent step is carried out.

The concrete steps and criteria of such a focus test will be described later.

Thereafter, the automatic inspection equipment 10 performs noise inspection for each of a plurality of images (st310).

The noise inspection of the image includes a grid removal image using each image, a filter application image, a difference image production step, a noise level calculation step, and an adequacy determination step. The grid elimination image, such as the black matrix area of each image, A noise removing filter is applied to each image to produce a filter removing image, a filter applying image is subtracted from the grid removing image to generate a difference image, a noise level is calculated from the difference image, If it is determined that the noise level is within the reference range, the next step is performed.

The specific steps and criteria for such noise testing will be described later.

Thereafter, the automatic inspection equipment 10 performs a tilt test for each of a plurality of images (st410).

The tilt inspection of an image includes a calculation step of a rotation angle of a specific pattern such as a tilt pattern of each image and an adequacy determination step. The rotation angle corresponding to the degree of rotation of a specific pattern from the reference direction is calculated, And if it is determined that the rotation angle is within the reference range, the image quality check is terminated.

If it is determined that the average brightness, the brightness deviation, the blurring area width, or the rotation angle deviate from the reference range in the brightness test (st110), the focus test (st210), the noise test (st310), or the tilt test (st410) It is possible to grasp the cause and correct the corresponding part of the automatic inspection equipment 10 (st510), and to perform the image quality check again after completion of the calibration.

Among these image quality inspection methods, the brightness inspection (st110), the focus inspection (st210) and the noise inspection (st310) will be described in detail with reference to the drawings.

FIG. 3 is a flowchart illustrating a method of checking brightness in an image quality inspection method using an automatic inspection apparatus for a display module according to an exemplary embodiment of the present invention. FIGS. 4A to 4D are views FIG. 4A corresponds to an original image, and FIGS. 4B to 4D correspond to an image in which a non-display area is removed. FIG.

As shown in FIG. 3, when the image quality inspection starts, the automatic inspection equipment 10 starts checking the brightness of each image.

First, as shown in Figs. 4A and 4B, the original image 150 produced by the camera module (30 in Fig. 1) is divided into an effective area 150 (corresponding to a plurality of pixel areas of the display module 40 And an edge area 154 corresponding to a non-display area of the display module 40. The automatic inspection equipment 10 (shown in FIG. 1) includes an edge area 154 that is removed from the original image 150 Only the region 152 is extracted to generate the effective image 156. [

4C, the automatic inspection equipment 10 has a central portion 156a from the effective image 156 and an outer frame portion 156b surrounding the central portion 156a in accordance with a predetermined region classification criterion (ST112).

The automatic inspection equipment 10 divides the central portion 156a into pixel units of the CCD camera 34 of the camera module 30 and uses the grayscale for a plurality of pixels as basic data to obtain the center portion 156a (step st114).

The automatic test equipment 10 determines whether the average brightness of the center portion 156a is within the first average brightness reference range (st116), and the average brightness of the center portion 156a is within the first average brightness reference range If so, proceed to the next step.

Thereafter, the automatic inspection equipment 10 divides the outer frame 156b into pixel units of the CCD camera 34 of the camera module 30, and uses the grayscale for a plurality of pixels as basic data to generate the outer frame 156b Is calculated (st118).

The automatic test equipment 10 determines whether the average brightness of the outer frame portion 156b is within the second average brightness reference range (st120), and the average brightness of the outer frame portion 156b is within the second average brightness reference range If it is judged that it is, the next step is carried out.

Thereafter, the automatic inspection apparatus 10 divides the effective image 156 into pixel units of the CCD camera 34 of the camera module 30, and uses the gradation of a plurality of pixels as basic data to generate an effective image 156 ) (Step 122).

4D, the automatic inspection equipment 10 detects the brightness deviation of the pixel row in the X direction in the horizontal direction and the brightness deviation of the pixel row in the Y direction in the vertical direction among the plurality of pixels of the effective image 156 Can be calculated.

The automatic inspection equipment 10 determines whether the brightness deviation of the effective image 156 is within the brightness deviation reference range (st124) , The brightness check is terminated.

Here, the first and second average brightness reference ranges may be previously set to be equal to or greater than a specific gradation level, and the brightness deviation reference range may be set in advance to be equal to or less than a specific gradation level.

When the average brightness of the center portion 156a and the outer frame portion 156b is determined to be out of the first and second average brightness reference ranges respectively or when the brightness deviation of the direction of the effective image 156 is within the brightness deviation reference range If it is determined that the deviation has occurred, the cause of the deviation is determined and the corresponding part of the automatic inspection equipment 10 is corrected (st510), and the brightness check can be performed again after completion of the calibration.

As described above, the accuracy of the image quality check is improved by determining the brightness level of the effective image 156 by using the average brightness of the entire central portion 156a or the outer frame portion 156b, and the brightness deviation Is added as an image quality inspection item, the detection power of the image quality inspection is improved.

FIG. 5 is a flowchart illustrating a focus inspection method in an image quality inspection method using an automatic inspection apparatus for a display module according to an exemplary embodiment of the present invention. FIG. 6A and FIG. FIG. 6A corresponds to a case where the result of the focus test is good, and FIG. 6B corresponds to a case where the result of the focus test is poor.

As shown in FIG. 5, after the brightness test is completed, the automatic test equipment 10 starts the focus test of each image.

First, the automatic inspection apparatus 10 detects a specific pattern such as a focus pattern from an effective image 156 (FIG. 4B) and extracts a start point of an edge of the specific pattern (ST212).

Then, the automatic inspection equipment 10 sets the position of the corresponding camera pixel unit in the X direction (FIG. 4D) of the start point of the edge as the coordinate X. At this time, the reference of the degree of focusing on the edge, It is possible to set the blurred area on the pixel basis and set the initial value of the fluctuating blurring area width S to 1.

Subsequently, the automatic inspection equipment 10 determines whether or not the gradation of the coordinate X is lower than the gradation of the coordinate X + 1 (st214), the gradation of the coordinate X is the gradation of the coordinate X + If it is judged to be lower than the threshold value, the next step is carried out.

The automatic inspection equipment 10 determines whether the grayscale of the coordinate X is lower than the grayscale of the normal region (st216), and when it is determined that the grayscale of the coordinate X is lower than the grayscale of the normal region, Proceed to step.

Here, the grayscale corresponding to the average brightness calculated by the brightness check can be used as the grayscale of the steady region.

Thereafter, the automatic inspection equipment 10 adds 1 to the fluctuation range width S to set the new fluctuation range width S (st218), adds 1 to the coordinate X, (St220), and repeating the steps (st214, st216) of comparing the gradation of the new coordinate (X) with the gradation of the coordinate (X + 1) and the gradation of the normal region.

That is, the automatic inspection equipment 10 sets the fluctuation spreading region width S and the coordinate X to 1 (1) until the gradation of the coordinate (X + 1) or the gradation of the steady region becomes the gradation of the coordinate (St214, st216) is repeated.

When it is determined that the gradation of the coordinate X is not lower than the gradation of the coordinate X + 1 or the gradation of the coordinate X is not lower than the gradation of the normal region, The value of the fluctuating range width S is determined as the blurring range width S of the edge (st222).

That is, the number of camera pixels from the start point of the edge, which is a point having a gradation lower than the surrounding, to the point where the gradation remains the same or increases, while increasing the coordinate X by 1, is determined as the blurring region of the edge .

Then, the automatic inspection equipment 10 determines whether or not the blurring area width S is within the reference range of the blurring area width (st224). If it is determined that the blurring area width S is within the blurring area width reference range, The focus check is terminated.

Here, the blurred region width reference range can be set in advance to be equal to or less than the number of specific camera pixels.

If it is determined that the fogging area width S is out of the fogging area width reference range, the cause of the fogging area width S is determined and the corresponding part of the automatic inspection equipment 10 is corrected (st510). After completion of the correction, .

For example, as shown in FIGS. 6A and 6B, when the first flare area width S1 is equal to or smaller than the number of specific camera pixels in the flare area width reference range, the focus inspection can be terminated. If the width S2 is greater than the number of specific camera pixels, which is the reference range of the blurring area width, the focus test can be restarted through the cause identification and the corresponding partial correction.

FIG. 7 is a flowchart illustrating a noise checking method in an image quality checking method using an automatic testing equipment for a display module according to an exemplary embodiment of the present invention. FIGS. 8A to 8D are views illustrating an automatic checking method for a display module according to an exemplary embodiment of the present invention 8A to 8C correspond to the effective image, the grid removal image, and the filter application image, respectively, and FIG. 8D corresponds to the grid removal image and the filter application image, respectively. And corresponds to the generated difference image.

As shown in Fig. 7, after the focus inspection is completed, the automatic inspection equipment 10 starts the noise inspection of each image.

First, as shown in FIGS. 8A and 8B, the automatic inspection equipment 10 removes the grid from the valid image 156 (FIG. 4B) to generate the grid removal image 158 (st312).

The grid may be a regular pattern corresponding to a black matrix area of the display module (40 in Fig. 1) and having a lower gradation than the periphery.

Thereafter, as shown in FIG. 8C, the automatic inspection equipment 10 generates a noise canceling image 160 by removing noise from the grid elimination image 158 using a noise filter (st314).

For example, the noise filter may be a low-pass filter, a sigma filter, a median filter, or a Nagao-Matsuyama filter.

8D, the automatic inspection equipment 10 generates (st316) a difference image 162 by subtracting the noise removal image 160 from the grid removal image 158, The noise level is calculated from the difference image 162 (st318).

That is, only the noise component of the grid removal image 158 is left by subtracting the noise removal image 160 from the grid removal image 158, and the standard deviation of the gradation of the difference image 162 including only the noise component You can set the noise level of the image.

Thereafter, the automatic test equipment 10 determines whether the noise level is within the noise level reference range (st320), and ends the noise test when it is determined that the noise level is within the noise level reference range.

Here, the noise level reference range can be set in advance to be equal to or lower than a specific gradation level.

If it is determined that the noise level is out of the reference range of the noise level, the cause of the noise level is determined and the corresponding part of the automatic inspection equipment 10 is corrected (st510).

Then, after the image quality, such as brightness, focus, noise, etc., of the image satisfies the reference range, defect inspection for the display module 40 is performed.

As described above, in the automatic inspection equipment for a display module and the image quality inspection method using the automatic inspection equipment according to the present invention, the image of the automatic inspection equipment is processed to digitize it, and the brightness inspection, the focus inspection, It is possible to improve the precision and the detection power of the quality inspection and to carry out the image quality inspection with a qualitative result value in real time and as a result, the productivity and the yield of the display device are improved.

It will be apparent to those skilled in the art that various modifications and variations can be made in the present invention without departing from the spirit or scope of the invention as defined in the appended claims. It can be understood that

10: automatic inspection equipment 20: stage
30: camera module 40: display module
st110: Brightness check st210: Focus check
st310: noise inspection st410: tilt inspection

Claims (11)

A first step of calculating an average brightness and a brightness deviation for each region of the image of the display module and determining whether the average brightness and the brightness deviation satisfy the first and second reference ranges, respectively;
A second step of calculating a blurring region width of an edge of a pattern included in the image and determining whether the blurring region width satisfies a third reference range;
Removing the grid from the image to generate the grid removal image, removing noise from the grid removal image using a noise filter to generate the filter application image, subtracting the filter application image from the grid removal image, And a third step of setting the standard deviation of the gradation of the difference image to the noise level and determining whether the noise level satisfies a fourth reference range .
The method according to claim 1,
In the first step,
Dividing the image into a plurality of pixels of the camera, calculating an average value of the gradation areas of the plurality of pixels as the average brightness;
Calculating a deviation value for each direction of the gradation of a pixel row or a pixel column among the plurality of pixels as the brightness deviation
The image quality inspection method comprising:
The method according to claim 1,
The second step comprises:
(X + 1), the variable spreading region width (S) is set to 1, and the gradation of the coordinate (X) is determined to be lower than the gradation of the coordinate 4 steps;
A fifth step of determining whether the grayscale of the coordinate (X) is lower than the grayscale of the normal region;
A sixth step of determining the fluctuation region width S as the fogging region width when the grayscale of the coordinate X is the grayscale of the coordinate (X + 1) or the grayscale of the steady region,
The image quality inspection method comprising:
The method of claim 3,
The second step comprises:
(X) is increased by 1 when the gradation of the coordinate (X) is lower than the gradation of the coordinate (X + 1) and the gradation of the normal region, Step 4 and Step 5 are repeated
The image quality inspection method further comprising:
delete The method according to claim 1,
Further comprising calculating a rotation angle of the pattern included in the image and determining whether the rotation angle satisfies a fifth reference range.
A stage on which the display module is placed;
A camera disposed on the stage and generating an image by photographing the display module;
And a control unit,
The control unit may include a first step of calculating an average brightness and a brightness deviation of each direction of the image of the display module and determining whether the average brightness and the brightness deviation satisfy the first and second reference ranges, A second step of calculating a blurring region width of an edge of a pattern included in the image and determining whether the blurring region width satisfies a third reference range; Removing the grid from the image to generate the grid removal image, removing noise from the grid removal image using a noise filter to generate the filter application image, subtracting the filter application image from the grid removal image, And a third step of determining whether the noise level satisfies a fourth reference range by setting the standard deviation of the gradation of the difference image to the noise level, Inspection equipment.
8. The method of claim 7,
Wherein the average brightness is an average value of the gradation areas of the plurality of pixels of the camera,
Wherein the brightness deviation is a deviation value by a direction of the gradation of a pixel row or a pixel column among the plurality of pixels.
8. The method of claim 7,
Wherein the blurred region width is the number of pixels from a starting point having a gradation lower than the surrounding to the point having the gradation that is maintained or increased equally.
8. The method of claim 7,
Wherein the noise level is a standard deviation of a gradation of the difference image. 8. The apparatus of claim 7, wherein the noise filter is a low-pass filter, a sigma filter, a median filter, or a Nagao-Matsuyama filter.

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