Spot detection device, spot detection method, and display device

Abstract

A spot detection device, a spot detection method, and a display device are provided. The spot detection device includes an imager and a spot detector, in which: the imager is configured to capture a display panel displaying a first image of a first gray scale and a second image of a second gray scale different from the first gray scale, and generate image data; and the spot detector is configured to receive the image data from the imager to detect a spot. The image data includes first image data obtained by capturing the first image, second image data obtained by capturing the second image, and a plurality of third image data obtained by capturing a portion of the first image.

Description

[0001] Cross-references to related applications

[0002] This application claims priority to Korean Patent Application No. 10-2019-0092931, filed on July 31, 2019, and Korean Patent Application No. 10-2019-0104935, filed on August 27, 2019, the entire contents of which are incorporated herein by reference. Technical Field

[0003] This invention relates to display devices. Specifically, this disclosure relates to a spot detection apparatus with improved spot detection reliability, a spot detection method, and a display device having information related to the detected spots. Background Technology

[0004] After the display panel is manufactured, a spot inspection process can be performed to check for spots or scratches on the display panel during its operation. Through this process, spots of various patterns can be inspected using various inspection devices. Once a spot is detected, it can be corrected by reflecting the inspection results. Summary of the Invention

[0005] This disclosure provides a spot detection apparatus and a spot detection method with improved spot detection reliability.

[0006] This disclosure also provides a display device having information relating to spots detected by a spot detection device and a spot detection method.

[0007] Embodiments of this disclosure provide a speckle detection apparatus, comprising: an imager configured to capture a display panel displaying a first image of a first gray level and a second image of a second gray level different from the first gray level, and to generate a plurality of image data; and a speckle detector configured to receive image data from the imager to detect specks, wherein the image data includes first image data obtained by capturing the first image, second image data obtained by capturing the second image, and a plurality of third image data obtained by capturing portions of the first image.

[0008] In one embodiment, the imager may include a first camera for capturing the entire display area of ​​the display panel and a second camera for capturing a portion of the display area.

[0009] In some implementations, the imager may also include a third camera for capturing another portion of the display area.

[0010] In one implementation, the second camera can capture a portion of the display area from a first position and another portion of the display area from a second position different from the first position.

[0011] In one embodiment, the imager may include a camera, wherein the camera may acquire first image data and second image data at a first position, and acquire at least some of a plurality of third image data at a second position different from the first position.

[0012] In an implementation, the speckle detector may include a first filter for removing impulse noise from first image data, second image data, and a plurality of third image data, wherein the first filter may convert the first image data, second image data, and a plurality of third image data into first intermediate data, second intermediate data, and a plurality of third intermediate data, respectively, through an intermediate value filter.

[0013] In an implementation, the speckle detector may further include a computational processor for removing noise from the first intermediate data, the second intermediate data, and a plurality of third intermediate data, wherein the computational processor may convert the first intermediate data, the second intermediate data, and the plurality of third intermediate data into first response data, second response data, and a plurality of third response data, respectively, through a morphological operation process.

[0014] In an implementation, the computation processor may include: a first maximum value filter configured to filter first intermediate data, second intermediate data, and a plurality of third intermediate data using a mask of size a×a; a first minimum value filter configured to filter a set of data filtered by the first maximum value filter using a mask of size (2a+1)×(2a+1); a second minimum value filter configured to filter the first intermediate data, second intermediate data, and a plurality of third intermediate data using a mask of size a×a; a second maximum value filter configured to filter a set of data filtered by the second minimum value filter using a mask of size (2a+1)×(2a+1); an averager configured to average the data filtered by the first minimum value filter and the corresponding data filtered by the second maximum value filter; and a synthesizer configured to generate first response data, second response data, and a plurality of third response data by removing the corresponding average data derived by the averager from the first intermediate data, second intermediate data, and a plurality of third intermediate data, respectively.

[0015] In an implementation, the processing unit may include: a second filter configured to filter first intermediate data, second intermediate data, and a plurality of third intermediate data using a mask of size a×a; a third filter configured to filter a set of data filtered by the second filter using a mask of size (2a+1)×(2a+1); and a synthesizer configured to generate first response data, second response data, and a plurality of third response data by removing corresponding data filtered by the third filter from the first intermediate data, second intermediate data, and a plurality of third intermediate data, respectively.

[0016] In an implementation, the speckle detector may further include a selector configured to select speckle candidates for first response data, second response data, and a plurality of third response data, wherein the selector can convert the first response data, second response data, and a plurality of third response data into first candidate data, second candidate data, and a plurality of third candidate data, respectively.

[0017] In an implementation, the speckle detector may further include: a comparator configured to generate result data by comparing first candidate data, second candidate data, and a plurality of third candidate data; and a quantization unit configured to quantize the specks of the result data.

[0018] In an embodiment of the present invention, the display device includes a display panel, a first printed circuit board electrically connected to the display panel, and a memory mounted on the first printed circuit board. The memory stores spot information detected based on first image data, second image data, and a plurality of third image data. The first image data is obtained by capturing a first image at a first gray level displayed on the display panel. The second image data is obtained by capturing a second image at a second gray level different from the first gray level displayed on the display panel. The plurality of third image data are obtained by capturing portions of the first image.

[0019] In an implementation, the blob information may be information relating to common blobs included in all of a first blob group detected in first image data, a second blob group detected in second image data, and a third blob group detected in a plurality of third image data.

[0020] In an embodiment of the present invention, the spot detection method includes: capturing a first image of a first gray level displayed on a display panel to generate first image data; capturing a second image of a second gray level different from the first gray level displayed on the display panel to generate second image data; capturing a portion of the first image to generate a plurality of third image data; and detecting spots using the first image data, the second image data, and the plurality of third image data.

[0021] In this implementation, the first image data and multiple third image data can be obtained by cameras positioned at different locations.

[0022] In an implementation, the step of detecting blots may include: filtering the first image data, the second image data, and a plurality of third image data through an intermediate value filter to generate first intermediate data, second intermediate data, and a plurality of third intermediate data.

[0023] In an implementation, the step of detecting spots may further include: morphologically processing the first intermediate data, the second intermediate data, and a plurality of third intermediate data to generate first response data, second response data, and a plurality of third response data.

[0024] In an implementation, the step of detecting spots may further include: selecting spot candidates from first response data, second response data, and a plurality of third response data to generate first candidate data, second candidate data, and a plurality of third candidate data.

[0025] In an implementation, the step of detecting spots may further include: generating result data by comparing first candidate data, second candidate data, and multiple third candidate data; and quantifying the spots in the result data.

[0026] In an implementation, the step of generating result data may include: generating first preliminary result data by removing values ​​that are not present in the second candidate data from the first candidate data; and generating result data by removing values ​​that are not present in a plurality of third candidate data from the first preliminary result data. Attached Figure Description

[0027] The accompanying drawings are included to provide a further understanding of the inventive concept and are incorporated in and constitute a part of this specification. The drawings illustrate exemplary embodiments of the present disclosure and, together with the description, serve to explain the principles of the inventive concept. In the drawings:

[0028] Figure 1A This is a top view of a display panel according to an embodiment of the present disclosure;

[0029] Figure 1B This is a block diagram of a spot detection apparatus according to an embodiment of the present disclosure;

[0030] Figure 2 This is a flowchart of a spot detection operation according to an embodiment of the present disclosure;

[0031] Figure 3A This is a top view of an imager according to an embodiment of the present disclosure;

[0032] Figure 3B This is a top view of a display panel according to an embodiment of the present disclosure;

[0033] Figure 4A This is a top view of an imager according to an embodiment of the present disclosure;

[0034] Figure 4B This is a top view of a display panel according to an embodiment of the present disclosure;

[0035] Figure 5 This is a top view of an imager according to an embodiment of the present disclosure;

[0036] Figure 6A It is the image corresponding to the first image data;

[0037] Figure 6B It is the image corresponding to the second image data;

[0038] Figure 6C It is the image corresponding to the third image data;

[0039] Figure 7 This is a block diagram of a speckle detector according to an embodiment of the present disclosure;

[0040] Figure 8A This is a block diagram of an arithmetic processor according to an embodiment of the present disclosure;

[0041] Figure 8B This is a block diagram of an arithmetic processor according to an embodiment of the present disclosure;

[0042] Figure 9A It is the image corresponding to the first response data;

[0043] Figure 9B It is the image corresponding to the second response data;

[0044] Figure 9C It is the image corresponding to the third response data;

[0045] Figure 10A It is the image corresponding to the first candidate data;

[0046] Figure 10B It is the image corresponding to the second candidate data;

[0047] Figure 10C It is the image corresponding to the third candidate data;

[0048] Figure 11 This is a flowchart of the operation for generating result data according to the embodiments of this disclosure;

[0049] Figure 12 It is the image corresponding to the result data;

[0050] Figure 13This is a graph illustrating an example of quantifying the resulting data; and

[0051] Figure 14 It is a display device according to an embodiment of the present disclosure. Detailed Implementation

[0052] In this specification, when a component (or region, layer, part, etc.) is referred to as being “on”, “connected to”, or “combined to” another component, it means that the component may be directly on, connected to, or combined to the other component, or that a third component may be present between them.

[0053] The same reference numerals denote the same elements. Furthermore, in the accompanying drawings, the thickness, proportions, and sizes of the parts are exaggerated for the sake of effective description.

[0054] "And / or" includes all of one or more combinations defined by the relevant components.

[0055] It should be understood that the terms "first" and "second" are used herein to describe various components, but these components should not be limited by these terms. The terms are used only to distinguish one component from another. For example, without departing from the scope of the inventive concept, a first component may be referred to as a second component, and conversely, a second component may be referred to as a first component. Singular expressions include plural expressions unless the context clearly indicates otherwise.

[0056] Furthermore, terms such as "below," "lower side," "upper," and "upper side" are used to describe the relationships of the configurations shown in the accompanying drawings. These terms are described as relative concepts based on the directions in the accompanying drawings.

[0057] Unless otherwise defined, all terms used herein (including technical and scientific terms) have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. Generally, terms defined in dictionaries should be considered to have the same meaning as in the context of the relevant art, and should not be interpreted anomalously or as having an overly formal meaning unless clearly defined herein.

[0058] In various embodiments of the present invention, the terms "include", "comprise" or "comprising" specify attributes, areas, fixed quantities, steps, processes, elements and / or components, but do not exclude other attributes, areas, fixed quantities, steps, processes, elements and / or components.

[0059] Figure 1A This is a top view of a display panel 1000 according to an embodiment of the present disclosure. Figure 1BThis is a block diagram of a spot detection apparatus according to an embodiment of the present disclosure.

[0060] refer to Figure 1A and Figure 1B The display panel 1000 can be a device activated by an electrical signal. The display panel 1000 can be included in various electronic devices. For example, in addition to large electronic devices such as televisions, monitors, or billboards, the display panel 1000 can also be used in medium-sized electronic devices such as personal computers, laptop computers, personal digital terminals, car navigation units, game consoles, portable electronic devices, or cameras. Furthermore, these are presented only as embodiments, and it is obvious that the display panel 1000 can be used in other electronic devices without departing from the scope of this disclosure.

[0061] Display panel 1000 can display images through display area 1000-D. Display area 1000-D can have multiple pixels, and each of the multiple pixels can include sub-pixels. Sub-pixels can be, for example, red sub-pixels, blue sub-pixels, and green sub-pixels. However, this is just an example, and the colors of the sub-pixels constituting a pixel can be changed differently.

[0062] Before applying the display panel 1000 to an electronic device, an inspection can be performed to detect spots on the display panel 1000. Afterward, a correction value for compensating the detected spots can be calculated and stored in memory. Therefore, the display panel 1000 can display an image in which the spots have been corrected.

[0063] The spot detection device 100 can be used to inspect spots on the display panel 1000. For example... Figure 1B As shown, the speckle detection device 100 may include an imager 2000 and a speckle detector 3000.

[0064] Imager 2000 can capture images displayed by display panel 1000. Imager 2000 may include at least one camera. For example, display panel 1000 may display a first image at a first grayscale level or a second image at a second grayscale level. Imager 2000 can capture the first image and the second image. Furthermore, a portion of the first image can be captured. This will be described in more detail below.

[0065] Display panel 1000 displays a first image on the entire surface of display area 1000-D during a first time period, and a second image on the entire surface of display area 1000-D during a second time period. The first grayscale level and the second grayscale level can be different from each other. The second grayscale level can be a grayscale level adjacent to the first grayscale level. For example, the first grayscale level can be 64 grayscale levels, and the second grayscale level can be 32 grayscale levels. Alternatively, the first grayscale level can be 128 grayscale levels, and the second grayscale level can be 64 grayscale levels. The first grayscale level and the second grayscale level can be changed depending on the type of display panel 1000 to be inspected.

[0066] The imager 2000 can generate first image data 10 obtained by capturing a first image, second image data 20 obtained by capturing a second image, and third image data 30 obtained by capturing a portion of the first image, and transmit them to the speckle detector 3000. The third image data 30 may be data obtained by capturing the first image at an angle different from the angle of the first image data 10.

[0067] The speckle detector 3000 can detect specks by receiving first image data 10, second image data 20, and third image data 30. The speckle detector 3000 can be a processing unit. For example, the speckle detector 3000 can be a graphics processing unit.

[0068] Figure 2 This is a flowchart of a spot detection operation according to an embodiment of the present disclosure.

[0069] refer to Figure 2 The blob detection operation may include: a step of generating first image data, second image data, and multiple third image data (S100); a step of generating first intermediate data, second intermediate data, and multiple third intermediate data by filtering the first image data, second image data, and multiple third image data (S200); a step of generating first response data, second response data, and multiple third response data by performing morphological operations on the first intermediate data, second intermediate data, and multiple third intermediate data (S300); a step of generating first candidate data, second candidate data, and third candidate data by selecting blob candidates from the first response data, second response data, and multiple third response data (S400); a step of comparing the first candidate data, second candidate data, and third candidate data to generate result data (S500); and a step of quantizing the blobs in the result data (S600). Each of the above operations is described in detail below.

[0070] Figure 3A This is a top view of an imager 2000 according to an embodiment of the present disclosure. Figure 3BThis is a top view of a display panel 1000 according to an embodiment of the present disclosure.

[0071] refer to Figure 2 , Figure 3A and Figure 3B The imager 2000 can be used to detect spots. Therefore, fine spots that are difficult to detect with the naked eye can also be easily detected by the imager 2000.

[0072] The imager 2000 generates first image data 10, second image data 20, and third image data 30 (S100).

[0073] The imager 2000 may include a support fixture 2100, a first camera 2200, a second camera 2300, a third camera 2400, a fourth camera 2500, and a fifth camera 2600.

[0074] The support fixture 2100 may define a first region P1, a second region P2, a third region P3, a fourth region P4, and a fifth region P5. The first region P1 may be defined in the central region of the support fixture 2100. The second region P2, the third region P3, the fourth region P4, and the fifth region P5 may be defined around the first region P1.

[0075] The first camera 2200, the second camera 2300, the third camera 2400, the fourth camera 2500, and the fifth camera 2600 can be mounted on the support fixture 2100. For example, the first camera 2200 can be set in the first region P1, the second camera 2300 can be set in the second region P2, the third camera 2400 can be set in the third region P3, the fourth camera 2500 can be set in the fourth region P4, and the fifth camera 2600 can be set in the fifth region P5.

[0076] The first camera 2200 can capture the entire display area 1000-D of the display panel 1000. The first camera 2200 can generate first image data 10 by capturing a first image at a first grayscale level, and generate second image data 20 by capturing a second image at a second grayscale level.

[0077] According to embodiments of this disclosure, when detecting blobes by comparing two images at different gray levels, noise that only occurs at a specific gray level can be removed. The noise is not the blob to be corrected.

[0078] The second camera 2300, the third camera 2400, the fourth camera 2500, and the fifth camera 2600 can generate third image data 30 corresponding to a portion of the display area 1000-D. For example, as... Figure 3BAs depicted, the display area 1000-D can be divided into four sub-display areas 1001, 1002, 1003, and 1004. The second camera 2300, the third camera 2400, the fourth camera 2500, and the fifth camera 2600 can respectively capture images of the sub-display areas 1001, 1002, 1003, and 1004 to generate third image data 30.

[0079] For example, the second camera 2300 captures a first image of a first grayscale level displayed in the first sub-display area 1001 to generate third image data 30. The third camera 2400 captures a first image of a first grayscale level displayed in the second sub-display area 1002 to generate third image data 30. The fourth camera 2500 captures a first image of a first grayscale level displayed in the third sub-display area 1003 to generate third image data 30. The fifth camera 2600 captures a first image of a first grayscale level displayed in the fourth sub-display area 1004 to generate third image data 30. The location of the sub-display area captured by each of the second camera 2300, the third camera 2400, the fourth camera 2500, and the fifth camera 2600 is not limited to the above example.

[0080] The first image data 10 and the third image data 30 may be data obtained by capturing a first image having the same first grayscale level. However, the first image data 10 may be image data obtained by a first camera 2200 located at a first position (e.g., first region P1). The third image data 30 may be image data obtained by a second camera 2300, a third camera 2400, a fourth camera 2500, and a fifth camera 2600 located at positions different from the first position (e.g., second region P2, third region P3, fourth region P4, and fifth region P5).

[0081] Spots on the display panel 1000 itself are visible from any angle and are spots to be corrected. However, since the protective film is removed from the final product, scratches formed on the protective film are not spots to be corrected. Depending on the viewing angle, scratches may be visible or invisible. According to embodiments of this disclosure, spots can be detected using image data obtained at positions where the display panel 1000 is viewed at different angles. Therefore, the possibility of misidentifying scratches formed on the protective film (not shown) attached to the display panel 1000 as spots on the display panel 1000 itself can be reduced.

[0082] Figure 4A This is a top view of an imager 2001 according to an embodiment of the present disclosure. Figure 4B This is a top view of a display panel 1000 according to an embodiment of the present disclosure.

[0083] refer to Figure 4A and Figure 4B The imager 2001 may include a support fixture 2100, a first camera 2200, a second camera 2301 and a third camera 2401.

[0084] The support clamp 2100 may define a first region P1, a second region P2-1, and a third region P3-1. The second region P2-1 and the third region P3-1 may be spaced apart from each other relative to the first region P1 inserted between them.

[0085] A first camera 2200 is located in a first region P1, a second camera 2301 is located in a second region P2-1, and a third camera 2401 is located in a third region P3-1. In one embodiment, the first camera 2200, the second camera 2301, and the third camera 2401 may be fixed to the first region P1, the second region P2-1, and the third region P3-1, but are not limited thereto. For example, in one embodiment, the second camera 2301 and the third camera 2401 may be movable on a support clamp 2100.

[0086] The first camera 2200 can capture the entire display area 1000-D of the display panel 1000. The first camera 2200 can generate first image data 10 by capturing a first image at a first grayscale level, and generate second image data 20 by capturing a second image at a second grayscale level.

[0087] The second camera 2301 and the third camera 2401 can generate third image data 30 corresponding to a portion of the display area 1000-D. The second camera 2301 can generate the third image data 30 by capturing a first image of a first grayscale level displayed in the first sub-display area 1001-1, and the third camera 2401 can generate the third image data 30 by capturing a first image of a first grayscale level displayed in the second sub-display area 1002-1.

[0088] In one implementation, the third camera 2401 can be omitted. In this case, the second camera 2301 can capture an image of a portion of the display area 1000-D in the second area P2-1 and an image of another portion in the third area P3-1. That is, the position of the first camera 2200 can be fixed, and the second camera 2301 can move on the support clamp 2100.

[0089] Figure 5 This is a top view of an imager 2002 according to an embodiment of the present disclosure.

[0090] refer to Figure 5The imager 2002 may include a support clamp 2100 and a camera 2200-1. The camera 2200-1 may move on the support clamp 2100. For example, the camera 2200-1 may move between a first region P1, a second region P2, a third region P3, a fourth region P4, and a fifth region P5, and may capture images of the display panel 1000.

[0091] Figure 6A It is the image corresponding to the first image data 10. Figure 6A The image shown can be referred to as a grayscale detection image.

[0092] refer to Figure 3A and Figure 6A The first image data 10 can be captured and acquired by a camera disposed in the first region P1 of the support fixture 2100. The first image data 10 can be data obtained by capturing a first image at a first gray level. The first gray level can be 64 gray levels, but is not limited thereto.

[0093] Figure 6B It is the image corresponding to the second image data 20. Figure 6B The image shown can be referred to as a neighboring grayscale image.

[0094] refer to Figure 3A and Figure 6B The second image data 20 can be captured and acquired by a camera positioned in the first region P1 of the support fixture 2100. The second image data 20 can be data obtained by capturing a second image at a second gray level. The second gray level can be 32 gray levels, but is not limited to this.

[0095] Figure 6C It is the image corresponding to the third image data 30. Figure 6C The image shown can be referred to as a detection grayscale view image. Figure 6C The image can be set with Figure 6A Images obtained from cameras at different camera positions.

[0096] refer to Figure 3A and Figure 6C The third image data 30 can be captured and acquired by cameras located in the second region P2, the third region P3, the fourth region P4, and the fifth region P5 of the support fixture 2100. The third image data 30 can be data obtained by capturing a portion of the first image at a first gray level. The first gray level can be 64 gray levels, but is not limited to this.

[0097] Figure 7 This is a block diagram of a speckle detector 3000 according to an embodiment of the present disclosure.

[0098] refer to Figure 2 and Figure 7 The speckle detector 3000 may include a first filter 3100, an arithmetic processor 3200, a selector 3300, a comparator 3400, and a quantization unit 3500. The quantization unit 3500 may be referred to as a quantization circuit.

[0099] The first filter 3100 receives first image data 10, second image data 20, and third image data 30. Thereafter, the first filter 3100... Figure 2 As shown in step S200, the first image data 10 is filtered to generate the first intermediate data 11, the second image data 20 is filtered to generate the second intermediate data 21, and the third image data 30 is filtered to generate the third intermediate data 31.

[0100] The first filter 3100 can remove impulse noise. Impulse noise may not be a speckle to be corrected. The first filter 3100 can be an intermediate value filter. For example, the first filter 3100 can use a 3×3 mask to filter the first image data 10, the second image data 20, and the third image data 30. The size of the mask is presented as an example only, and the size of the mask is not limited to the example described above. In this disclosure, a k×k mask can mean a mask having a size corresponding to k pixels horizontally and k pixels vertically.

[0101] The arithmetic processor 3200 can remove noise. The noise may not be the speckle to be corrected. The arithmetic processor 3200 receives first intermediate data 11, second intermediate data 21, and third intermediate data 31. The arithmetic processor 3200, as... Figure 2 As shown in step S300, first response data 12 is generated by performing morphological operations on first intermediate data 11, second response data 22 is generated by performing morphological operations on second intermediate data 21, and third response data 32 is generated by performing morphological operations on third intermediate data 31.

[0102] Figure 8A This is a block diagram of an arithmetic processor 3200 according to an embodiment of the present disclosure.

[0103] refer to Figure 8A The processing unit 3200 may include a first maximum value filter 3210, a first minimum value filter 3220, a second minimum value filter 3230, a second maximum value filter 3240, an averager 3250, and a synthesizer 3260.

[0104] The first maximum value filter 3210 uses a first mask of size a×a to filter the first intermediate data 11, the second intermediate data 21, and multiple third intermediate data 31. For example, the first maximum value filter 3210 can generate first intermediate data 11-1 by maximizing the filtering of the first intermediate data 11 using the first mask, generate second intermediate data 21-1 by maximizing the filtering of the second intermediate data 21 using the first mask, and generate third intermediate data 31-1 by maximizing the filtering of the third intermediate data 31 using the first mask. The first intermediate data 11-1, the second intermediate data 21-1, and the third intermediate data 31-1 can be referred to as a set of data.

[0105] The first minimum value filter 3220 can filter the first intermediate data 11-1, the second intermediate data 21-1, and the third intermediate data 31-1 using a second mask with a size of (2a+1)×(2a+1). For example, the first minimum value filter 3220 can use the second mask to perform minimum filtering on the first intermediate data 11-1, the second intermediate data 21-1, and the third intermediate data 31-1 to produce the first intermediate data 11-2, the second intermediate data 21-2, and the third intermediate data 31-2. The first intermediate data 11-2, the second intermediate data 21-2, and the third intermediate data 31-2 can be referred to as a set of data.

[0106] The second minimum filter 3230 can use a first mask of size a×a to filter the first intermediate data 11, the second intermediate data 21, and the third intermediate data 31. For example, the second minimum filter 3230 can use the first mask to perform minimum filtering on the first intermediate data 11, the second intermediate data 21, and the third intermediate data 31 to produce first intermediate data 11-3, second intermediate data 21-3, and third intermediate data 31-3. The first intermediate data 11-3, the second intermediate data 21-3, and the third intermediate data 31-3 can be referred to as a set of data.

[0107] The second maximum value filter 3240 can filter the first intermediate data 11-3, the second intermediate data 21-3, and the third intermediate data 31-3 by using a second mask with a size of (2a+1)×(2a+1). For example, the second maximum value filter 3240 can use the second mask to maximize the filtering of the first intermediate data 11-3, the second intermediate data 21-3, and the third intermediate data 31-3 to produce the first intermediate data 11-4, the second intermediate data 21-4, and the third intermediate data 31-4. The first intermediate data 11-4, the second intermediate data 21-4, and the third intermediate data 31-4 can be referred to as a set of data.

[0108] The averager 3250 receives first intermediate data 11-2, second intermediate data 21-2, and third intermediate data 31-2 from the first minimum value filter 3220, and first intermediate data 11-4, second intermediate data 21-4, and third intermediate data 31-4 from the second maximum value filter 3240. The averager 3250 can generate first intermediate data 11-5 by averaging the first intermediate data 11-2 and the first intermediate data 11-4, generate second intermediate data 21-5 by averaging the second intermediate data 21-2 and the second intermediate data 21-4, and generate third intermediate data 31-5 by averaging the third intermediate data 31-2 and the third intermediate data 31-4.

[0109] Synthesizer 3260 receives first intermediate data 11, second intermediate data 21, and third intermediate data 31, as well as first intermediate data 11-5, second intermediate data 21-5, and third intermediate data 31-5 from averager 3250. Synthesizer 3260 removes first intermediate data 11-5 from first intermediate data 11 and generates first response data 12, removes second intermediate data 21-5 from second intermediate data 21 and generates second response data 22, and removes third intermediate data 31-5 from third intermediate data 31 and generates third response data 32.

[0110] Figure 8B This is a block diagram of an arithmetic processor 3201 according to an embodiment of the present disclosure.

[0111] refer to Figure 8B The arithmetic processor 3201 may include a second filter 3211, a third filter 3221, and a synthesizer 3231.

[0112] The second filter 3211 can filter the first intermediate data 11, the second intermediate data 21, and the third intermediate data 31 to generate the first intermediate data 11-a, the second intermediate data 21-a, and the third intermediate data 31-a. The third filter 3221 can filter the first intermediate data 11-a, the second intermediate data 21-a, and the third intermediate data 31-a to generate the first intermediate data 11-b, the second intermediate data 21-b, and the third intermediate data 31-b.

[0113] Synthesizer 3231 receives first intermediate data 11, second intermediate data 21, and third intermediate data 31, as well as first intermediate data 11-b, second intermediate data 21-b, and third intermediate data 31-b. Synthesizer 3231 removes first intermediate data 11-b, second intermediate data 21-b, and third intermediate data 31-b from first intermediate data 11, second intermediate data 21, and third intermediate data 31, respectively, to generate first response data 12, second response data 22, and third response data 32.

[0114] In one implementation, the second filter 3211 may be a reference. Figure 8A The first maximum value filter 3210 is described, and the third filter 3221 can be a reference. Figure 8A The first minimum value filter described is 3220.

[0115] In one implementation, the second filter 3211 may be a reference. Figure 8A The second minimum value filter 3230 is described, and the third filter 3221 may be a reference. Figure 8A The second maximum value filter 3240 is described.

[0116] Computing processor 3200 (see Figure 7 This can highlight spots that are candidates for correction and remove noise. Figure 9A It is the image corresponding to the first response data 12 from which noise has been removed. Figure 9B It is the image corresponding to the second response data 22 from which noise has been removed. Figure 9C It is the image corresponding to the third response data 32 from which noise has been removed.

[0117] Return to reference Figure 2 and Figure 7 The selector 3300 receives first response data 12, second response data 22, and third response data 32 from the processing unit 3200. The selector 3300, as... Figure 2 As shown in step S400, spot candidates of the first response data 12 are selected to generate the first candidate data 13, spot candidates of the second response data 22 are selected to generate the second candidate data 23, and spot candidates of the third response data 32 are selected to generate the third candidate data 33.

[0118] Selector 3300 can use an adaptive threshold to generate first candidate data 13, second candidate data 23, and third candidate data 33. For example, selector 3300 can select spot candidates that are darker or brighter than the average brightness value. For example, the values ​​selected as spot candidates may be outside the standard deviation range.

[0119] Figure 10A It is the image corresponding to the first candidate data 13. Figure 10B It is the image corresponding to the second candidate data 23. Figure 10C It is the image corresponding to the third candidate data 33.

[0120] The first candidate data 13 may include information related to the first spot group 10-M, the second candidate data 23 may include information related to the second spot group 20-M, and the third candidate data 33 may include information related to the third spot group 30-M.

[0121] The first spot group 10-M can be derived from the first image data 10 (see...). Figure 1B The detected spots are configured such that the first spot group 10-M may include a first spot 10-1, a second spot 10-2, and a third spot 10-3.

[0122] The first spot 10-1 could be display panel 1000 (see...) Figure 1A The first spot 10-2 can be a scratch formed on a film (e.g., a protective film) additionally attached to the display panel 1000. The second spot 10-3 can be a specific gray-level noise seen at the first gray level.

[0123] The second spot group 20-M can be derived from the second image data 20 (see...). Figure 1B The detected spots are configured as follows. The second spot group 20-M may include a first spot 20-1 and a second spot 20-2. The first spot 20-1 may be a display panel 1000 (see...). Figure 1A The second spot 20-2 may be a scratch formed on a film (e.g., a protective film) additionally attached to the display panel 1000.

[0124] The second spot group 20-M is a group of spots detected from data obtained by capturing an image at a second gray level that is different from the first gray level. Therefore, the second spot group 20-M may not include specific gray level noise seen at the first gray level, such as the third spot 10-3.

[0125] The third spot group 30-M can be derived from the third image data 30 (see...). Figure 1B The detected spots are configured as follows. The third spot group 30-M may include a first spot 30-1 and a second spot 30-2. The first spot 30-1 may be a display panel 1000 (see...). Figure 1A The second spot 30-2 can be a specific gray-level noise seen at the first gray level.

[0126] The third spot group 30-M is a group of spots detected from third image data 30 taken by a camera at a different location than the camera that acquired the first image data 10. Physical damage such as scratches may be visible or invisible depending on the camera's viewpoint or location. Therefore, the third spot group 30-M may not include scratches, for example, the second spot 10-2.

[0127] refer to Figure 2 and Figure 7Comparator 3400 receives first candidate data 13, second candidate data 23, and third candidate data 33. Comparator 3400 as follows: Figure 2 As shown in step S500, result data 40 is generated by comparing first candidate data 13, second candidate data 23 and third candidate data 33.

[0128] Figure 11 This is a flowchart of the operation of generating result data 40 according to the embodiments of this disclosure.

[0129] refer to Figure 2 , Figure 7 and Figure 11 The step of generating result data 40 (step S500) includes: generating first preliminary result data by removing values ​​that are not present in the second candidate data 23 from the first candidate data 13 (step S510); and generating result data 40 by removing values ​​that are not present in the third candidate data 33 from the first preliminary result data (step S520). Each of the values ​​that are not present in the second candidate data 23 and the values ​​that are not present in the third candidate data 33 may be single or non-existent.

[0130] Figure 12 This is the image corresponding to result data 40. Result data 40 may include information corresponding to common spots 40-M. Common spots 40-M may be the first spot group 10-M (see...). Figure 10A ), second spot group 20-M (see Figure 10B ) and the third spot group 30-M (see Figure 10C The spots included in the entirety of )

[0131] Return to reference Figure 2 and Figure 7 The quantization unit 3500 receives 40 result data. The quantization unit 3500, as shown... Figure 2 The spots of the resulting data 40 are quantified as shown in step S600.

[0132] Figure 13 This is a diagram illustrating an example of quantizing the resulting data 40.

[0133] refer to Figure 13 Quantization unit 3500 (see Figure 7 The severity of the spots can be scored. Figure 50 shows a response to scoring the intensity of a common spot 40-M as an example.

[0134] The reaction diagram 50 may include data scored in block units. A block 1000-B may include 8×8 pixels. However, the units constituting a block 1000-B are not limited to the examples described above.

[0135] According to embodiments of this disclosure, target spots for correction can be selected from the blocks with the highest scores. For example, when a total of three blocks are selected as spot correction targets, three blocks with scores of 900, 800, and 700 can be selected as spot correction targets to obtain the highest score.

[0136] Figure 14 It is a display device according to an embodiment of the present disclosure.

[0137] refer to Figure 14 The display device DD may include a display panel 1000, a first connecting film 1100, a first printed circuit board 1200, a memory 1300, a second connecting film 1400, a second printed circuit board 1500, and a timing controller 1600.

[0138] The first connecting film 1100 can be electrically connected to the display panel 1000. Each of the first connecting films 1100 can be a carrier encapsulation film or a chip-on-film.

[0139] The first printed circuit board 1200 can be electrically connected to the display panel 1000 via the first connecting film 1100. A memory 1300 can be mounted on the first printed circuit board 1200. Information related to the spot selected as the correction target can be stored in the memory 1300.

[0140] The second connecting membrane 1400 can electrically connect the first printed circuit board 1200 and the second printed circuit board 1500. The timing controller 1600 can be mounted on the second printed circuit board 1500.

[0141] The timing controller 1600 can receive speckle information from the memory 1300 and then correct the image data received from the outside. Therefore, the display quality of the display device DD can be improved.

[0142] According to this disclosure, spots can be detected using image data obtained from two images with different gray levels and image data obtained from different viewing angles of the display panel. Therefore, scratches that are not spots and noise occurring only at specific gray levels can be prevented from being identified as spots. Thus, a spot detection apparatus and method with improved reliability can be provided. Furthermore, since a display device is provided that has information related to the spots detected using this spot detection apparatus and method, the displayed image quality of the display device can be improved.

[0143] Although exemplary embodiments of the inventive concept have been described, it should be understood that the inventive concept is not limited to these exemplary embodiments, but that various changes and modifications can be made by those skilled in the art within the spirit and scope of the appended claims disclosure.

Claims

1. A spot detection device, comprising: An imager is configured to capture images of a display panel displaying a first image at a first gray level and a second image at a second gray level different from the first gray level, and to generate multiple image data. as well as A speckle detector is configured to receive the plurality of image data from the imager to detect specks. The plurality of image data includes first image data obtained by capturing the entire first image from a first position, second image data obtained by capturing the entire second image from the first position, and a plurality of third image data obtained by capturing portions of the first image from a second position different from the first position. The speckle detector is configured to detect common speckles included in a first group of speckles detected in the first image data, a second group of speckles detected in the second image data, and a third group of speckles detected in the plurality of third image data. The common spots include spots in the first spot group, the second spot group, and the third spot group, excluding specific gray-level noise and scratches seen at the first gray level.

2. The spot detection device according to claim 1, wherein, The imager includes a first camera for capturing the entire display area of ​​the display panel and a second camera for capturing a portion of the display area.

3. The spot detection device according to claim 2, wherein, The imager also includes a third camera for capturing another portion of the display area.

4. The spot detection device according to claim 2, wherein, The second camera captures a portion of the display area from the second position and another portion of the display area from a third position different from the second position.

5. The spot detection device according to claim 1, wherein, The imager includes a camera. The camera obtains the first image data and the second image data from the first position, and obtains at least some of the plurality of third image data from the second position, which is different from the first position.

6. The spot detection device according to claim 1, wherein, The speckle detector includes a first filter for removing impulse noise from the first image data, the second image data, and the plurality of third image data. The first filter converts the first image data, the second image data, and the plurality of third image data into first intermediate data, second intermediate data, and plurality of third intermediate data respectively through an intermediate value filter.

7. The spot detection device according to claim 6, wherein, The speckle detector further includes a computational processor for removing noise from the first intermediate data, the second intermediate data, and the plurality of third intermediate data. The processing unit converts the first intermediate data, the second intermediate data, and the plurality of third intermediate data into first response data, second response data, and plurality of third response data respectively through morphological operations.

8. The spot detection device according to claim 7, wherein, The processing unit includes: The first maximum value filter is configured to filter the first intermediate data, the second intermediate data, and the plurality of third intermediate data using a mask of size a×a; The first minimum value filter is configured to filter a set of data filtered by the first maximum value filter using a mask of size (2a+1)×(2a+1); The second minimum value filter is configured to filter the first intermediate data, the second intermediate data, and the plurality of third intermediate data using a mask of size a×a; The second maximum value filter is configured to filter a set of data filtered by the second minimum value filter using a mask of size (2a+1)×(2a+1); An averager, configured to average the data filtered by the first minimum value filter and the corresponding data filtered by the second maximum value filter; and The synthesizer is configured to generate the first response data, the second response data, and the plurality of third response data by removing corresponding average data derived from the averager from the first intermediate data, the second intermediate data, and the plurality of third intermediate data, respectively.

9. The spot detection device according to claim 7, wherein, The processing unit includes: The second filter is configured to filter the first intermediate data, the second intermediate data, and the plurality of third intermediate data using a mask of size a×a; A third filter is configured to filter a set of data filtered by the second filter using a mask of size (2a+1) × (2a+1); and The synthesizer is configured to generate the first response data, the second response data, and the plurality of third response data by removing corresponding data filtered by the third filter from the first intermediate data, the second intermediate data, and the plurality of third intermediate data, respectively.

10. The spot detection device according to claim 7, wherein, The speckle detector further includes a selector configured to select speckle candidates from the first response data, the second response data, and the plurality of third response data. The selector converts the first response data, the second response data, and the plurality of third response data into first candidate data, second candidate data, and a plurality of third candidate data, respectively.

11. The spot detection device according to claim 10, wherein, The speckle detector further includes a comparator and a quantization unit. The comparator is configured to generate result data by comparing the first candidate data, the second candidate data, and the plurality of third candidate data. The quantization unit is configured to quantize the speckles in the result data.

12. A display device, comprising: Display panel; A first printed circuit board is electrically connected to the display panel; as well as The memory is mounted on the first printed circuit board. The memory stores speckle information detected based on first image data, second image data, and multiple third image data. The first image data is obtained by capturing an entire first image of a first grayscale level displayed on the display panel from a first position. The second image data is obtained by capturing an entire second image of a second grayscale level, different from the first grayscale level, displayed on the display panel from the first position. The multiple third image data are each obtained by capturing a portion of the first image from a second position, different from the first position. Wherein, the blob information is information relating to common blobs included in all of the first blob group detected in the first image data, the second blob group detected in the second image data, and the third blob group detected in the plurality of third image data, and The common spots include spots in the first spot group, the second spot group, and the third spot group, excluding specific gray-level noise and scratches seen at the first gray level.

13. Spot detection methods, including: A first image of the first grayscale level is captured from a first position and displayed on a display panel to generate first image data; A second image of a second gray level, different from the first gray level, is captured from the first position and displayed on the display panel to generate second image data. A portion of the first image is captured from a second position different from the first position to generate multiple third image data; as well as Spots are detected using the first image data, the second image data, and the plurality of third image data. The step of detecting the spots includes detecting common spots included in a first group of spots detected in the first image data, a second group of spots detected in the second image data, and a third group of spots detected in the plurality of third image data. The common spots include spots in the first spot group, the second spot group, and the third spot group, excluding specific gray-level noise and scratches seen at the first gray level.

14. The method according to claim 13, wherein, The first image data and the plurality of third image data were obtained by cameras positioned at different locations.

15. The method according to claim 13, wherein, The step of detecting the spots includes: filtering the first image data, the second image data, and the plurality of third image data through an intermediate value filter to generate first intermediate data, second intermediate data, and a plurality of third intermediate data.

16. The method according to claim 15, wherein, The step of detecting the spots further includes: morphologically processing the first intermediate data, the second intermediate data, and the plurality of third intermediate data to generate first response data, second response data, and a plurality of third response data.

17. The method according to claim 16, wherein, The step of detecting the spots further includes: selecting spot candidates from the first response data, the second response data, and the plurality of third response data to generate first candidate data, second candidate data, and a plurality of third candidate data.

18. The method according to claim 17, wherein, The step of detecting the spots further includes: generating result data by comparing the first candidate data, the second candidate data, and the plurality of third candidate data; and quantifying the spots in the result data.

19. The method according to claim 18, wherein, The steps for generating the result data include: First preliminary result data is generated by removing values ​​that are not present in the second candidate data from the first candidate data; and The result data is generated by removing values ​​that are not present in the plurality of third candidate data from the first preliminary result data.

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