Pixel defect detection apparatus having concave light source and diffuser structure, and method and system for determining pixel defects by adjusting luminance deviation

Abstract

The present invention relates to an apparatus for determining pixel defects of an image sensor with respect to a camera that includes the image sensor and outputs image data on the basis of a signal output from the image sensor, the apparatus comprising: a reception unit for receiving the image data output from the camera; and a processor for processing the image data transmitted to the reception unit, wherein the processor divides the image data into at least one region on the basis of the luminance distribution of the image data and extracts a defective pixel on the basis of a criterion for each divided region.

Description

Pixel defect detection device having a concave light source and diffuser structure, method for determining pixel defects by adjusting brightness deviation, and system

[0001] The present invention relates to a quality evaluation technology for an image sensor. Specifically, it relates to a technology for detecting pixel defects in an image sensor.

[0002] In addition, the present invention relates to a pixel defect detection device having a concave light source and a diffuser structure that provides uniform illumination over the entire field of view of an image sensor.

[0003] When conventional image sensors are placed under a uniform light source, the difference in light intensity between the center and periphery of the image results in an uneven brightness distribution, which distorts defect detection criteria. Furthermore, static criteria, such as the overall brightness average or a predetermined threshold, do not account for light intensity deviations; consequently, errors occur where normal pixels are misidentified or defects are missed. Additionally, static criteria lack adaptability to changes in the image sensor's test environment. Moreover, for image sensors with a wide field of view, it is difficult to provide uniform illumination across the entire angle of view. Finally, it is difficult to distinguish whether pixels detected as defective are due to image brightness deviations or actual pixel defects.

[0004] In addition, image sensors such as CMOS and CCD are devices that convert external light into electrical signals and output them as digital images, and each pixel of the image sensor performs the functions of receiving light and generating electrical signals. Some pixels of the image sensor may have defects that prevent them from providing normal output values ​​due to microscopic defects in the manufacturing process or damage caused by the external environment.

[0005] Conventionally, when a uniform light source is shone onto an image sensor, the center of the sensor experiences relatively high illumination while the periphery experiences low illumination, resulting in brightness inconsistencies and making it difficult to provide uniform illumination across the entire field of view of the image sensor. Additionally, when a uniform light source is shone onto an image sensor with a wide angle, there is a problem in that the illumination coverage of the image sensor is insufficient.

[0006] The present invention aims to solve the problem in which defect judgment criteria are distorted due to uneven brightness distribution caused by the difference in light intensity between the center and periphery of an image.

[0007] In addition, it aims to resolve the problem of errors occurring where normal pixels are misdetected or defects are missed.

[0008] In addition, it aims to solve the problem of the image sensor's lack of adaptability to changes in the test environment.

[0009] In addition, it aims to solve the problem of difficulty in providing uniform illumination across the entire field of view.

[0010] In addition, it aims to solve the problem of difficulty in distinguishing whether pixels detected as defective are caused by image brightness deviations or actual pixel defects.

[0011] The present invention aims to solve the phenomenon in which some pixels of an image sensor fail to provide normal output values ​​due to defects such as micro-defects during the manufacturing process or damage caused by the external environment.

[0012] The present invention can provide uniform illumination over the entire field of view of an image sensor.

[0013] The present invention aims to solve the problem of insufficient lighting coverage.

[0014] The present invention relates to an apparatus for determining pixel defects of an image sensor for a camera that includes an image sensor and outputs image data based on a signal output from the image sensor, the apparatus comprising: a receiver for receiving image data output from the camera; and a processor for processing image data applied to the receiver; wherein the processor is configured to divide the image data into at least one region based on the brightness distribution of the image data, and is configured to extract defective pixels based on a criterion for each divided region.

[0015] Additionally, the processor is configured to divide the regions such that each of the at least one region has a similar brightness deviation between pixels included within the region, and is configured to extract pixels presumed to be defective among the pixels included within the divided regions based on the brightness deviation of the pixels relative to a standard for each divided region.

[0016] Additionally, the processor is configured to classify the type of pixel defect from the extracted defect pixel, and the type of pixel defect is at least one of a cold pixel, a hot pixel, a dead pixel, or a noise pixel.

[0017] Additionally, the processor is configured to generate a report containing information about the extracted defect pixels.

[0018] In addition, the processor is configured to set the operating conditions of the image sensor as a default condition.

[0019] In addition, the processor is configured to extract defective pixels based on criteria for each of the segmented regions by utilizing at least one algorithm among K-Means Clustering, Adaptive Thresholding, Region Growing, Gaussian Mixture Models (GMM), Edge Detection, and Histogram-Based Segmentation algorithms.

[0020] In addition, the processor is configured to generate a report in at least one of a table format, a map image format, and a CSV format.

[0021] The present invention relates to a method for determining a pixel defect of an image sensor in a camera that includes an image sensor and outputs image data based on a signal output from the image sensor, wherein the method comprises: a receiving step in which a receiving unit of the pixel defect determination device receives image data output from the camera; and a processing step in which a processor of the pixel defect determination device processes the image data received from the receiving unit; wherein the processing step comprises: a division step in which the processor divides the image data into at least one region based on the brightness distribution of the image data; and an extraction step in which the processor extracts a defective pixel based on a criterion for each divided region.

[0022] Additionally, the above-mentioned segmentation step further comprises a step in which the processor segments the regions such that each of the at least one region has a similar brightness deviation between pixels included within the region; and the above-mentioned extraction step further comprises a step in which the processor extracts pixels presumed to be defective among the pixels included within the segmented regions, based on the brightness deviation of the pixels relative to a standard for each segmented region.

[0023] Additionally, the method further includes a classification step in which the processor classifies the type of pixel defect from the extracted defect pixels; wherein the classification step further includes a step in which the processor classifies the pixel defect into at least one of a cold pixel, a hot pixel, a dead pixel, and a noise pixel.

[0024] The present invention relates to a lighting device for use in determining pixel defects of an image sensor in a camera that includes an image sensor and outputs image data based on a signal output from the image sensor, the device comprising: a light source for emitting light; wherein the light source is configured such that the light emitted from the light source is uniformly irradiated over the entire imaging area of ​​the camera, and is configured to have a concave shape so that the emitted light can be uniformly irradiated over the entire imaging area of ​​the camera.

[0025] Additionally, it further includes a diffuser layer; said diffuser layer is configured to be positioned along the curved surface of the light source having the concave shape.

[0026] In addition, the diffuser layer is configured to reduce deviations in light irradiation direction and intensity according to the curvature of the light source having the concave shape.

[0027] In addition, the diffuser layer is formed to have a material that scatters and diffuses light generated from the light source.

[0028] Additionally, the camera includes an optical system; and the optical system includes a lens that refracts external light received by the camera to converge to a center.

[0029] In addition, the light source is configured to have a curvature corresponding to the curvature of the optical system, and the center of the curvature of the light source is formed to coincide with the center of curvature of the optical system or to have a distance of less than or equal to a critical point from the center of curvature of the optical system.

[0030] According to one embodiment of the present invention, the problem of distortion in defect judgment criteria due to uneven brightness distribution caused by a difference in light intensity between the center and periphery of an image can be resolved.

[0031] In addition, it can resolve issues where errors occur, such as misdetecting normal pixels or missing defects.

[0032] In addition, it can solve the problem of the image sensor's lack of adaptability to changes in the test environment.

[0033] In addition, it can solve the problem of difficulty in providing uniform illumination across the entire field of view.

[0034] In addition, it can solve the problem of difficulty in distinguishing whether pixels detected as defective are due to image brightness deviations or actual pixel defects.

[0035] The present invention can provide uniform illumination over the entire field of view of an image sensor.

[0036] The present invention can solve the problem of insufficient lighting coverage.

[0037] FIG. 1a is a diagram illustrating the configuration of a system for inspecting pixel defects of an image sensor according to one embodiment of the present invention.

[0038] FIG. 1b is a diagram illustrating image data output from a pixel defect inspection target device according to one embodiment of the present invention.

[0039] FIG. 2a is a drawing for explaining pixel defects according to an embodiment of the present invention.

[0040] FIG. 2b is a conceptual diagram for explaining the shadow phenomenon of image data according to one embodiment of the present invention.

[0041] FIG. 3 is a drawing for explaining a lighting device according to an embodiment of the present invention.

[0042] FIG. 4 is a diagram illustrating the step of inspecting pixel defects of an image sensor according to one embodiment of the present invention.

[0043] FIG. 5 is a diagram illustrating a pixel defect evaluation area separated from image data having a shading phenomenon according to an embodiment of the present invention.

[0044] FIG. 6 is a diagram illustrating a defective pixel information report, which is the result of a pixel defect inspection device according to one embodiment of the present invention.

[0045] Specific details of the embodiments are included in the detailed description and drawings. The advantages and features of the present invention and the methods for achieving them will become clear by referring to the embodiments described below in detail together with the accompanying drawings. However, the present invention is not limited to the embodiments disclosed below but may be implemented in various different forms. These embodiments are provided merely to ensure that the disclosure of the present invention is complete and to fully inform those skilled in the art of the scope of the invention, and the present invention is defined only by the scope of the claims. Throughout the specification, the same reference numerals refer to the same components.

[0046] FIG. 1a is a diagram illustrating the configuration of a system for inspecting pixel defects of an image sensor according to an embodiment of the present invention. FIG. 1b is a diagram illustrating image data output from a pixel defect inspection target device according to an embodiment of the present invention.

[0047] Referring to FIG. 1a, a system (10) for inspecting pixel defects of an image sensor may include a pixel defect inspection target device (100), a lighting device (200), and a pixel defect inspection device (300). Additionally, the pixel defect inspection target device (100) may include an image sensor (110) and an optical system (120).

[0048] According to one embodiment of the present invention, a pixel defect inspection device (300) may include a receiving unit (310), a processor (320), and a storage unit (330). Specifically, the receiving unit (310) may receive data output from a pixel defect inspection target device (100). Specifically, the data output from the pixel defect inspection target device (100) may include image data or brightness code data of the image data.

[0049] According to one embodiment of the present invention, the processor (320) can determine whether there is a defect in at least one pixel included in the image sensor (110) based on data output from the pixel defect inspection target device (100). A specific method for determining whether there is a pixel defect is described in detail below in the description of the step (S10) of inspecting pixel defects in the image sensor.

[0050] According to one embodiment of the present invention, the storage unit (330) may store data authorized by the receiving unit (310) or result data regarding whether there is a pixel defect determined by the processor (320).

[0051] According to one embodiment of the present invention, the pixel defect inspection target device (100) may be a device that is inspected in a system (10) for inspecting pixel defects. In this case, the pixel defect inspection target device (100) may be a device that performs the function of receiving external light and converting it into an electrical signal. For example, the pixel defect inspection target device (100) may be a camera.

[0052] Referring to FIG. 1b, an image sensor (110) according to one embodiment of the present invention may receive external light (1b-1). Additionally, the image sensor (110) may include a red filter (1b-2R), a green filter (1b-2G), a blue filter (1b-2B), and a pixel array (1b-3). Additionally, a pixel defect inspection target device (100) may output image data (1b-4R, 1b-4G, 1b-4B) based on the magnitude of the signal output from the pixel array (1b-3). A system (10) for inspecting pixel defects may analyze the image data (1b-4R, 1b-4G, 1b-4B) to extract and classify pixels having defects in the pixel array (1b-3).

[0053] FIG. 2a is a drawing for explaining pixel defects according to an embodiment of the present invention.

[0054] According to the present invention, a pixel defect means that a specific pixel within an image sensor (110) does not have normal light response characteristics. Specifically, a pixel defect means that the output stability of a specific pixel decreases over time under constant light source conditions, or that the output value of a specific pixel signal deviates from an absolute brightness standard or a relative brightness standard. Specifically, the absolute brightness standard may refer to a predefined brightness threshold. Additionally, the relative brightness standard may refer to the average brightness or median value of adjacent pixels.

[0055] According to one embodiment of the present invention, based on a relative brightness standard, a pixel with a pixel defect may exhibit a statistically significant brightness deviation compared to an adjacent pixel. Pixels exhibiting a statistically significant brightness deviation may include cold pixels, hot pixels, dead pixels, or noise pixels. In this case, a cold pixel may refer to a pixel whose output signal is abnormally low even when a light source is present. Additionally, a hot pixel may refer to a pixel whose output signal is abnormally high even when a light source is absent.

[0056] Referring to FIG. 1b and FIG. 2a, the image data (2a-B) may be image data in which only the parts presumed to have pixel defects are displayed among the image data (1b-4B) output by the pixel defect inspection target device (100) based on the signal output by the pixel array (1b-3), after external light (1b-1) passes through a blue filter (1b-2B) and is received by the pixel array (1b-3). In this case, the first marking (2a-1, 2a-2) indicates a part of the image data (2a-B) where the brightness value is abnormally high. Also, the second marking (2a-3) indicates a part where the brightness value is abnormally low. The first marking (2a-1, 2a-2) is a marking painted in black, and the second marking (2a-3) is a marking painted in a diagonal pattern. Here, the method for determining whether the brightness value is abnormally high or low is explained in detail in the step (S10) of inspecting pixel defects of the image sensor.

[0057] FIG. 2b is a conceptual diagram for explaining the shadow phenomenon of image data according to one embodiment of the present invention.

[0058] According to one embodiment of the present invention, the shading phenomenon refers to a phenomenon in which, in image data output by a pixel defect inspection target device (100), the area located in the center is brighter and the area located in the periphery is darker. The shading phenomenon of image data according to one embodiment of the present invention is described below.

[0059] Referring to FIG. 2b, a set of grid blocks (2b-1) arranged in a grid format and dots (2b-4, dots) conceptually represent the pixel array (1b-3) of the image sensor (110) and the amount of external light (1b-1) irradiated to each pixel. For example, a grid block (2b-2) in the center represents a pixel with a large amount of irradiated light because it has a small number of dots marked on the grid block. Additionally, a grid block (2b-3) in the periphery represents a pixel with a small amount of irradiated light because it has a large number of dots marked on the grid block.

[0060] According to one embodiment of the present invention, the optical system (120) may include a lens that refracts the received external light (1b-1) to converge toward the center. Additionally, the image sensor (110) may receive light that has passed through the optical system (120). Accordingly, the center of the pixel array (1b-3) may receive a large amount of light, while the periphery may receive a small amount of light. Accordingly, the signal of a pixel located at the center of the pixel array (1b-3) of the image sensor (110) may have a high output value, and the signal of a pixel located at the periphery of the pixel array (1b-3) of the image sensor (110) may have a low output value. Therefore, in the image data output from the pixel defect target device (100), a shadow phenomenon may occur in which the brightness distribution shows a decrease in brightness in the periphery compared to the center.

[0061] According to one embodiment of the present invention, a shadow phenomenon can distort the criteria for determining pixel defects. Specifically, a low output signal of a pixel classified as a cold pixel may be caused by a low amount of light entering the pixel, rather than a defect in the pixel itself.

[0062] FIG. 3 is a drawing for explaining a lighting device according to an embodiment of the present invention. FIG. 3(a) is a drawing for explaining the configuration of a lighting device of the prior art. FIG. 3(b) is a drawing for explaining the configuration of another lighting device according to an embodiment of the present invention.

[0063] As illustrated in FIG. 3(a), a conventional lighting device (3-1) includes a planar light source. At this time, the conventional lighting device (3-1) can irradiate uniform light for a viewing angle of 30 degrees (deg) or less of a mobile camera (3-4).

[0064] According to one embodiment of the present invention, the lighting device (200) may be a device that irradiates light to reduce the aforementioned shadow phenomenon based on the conditions of the optical system (120). Specifically, the lighting device (200) may include a concave light source (210) and a diffuser layer (220).

[0065] As illustrated in FIG. 3(b), the concave light source (210) can change the direction of light irradiated by the lighting device (200) based on the curvature of the optical system (120). Specifically, the concave shape of the concave light source (210) may be a shape that is convex inward when viewed in the direction (3-2) in which the lighting device (200) irradiates light toward the image sensor (110). In this case, since the concave light source (210) has a predetermined curvature, it can irradiate light uniformly across the entire pixel array (1b-3) within the image sensor (110).

[0066] For example, the center of curvature of the concave light source (210) may coincide with the center of curvature (O) of the optical system (120) or have a distance below a critical threshold from the center of curvature (O) of the optical system (120). Accordingly, the concave light source (210) can uniformly irradiate light not only to the center of the pixel array (1b-3) within the image sensor (110) but also to the periphery. For a mobile camera (3-4) having a viewing angle of about 120 degrees (120 deg), the center of curvature of the light source of the concave light source (210) can be set to about 120 degrees so that uniform light is irradiated across the entire pixel array (1b-3) within the mobile camera (3-4). Therefore, the lighting device (200) of the present invention can solve the problem of shadowing occurring when using a conventional planar light source.

[0067] According to one embodiment of the present invention, the diffuser layer (220) may be a material or structure that scatters and diffuses (2b-2) light generated from a light source of a lighting device (200). Specifically, the diffuser layer (220) is positioned along the curved surface of a concave light source (210) to reduce deviations in the direction and intensity of light irradiation according to the curvature of the concave light source (210). Additionally, the diffuser layer (220) may be composed of a translucent material to correct deviations in light distribution caused by the curvature of the concave light source (210). Furthermore, the diffuser layer (220) may be attached to the outside of the concave light source (210). Additionally, the diffuser layer (220) may have a uniform thickness to correct deviations in light distribution.

[0068] FIG. 4 is a diagram illustrating the step of inspecting pixel defects of an image sensor according to one embodiment of the present invention.

[0069] Referring to FIG. 4, the step of inspecting pixel defects of an image sensor (S10) may include: a step of setting basic operating conditions of the image sensor (S100); a step of setting lighting conditions of a lighting device based on the type of pixel defect of the image sensor (S110); a step of acquiring image data based on a signal output from the image sensor through a receiver (S120); a step of distinguishing an evaluation area of ​​pixel defects in the acquired image data through a processor (S130); a step of extracting the location of defective pixels of the image sensor and classifying the type of pixel defect based on the acquired image data and the distinguished evaluation area through a processor (S140); a step of creating a pixel defect inspection result report through a processor (S150); and a step of storing the created report in a storage unit (S160).

[0070] According to one embodiment of the present invention, the step of inspecting pixel defects of an image sensor (S10) and the step of setting basic operating conditions of the image sensor (S100) may be the step of setting the operating conditions of the pixel defect inspection target device (100) as basic conditions. Specifically, the operating conditions of the pixel defect inspection target device (100) may include the auto exposure (AE), gain, resolution, or frame conditions of the image sensor and may be set as specific conditions. For example, the pixel defect inspection target device (100) may adjust the auto exposure or gain so that the brightness code of the image data (1b-4) is 100 or higher and 150 or lower within the range of at least 0 or higher and at most 255 or lower. Additionally, the step of setting basic operating conditions of the image sensor (S100) may be omitted.

[0071] According to one embodiment of the present invention, the step (S110) of setting lighting conditions of a lighting device based on the type of pixel defect of an image sensor may be a step of setting conditions of a lighting device (200) based on the type of pixel defect to be evaluated in a pixel defect inspection target device (100).

[0072] According to one embodiment of the present invention, when the type of pixel defect to be evaluated is a cold pixel, the lighting device (200) may include a light source that ensures uniformity of illumination. For example, if the pixel defect inspection target device (100) does not include an optical system (120), the lighting device (200) may include a planar LED light source or a light guide plate that is a light source that ensures uniformity of illumination. Additionally, if the pixel defect inspection target device (100) includes an optical system (120), the lighting device (200) may be a concave light source (210) that is a light source that ensures uniformity of illumination and may include a diffuser layer (220).

[0073] According to one embodiment of the present invention, when the type of pixel defect to be evaluated is a hot pixel, the lighting device (200) can be set to a no-illumination condition close to a dark room condition.

[0074] According to one embodiment of the present invention, the step (S120) of acquiring image data based on a signal output from an image sensor through a receiver may be a step of applying image data (1b-4) generated by a pixel defect inspection target device (100) based on a signal output from an image sensor (110) to a pixel defect inspection device (300). Specifically, the receiver (310) may receive image data (1b-4) from the pixel defect inspection target device (100).

[0075] According to one embodiment of the present invention, the step (S130) of distinguishing an evaluation area of ​​pixel defects in image data acquired through a processor may be a step of distinguishing an evaluation area of ​​pixel defects in image data (1b-4) acquired in the step (S120) in which the processor (320) acquires image data based on a signal output from an image sensor through a receiver. In this case, the pixel defect evaluation area may mean at least one area of ​​image data (1b-4) distinguished according to optical or statistical criteria to evaluate defects of pixels of the image sensor (110).

[0076] According to one embodiment of the present invention, the processor (320) may divide the image data (1b-4) into at least one evaluation area to minimize brightness deviation within each evaluation area by considering the shadow phenomenon of the image data (1b-4). Specifically, the magnitude of the signal output from each pixel of the pixel array (1b-3) may differ from pixel to pixel. The image data (1b-4) may be data that visualizes brightness code data generated based on the signal output from each pixel of the pixel array (1b-3).

[0077] Accordingly, the image data (1b-4) may include brightness code data corresponding to each pixel of the pixel array (1b-3) and data regarding the distribution of brightness values ​​per pixel. At this time, the processor (320) may set at least one initial evaluation area from the distribution of brightness values ​​per pixel of the image data (1b-4) and calculate statistical quantities such as the average value, median value, or standard deviation of brightness values ​​for each initial evaluation area. Subsequently, the processor (320) may calculate the difference between the brightness value of a pixel within the initial evaluation area and the statistical quantity of the area, and reorganize the set of pixels so that this difference is less than or equal to a predetermined standard. Accordingly, the processor (320) may divide the image data (1b-4) into one or more evaluation areas containing only pixels with similar brightness deviations.

[0078] FIG. 5 is a diagram illustrating a pixel defect evaluation area separated from image data having a shading phenomenon according to an embodiment of the present invention.

[0079] As illustrated in FIG. 5, the processor (320) can divide the evaluation area of ​​the image data into a peripheral area (Zone 1) with the least amount of light, a middle area (Zone 2), and a central area (Zone 3) with the most amount of light. Additionally, the area division of the processor (320) can be dynamically implemented based on a brightness curve or an algorithm. However, the processor (320) of the present invention is not limited to using an algorithm and may include, for example, using artificial intelligence.

[0080] According to one embodiment of the present invention, the evaluation area distinguished by the processor (320) can be dynamically adjusted. Specifically, the processor (320) may utilize K-Means Clustering, Adaptive Thresholding, Region Growing, Gaussian Mixture Models (GMM), Edge Detection, or Histogram-Based Segmentation algorithms to distinguish the evaluation area of ​​image data. Specifically, when the processor (320) utilizes the K-Means Clustering algorithm, the processor (320) calculates the deviation between the brightness value of each grid block and each center value based on K center values, and assigns each grid block to the cluster with the smallest deviation, thereby distinguishing multiple regions composed of grid blocks with similar brightness distributions.

[0081] According to one embodiment of the present invention, when the processor (320) utilizes an Adaptive Thresholding algorithm, the processor (320) can distinguish evaluation areas in image data by applying different brightness threshold values ​​to each grid block within the area based on brightness statistics in a local area within the image data.

[0082] According to one embodiment of the present invention, when a processor (320) utilizes a Region Growing algorithm, the processor (320) evaluates the brightness similarity of adjacent grid blocks from an initial seed, which is a grid block set by a user, and gradually expands the region to distinguish continuous evaluation regions in image data.

[0083] According to one embodiment of the present invention, when the processor (320) utilizes a Gaussian Mixture Models (GMM) algorithm, the processor (320) models the brightness distribution of image data as a plurality of Gaussian distributions, thereby enabling the distinction of evaluation regions even in image data where brightness patterns are superimposed.

[0084] According to one embodiment of the present invention, when the processor (320) utilizes an edge detection algorithm, the processor (320) can detect boundaries where a rapid change in brightness occurs within the image data and distinguish evaluation areas of image data with strong shadow phenomena.

[0085] According to one embodiment of the present invention, when a processor (320) utilizes a Histogram-Based Segmentation algorithm, the processor (320) can analyze a histogram of pixel brightness values ​​of image data and automatically set a threshold value according to each distribution range to distinguish evaluation areas of image data.

[0086] According to one embodiment of the present invention, the processor (320) may utilize K-Means Clustering, Adaptive Thresholding, Region Growing, Gaussian Mixture Models (GMM), Edge Detection, or Histogram-Based Segmentation algorithms alone or in combination, and may dynamically distinguish evaluation areas based on the characteristics of the optical system (120) and the conditions (200) of the lighting device.

[0087] According to one embodiment of the present invention, the step (S140) of extracting the location of a defective pixel of an image sensor and classifying the type of pixel defect based on image data acquired through a processor and a separated evaluation area may be a step in which the processor (320) extracts the location of a pixel presumed to have a defect among the pixels of the image sensor (110) and classifies the type of pixel defect based on the evaluation area separated in the step (S130) of separating the evaluation area of ​​a pixel defect in image data acquired through a processor. Specifically, the processor (320) may extract the location of a pixel presumed to have a defect and classify the type of pixel defect based on Block-based software, Mask-based software, K-Means Clustering, Adaptive Thresholding, Region Growing, Gaussian Mixture Models (GMM), Edge Detection, or Histogram-Based Segmentation algorithm, or artificial intelligence.

[0088] Accordingly, the processor (320) can dynamically adjust the criteria for extraction and classification based on an algorithm or artificial intelligence. For example, the processor (320) can classify a grid block with an abnormally low brightness value of an adjacent grid block as a grid block corresponding to a cold pixel based on an Adaptive Thresholding algorithm. Additionally, the processor (320) can classify a grid block with a high brightness value relative to an adjacent grid block under dark room conditions as a grid block corresponding to a hot pixel. Additionally, a grid block with an irregular brightness value over time can be classified as a grid block corresponding to a noise pixel.

[0089] According to one embodiment of the present invention, the step (S150) of creating a pixel defect inspection result report through a processor may be a step of creating a report for grid blocks extracted and classified in the step (S140) in which the processor (320) extracts the location of defective pixels of an image sensor and classifies the type of pixel defect based on the acquired image data and a separated evaluation area through the processor.

[0090] According to one embodiment of the present invention, the processor (320) may generate information about pixels presumed to be defective in the form of a report. Additionally, the report may include information such as the division criteria of the defect evaluation area, the location and type of the defective pixel, or brightness deviation. Additionally, the report may be generated in a structured format such as a table, a map image, or a CSV.

[0091] FIG. 6 is a diagram illustrating a defective pixel information report, which is the result of a pixel defect inspection device according to an embodiment of the present invention. FIG. 6(a) is a diagram illustrating the contents of the defective pixel information report written in a table format. FIG. 6(b) is a diagram illustrating the contents of the defective pixel information report written in a map image format.

[0092] Referring to FIG. 6(a), the processor (320) can create a table of information regarding pixels presumed to be defective. In this case, the processor (320) can organize and create a table of information regarding an evaluation area classification method (6a-1), a defective pixel classification method (6a-2), a grid block or pixel location (6a-3), a type of pixel defect (6a-4), or a brightness deviation of a grid block based on a defective pixel classification criterion (6a-5).

[0093] Referring to FIG. 6(b), the processor (320) can create information about pixels presumed to be defective in the form of a map image. In this case, the processor (320) can display grid blocks or grid blocks corresponding to pixel locations (6a-3) and pixel defect types (6a-4) in the map image. Specifically, the first grid block (6b-1) displayed in the map image may include information that the pixel location (6a-3) is (2,7) and the pixel defect type (6a-4) is presumed to be a hot pixel. The second grid block (6b-2) displayed in the map image may include information that the pixel location (6a-3) is (6,5) and the pixel defect type (6a-4) is presumed to be a hot pixel. The third grid block (6b-3) displayed in the map image may include information that the pixel location (6a-3) is (6,3) and the pixel defect type (6a-4) is presumed to be a cold pixel.

[0094] According to one embodiment of the present invention, the step of storing the written report in the storage unit (S160) may be a step of storing the report written by the processor (320) in the step of writing the pixel defect inspection result report (S150) in the storage unit (330) through the processor.

[0095] The scope of the present invention is not limited to the embodiments described above but may be implemented in various forms of embodiments within the scope of the appended claims. It is deemed that the scope of the claims of the present invention includes various modifications that are possible by anyone with ordinary knowledge in the technical field to which the invention pertains, without departing from the essence of the invention claimed in the claims.

Claims

1. An apparatus for determining pixel defects of an image sensor for a camera that includes an image sensor and outputs image data based on a signal output from the image sensor, A receiver for receiving image data output from the above camera; and A processor for processing image data applied to the receiver; comprising The above processor is: The image data is configured to be divided into at least one region based on the brightness distribution of the image data, and Configured to extract defective pixels based on the criteria for each of the aforementioned separated regions, A device for determining pixel defects.

2. In Paragraph 1, The above processor is, Each of the above at least one region is configured to distinguish regions such that the brightness difference between pixels included within the region is similar, and Among the pixels included within the above-described regions, configured to extract pixels presumed to be defective based on the brightness deviation of the pixels relative to the criteria for each of the above-described regions. A device for determining pixel defects.

3. In Paragraph 1, The above processor is, It is configured to classify types of pixel defects from the extracted defect pixels, and The types of pixel defects mentioned above are, At least one of a cold pixel, a hot pixel, a dead pixel, or a noise pixel, A device for determining pixel defects.

4. In Paragraph 1, The above processor is, Configured to generate a report containing information about the aforementioned extracted defect pixels, A device for determining pixel defects.

5. In Paragraph 1, The above processor is, Configured to set the operating conditions of the above image sensor as default conditions, A device for determining pixel defects.

6. In Paragraph 1, The above processor is, A method configured to extract defective pixels based on criteria for each of the aforementioned separated regions by utilizing at least one algorithm among K-Means Clustering, Adaptive Thresholding, Region Growing, Gaussian Mixture Models (GMM), Edge Detection, and Histogram-Based Segmentation algorithms, A device for determining pixel defects.

7. In Paragraph 4, The above processor is, Configured to generate a report in at least one of table format, map image format, and CSV format, A device for determining pixel defects.

8. A method in which a pixel defect determination device determines a pixel defect of an image sensor in a camera that includes an image sensor and outputs image data based on a signal output from the image sensor, A receiving step in which the receiving unit of the pixel defect determination device receives image data output from the camera; and A processing step in which the processor of the pixel defect determination device processes image data authorized to the receiver; is included, The above processing steps are: A division step in which the processor divides the image data into at least one region based on the brightness distribution of the image data; and An extraction step in which the processor extracts defective pixels based on criteria for each of the aforementioned separated regions; comprising Method for determining pixel defects.

9. In Paragraph 8, The above classification step is, The method further includes the step of the processor dividing regions such that each of the at least one region has a similar brightness deviation between pixels included within the region. The above extraction step is, The method further comprises the step of configuring the processor to extract pixels presumed to be defective among the pixels included within the aforementioned separated regions, based on the brightness deviation of the pixels relative to the criteria for each of the aforementioned separated regions. Method for determining pixel defects.

10. In Paragraph 9, It further includes a classification step in which the processor classifies the type of pixel defect from the extracted defect pixels; and The above classification step is, The method further comprises the step of classifying the pixel defect into at least one of a cold pixel, a hot pixel, a dead pixel, and a noise pixel by the processor. Method for determining pixel defects.

11. A lighting device for use in determining pixel defects of an image sensor in a camera that includes an image sensor and outputs image data based on a signal output from the image sensor, Includes a light source for emitting light; and The above light source is, The light emitted from the light source is configured to be uniformly irradiated over the entire imaging area of ​​the camera, and Configured to have a concave shape so that the emitted light can be uniformly irradiated over the entire imaging area of ​​the camera, Lighting device.

12. In Paragraph 11, It further includes a diffuser layer, The above diffuser layer is, Configured to be positioned along the curved surface of a light source having the above-mentioned concave shape, Lighting device.

13. In Paragraph 12, The above diffuser layer is, A configuration configured to reduce deviations in light irradiation direction and intensity according to the curvature of a light source having the above-mentioned concave shape, Lighting device.

14. In Paragraph 11, The above diffuser layer is formed to have a material that scatters and diffuses light generated from the above light source, Lighting device.

15. In Paragraph 11, The above camera is, Includes an optical system; The above optical system is, A lens comprising a lens that refracts external light received by the camera to converge toward the center, Lighting device.

16. In Paragraph 15, The above light source is, It is configured to have a curvature corresponding to the curvature of the above optical system, and The center of the curvature of the above light source is, Formed to coincide with the center of curvature of the optical system or to have a distance of less than or equal to the center of curvature of the optical system, Lighting device.

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