KR102043664B1 - Auto Repair System and Method for Detecting and Repairing Defects in a Substrate - Google Patents

Abstract

Disclosed are an auto-repair system detecting and repairing a defect in a substrate and a method thereof. According to an embodiment of the present invention, the auto-repair system includes: a defect detection device creating an image of a substrate to be inspected, recognizing a unit pixel included in the substrate from the image of the substrate, and comparing a pre-stored reference image of a unit pixel to an image of each unit pixel to detect whether there is a defect in each unit pixel; a defect discrimination device receiving an image of a pixel with a defect, selecting a target pixel for analysis on the defect in the received image, and discriminating information on the defect existing in the target pixel; and a repair device selecting a repair method corresponding to the information of the defect based on the information of the defect discriminated by the defect discrimination device to repair the defect in accordance with the selected repair method.

Description

Auto Repair System and Method for Detecting and Repairing Defects in a Substrate

The present invention relates to an auto repair system and method for detecting and determining defects in a substrate and then repairing the identified defects.

The contents described in this section merely provide background information on the present embodiment and do not constitute a prior art.

With the remarkable development of the display device technology, the technology related to various types of image display apparatuses, such as a liquid crystal display and a plasma display, has advanced greatly. In particular, in image display apparatuses and the like which realize large sized and high-precision displays, high technological innovations have been made in order to reduce manufacturing costs and improve image quality. The glass substrates mounted on such various apparatuses and used for displaying images are also required to have high dimensional quality and high-precision surface properties. In manufacture of glass, such as a display device use, although a glass substrate is shape | molded by using various manufacturing apparatuses, it is common to perform shaping | molding to predetermined shape after heat-dissolving an inorganic glass raw material and homogenizing a molten glass in all. In this case, there are various reasons such as insufficient melting of the glass raw material, unintended mixing of foreign materials during the manufacturing process, problems of aging of the molding apparatus, temporary molding conditions, and defects occurring during the process of cutting to a desired size after completion. This may cause defects such as abnormalities in surface quality on the glass substrate.

Various countermeasures have been taken so far to suppress the occurrence of such defects in glass substrates, but it is difficult to completely suppress the occurrence of defects, and even to some extent, the occurrence of defects can be suppressed. If there is no technique for clearly identifying the defects, defects that are supposed to be defects are mixed in glass substrates determined as good products. Therefore, the technique of detecting defects of the glass substrate with high precision and discriminating the detected defects is very important.

As a method of inspecting and determining defects in glass substrates, the visual inspection method, which relies on the inspector's senses, has been widely used in the past, but such visual inspection method has a great effect on the accuracy of inspection and the time required for inspection as the glass substrate is enlarged. Exposing the limits.

In addition, due to such incorrect defect determination, repair of defects occurring in the glass substrate is inevitably performed. Where the defects in the glass substrates occur and what kind of defects in the glass substrates are clearly determined, the repair of the defects can be performed correctly accordingly. However, as the detection and discrimination of defects occurring in the glass substrate are inaccurately performed, the repair of defects is also inaccurately performed, and there is a problem that a repair that should not be performed may be performed on a portion of the glass substrate that is not abnormal, and the repair to be performed is performed. Problems can also occur if is not performed.

Therefore, it is necessary to develop an automated repair system that accurately inspects and identifies glass substrate defects and performs appropriate repairs according to the identified defects.

One embodiment of the present invention is to provide an auto repair system and method for analyzing and analyzing the image of the substrate to detect and determine the defect in the substrate, and to properly repair according to the type of the determined defect.

According to an aspect of the present invention, an image of a substrate to be inspected is generated, a unit pixel included in the substrate is recognized from the image of the substrate, and a reference image of a previously stored unit pixel is compared with an image of each generated unit pixel. Receiving a defect detection device for detecting whether a defect exists in each unit pixel and an image of a pixel in which the defect exists, selecting a target pixel for analyzing a defect in the received image, A repair apparatus for determining a defect information and a repair method corresponding to the defect information are selected based on the defect information determined by the defect determination apparatus, and the repair apparatus repairs the defect according to the selected repair method. It provides an auto repair system comprising a.

According to an aspect of the present invention, the information of the defects may include information about the type of defects related to how the defects present in the target pixel exist in the target pixel, and at which position of the layer the defects in the target pixel exist. It characterized in that it comprises the position of a defect with respect to.

According to an aspect of the invention, the repair method is characterized in that it comprises some or all of the digital micromirror device (DMD), cutting (Laser Chemical Vapor Deposition) and laser irradiation.

According to an aspect of the present invention, a first generation process of generating an image of a substrate to be inspected, a recognition process of recognizing unit pixels included in the substrate from the image of the substrate, a reference image of the prestored unit pixels, and the generated angle A detection process of detecting whether a defect exists in each unit pixel by contrasting an image of a unit pixel, a selection process of selecting a target pixel for analysis of a defect in the image of the pixel in which the defect exists, and an existing process in the target pixel Determination process of determining defect information, selection process of selecting a repair method corresponding to defect information based on the defect information determined in the determination process, and repair process of repairing defects according to the selected repair method It provides an auto repair method comprising a.

According to an aspect of the present invention, the information of the defects may include information about the type of defects related to how the defects present in the target pixel exist in the target pixel, and at which position of the layer the defects in the target pixel exist. It characterized in that it comprises the position of a defect with respect to.

According to an aspect of the invention, the repair method is characterized in that it comprises some or all of the digital micromirror device (DMD), cutting (Laser Chemical Vapor Deposition) and laser irradiation.

As described above, according to an aspect of the present invention, by detecting and discriminating a defect in a substrate and automating repair of the determined defect, there is an advantage that it is possible to easily and accurately handle the detection, discrimination and repair of a defect in the substrate. have.

1 is a diagram illustrating a configuration of an auto repair system according to an embodiment of the present invention.
2 is a diagram showing the configuration of a defect detection apparatus according to an embodiment of the present invention.
3 is a diagram illustrating a reference image of a unit pixel and an image of a substrate to be inspected according to an embodiment of the present invention.
4 is a diagram illustrating an analysis of a reference image and an image of a substrate to be inspected according to an embodiment of the present invention.
5 is a diagram illustrating a result of analyzing an image of a unit pixel according to an exemplary embodiment of the present invention.
6 is a diagram illustrating an area of each unit pixel in a substrate according to an embodiment of the present invention.
7 illustrates a reference image of a unit pixel, an image of a unit pixel, and a subtraction image according to an embodiment of the present invention.
8 illustrates a mask generated according to an embodiment of the present invention.
FIG. 9 illustrates a method of generating a binarized image by using a subtraction image and a mask according to an embodiment of the present invention.
FIG. 10 is a diagram illustrating a final binarized image from which noise existing in a binarized image is removed according to an embodiment of the present invention.
FIG. 11 is a diagram illustrating a reference image of a unit pixel group that varies according to an embodiment of the present invention.
12 is a diagram illustrating a reference image of a unit pixel according to a second embodiment of the present invention.
FIG. 13 is a diagram illustrating a reference image of a unit pixel and an image of a substrate to be inspected according to a second exemplary embodiment of the present invention.
14 is a diagram illustrating an area of each unit pixel in a substrate according to a second exemplary embodiment of the present invention.
15 is a flowchart illustrating a method of detecting a defect in a substrate by a defect detecting apparatus according to an embodiment of the present invention.
16 is a diagram illustrating a configuration of a defect determining apparatus according to an embodiment of the present invention.
17 illustrates a target pixel according to an embodiment of the present invention.
18 is a diagram illustrating a method of determining a type of a defect by a defect type determining unit according to an embodiment of the present invention.
19 is a diagram illustrating a method for analyzing defects in detail according to an embodiment of the present invention.
20 is a diagram illustrating a method for analyzing a second type of defect according to an embodiment of the present invention.
21 is a diagram illustrating a method of analyzing a location of a defect according to an embodiment of the present invention.
22 is a diagram illustrating a method of analyzing a region of a defect, according to an embodiment of the present invention.
FIG. 23 is a flowchart illustrating a method of determining a defect detected in a substrate by a defect determining apparatus according to an embodiment of the present invention.
24 is a diagram illustrating a configuration of a repair apparatus according to an embodiment of the present invention.
25 is a flowchart illustrating a method of repairing a defect of a substrate by a repair apparatus according to an embodiment of the present invention.

As the inventive concept allows for various changes and numerous embodiments, particular embodiments will be illustrated in the drawings and described in detail in the written description. However, this is not intended to limit the present invention to specific embodiments, it should be understood to include all changes, equivalents, and substitutes included in the spirit and scope of the present invention. In describing the drawings, similar reference numerals are used for similar elements.

Terms such as first, second, A, and B may be used to describe various components, but the components should not be limited by the terms. The terms are used only for the purpose of distinguishing one component from another. For example, without departing from the scope of the present invention, the first component may be referred to as the second component, and similarly, the second component may also be referred to as the first component. The term and / or includes a combination of a plurality of related items or any item of a plurality of related items.

When a component is referred to as being "connected" or "connected" to another component, it may be directly connected to or connected to that other component, but it may be understood that other components may be present in between. Should be. On the other hand, when a component is said to be "directly connected" or "directly connected" to another component, it should be understood that there is no other component in between.

The terminology used herein is for the purpose of describing particular example embodiments only and is not intended to be limiting of the invention. Singular expressions include plural expressions unless the context clearly indicates otherwise. It is to be understood that the term "comprises" or "having" in the present application does not exclude in advance the possibility of the presence or addition of features, numbers, steps, operations, components, parts or combinations thereof described in the specification. .

Unless defined otherwise, all terms used herein, including technical or scientific terms, have the same meaning as commonly understood by one of ordinary skill in the art.

Terms such as those defined in the commonly used dictionaries should be construed as having meanings consistent with the meanings in the context of the related art and shall not be construed in ideal or excessively formal meanings unless expressly defined in this application. Do not.

In addition, each component, process, process, or method included in each embodiment of the present invention may be shared within a range that is not technically contradictory.

1 is a diagram illustrating a configuration of an auto repair system according to an embodiment of the present invention.

Referring to FIG. 1, an auto repair system 100 according to an exemplary embodiment of the present invention includes a defect detecting apparatus 110, a defect determining apparatus 120, a repair apparatus 130, and a controller 140.

The defect detector 110 generates an image of the substrate to detect a defect of the substrate. The defect detection apparatus 110 analyzes an image of the substrate and recognizes each unit pixel included in the substrate in the image of the substrate. The defect detection apparatus 110 recognizes the coordinates of each unit pixel, and also recognizes each layer in the pixel together with the pixel coordinates. Defects can occur across an entire pixel, but may only occur for some layers within a pixel. If only the pixel is recognized, there is a possibility that the defect detection apparatus 110 may not fully detect the specific location where the defect occurred in the pixel. Accordingly, the defect detection apparatus 110 may distinguish each layer with a different color so that the defect determination apparatus 120 may recognize each layer in the pixel. Thereafter, the defect detection apparatus 110 compares a pre-stored reference image of a unit pixel (hereinafter, abbreviated as 'reference image') and an image of each unit pixel (hereinafter, abbreviated as 'pixel image'), It is determined whether a defect exists in each unit pixel. The defect detector 110 detects a defect in the subtraction image by generating a subtraction image by subtracting the reference image and the pixel image. The reference image corresponds to each pixel image in which no defect exists, and in some cases, may be replaced in the defect detection process. If the substrate is a substrate of several m * s m size for fabricating a plurality of display devices, a significant number of pixels in the substrate will be included. Accordingly, even though there is no structural difference between the pixel at one end of the substrate and the pixel at the other end, minute differences such as color, brightness, and contrast may occur. Due to this difference, there is a fear that a defect is detected even in unit pixels without substantial (structural) defects. In order to prevent such a problem, the defect detection apparatus 110 may replace the reference image for each predetermined area.

In this case, the reference image and the pixel image include R, G, and B channels, respectively. As described above, in the case of a substrate having a size of several m * several m, a considerable number of pixels are included in the substrate, and the process of detecting defects because each pixel image and the reference image include R, G, and B channels. There is a concern that the amount of computation will be very high. Accordingly, the defect detection apparatus 110 may generate an average image (average reference image and average pixel image) by calculating an average value for each of the R, G, and B channels of the reference image and the pixel image, thereby reducing the amount of computation. In addition, the defect detection apparatus 110 may binarize each image by using a mask in order to increase the detection probability of the defect. The defect detection apparatus 110 performs binarization so that different portions of the reference image and the pixel image can be more clearly highlighted. The defect detection apparatus 110 transmits the pixel image, the subtraction image, and the binarized image of each image to the defect determination apparatus 120. A detailed description of the defect detection apparatus will be described with reference to FIGS. 2 to 15.

The defect determining apparatus 120 determines the type, type, and location of the defect by using each image and each binarization image received from the defect detecting apparatus 110. The defect determining apparatus 120 determines, in detail, which defects have occurred in which pixels of which layers, with respect to the defects detected by the defect detecting apparatus 110. As described above, the defect discrimination apparatus 120 specifically discriminates the detected defect, so that the defect can be appropriately compensated according to the determination result. A detailed description of the defect determination apparatus will be described with reference to FIGS. 16 to 23.

The repair apparatus 130 receives the defect information determined by the defect determination apparatus 120 and repairs the defect appropriately in accordance with the defect information. The repair apparatus 130 receives the defect information including the type, type, and location of the defect from the defect determination apparatus 120. The repair apparatus 130 analyzes the received defect information and selects a repair method suitable for repairing a defect generated in the substrate. The repair apparatus 130 repairs the defect of the substrate by using the selected repair method. After repairing the defect, the repair apparatus 130 may check whether the repair is correctly performed and review whether the repair is completely performed, and if the repair is not performed completely, may repair again. A detailed description of the repair apparatus will be described with reference to FIGS. 24 and 25.

The controller 140 controls the operations of the devices 110, 120, and 130. When the substrate for inspecting the presence of a defect is transferred, the controller 140 controls the defect detection apparatus 110 to detect whether a defect in the substrate to be transferred exists. The controller 140 controls the defect detector 110 to transmit each image of the substrate detected by the defect detector 110 to the defect determiner 120, and the defect determiner 120 specifically includes a defect such as the type, type, and location of the defect. Control the analysis and determination of information. Subsequently, the controller 140 controls the defect determining apparatus 120 to transmit the information of the defect determined to the repair apparatus 130, and the repair apparatus 140 is optimal for removing the defect caused by analyzing the information of the defect. Select repair method and control to repair.

In FIG. 1, the defect detection device 110, the defect determination device 120, the repair device 130, and the control device 140 are respectively implemented as separate devices, but are not necessarily limited thereto. Each device 11, 120, 130 and 140 in the device may be implemented in the form of a module, respectively. However, hereinafter, for convenience of explanation, each device 11, 120, 130 and 140 will be described as an example implemented as a separate device.

2 is a diagram showing the configuration of a defect detection apparatus according to an embodiment of the present invention.

Referring to FIG. 2, the defect detecting apparatus 110 according to an exemplary embodiment of the present invention may include a substrate transfer unit 210, an image generator 220, a unit pixel recognition unit 230, a memory unit 240, and a preprocessor. 250, an image collation unit 260, a defect detector 270, a control unit 280, and a communication unit 290.

The substrate for detecting a defect includes a plurality of pixels. In general, a substrate includes a large number of pixels, and each pixel also includes a plurality of layers. The pixel in the substrate is implemented by a plurality of layers such as an active layer, a gate layer, a source and a drain layer. In the process of generating a substrate, fine particles may be introduced to cause defects on the substrate, and in particular, may be introduced into any layer of pixels in the substrate to cause defects on a specific layer. The defect detecting apparatus 110 may detect which pixels of which layers of the layers included in the substrate exist.

The substrate transfer unit 210 transfers the substrate in a predetermined direction. The substrate transfer unit 210 transfers the substrate to the correct position for detecting the defect. In addition, the substrate transfer unit 210 transfers the substrate after the defect detection process so as to undergo a substrate processing process or a precision defect inspection process.

The image generator 220 generates an image of the substrate to detect a defect of the substrate. The image generator 220 is implemented as a device capable of generating an image of a substrate, such as a camera, and generates an image of the substrate transferred by the substrate transfer unit 210.

The unit pixel recognition unit 230 recognizes each unit pixel included in the substrate in the image of the substrate. The unit pixel recognition unit 230 analyzes an image of the substrate and recognizes each unit pixel included in the substrate. The unit pixel recognition unit 230 analyzes the image of the substrate in the horizontal and vertical directions, respectively, and recognizes the start x coordinate and the start y coordinate of each unit pixel. The unit pixel recognizing unit 230 recognizes a start x coordinate and a start y coordinate of each unit pixel, thereby using the start coordinates of the specific unit pixel and the start coordinates of the unit pixel adjacent to the specific unit pixel in the x-axis direction. The length, the length and the area in the y-axis direction can be recognized. For example, when the start coordinate of a specific unit pixel is (0, 0) and the coordinates of the unit pixel adjacent thereto are (45,0), (0, 45), respectively, the x-axis direction of the specific unit pixel Are 45 and 45, respectively, and the area of the specific unit pixel is 2025. As such, the unit pixel recognition unit 230 recognizes each unit pixel, so that later configuration can identify which pixel is defective in confirming the existence of the defect through comparison with the reference image.

The unit pixel recognition unit 230 may also recognize each layer in the pixel in recognizing each pixel in the substrate. Defects can occur across an entire pixel, but may only occur for some layers within a pixel. In this case, if the unit pixel recognition unit 230 recognizes only the pixel, there is a possibility that the defect detection apparatus may not fully detect the specific position where the defect occurred in the pixel. Accordingly, the unit pixel recognition unit 230 may distinguish each layer in the pixel by an identifier or a color indicating each layer so that the control unit 280 may recognize the layers.

In addition, the unit pixel recognition unit 230 may recognize the unit pixel by using a line profile method. The line profile method is a method of representing the characteristics of an image in lines. The line profile method may analyze the entire image or only a certain region or section in the image, and represents an average value or a sum for a certain direction. The unit pixel recognition unit 230 may recognize each unit pixel start coordinate by analyzing a line representing such image characteristics. However, the present invention is not necessarily limited thereto, and any method may be used as long as it can recognize the starting coordinate of each unit pixel. However, hereinafter, for convenience of explanation, the unit pixel recognition unit 230 will be described as recognizing the unit pixel using the line profile method.

The memory unit 240 stores a reference image of a unit pixel. The memory unit 240 stores a reference image of the unit pixel so that the unit pixel recognition unit 230 may determine whether there is a defect in each unit pixel through comparison with each unit pixel recognized. The reference image of the unit pixel stored in the memory unit 240 corresponds to an image of the unit pixel without a defect. The memory unit 240 stores an image of a unit pixel without any defect as a reference image, so that another configuration may later detect whether a defect exists in each unit pixel by contrasting with the reference image.

The memory unit 240 may replace the stored reference image of the unit pixel under the control of the controller 280. If the number of pixels included in the substrate is very large, the pixels may be slightly different depending on the positions disposed in the substrate. For example, if the substrate is a substrate of size m * several m for fabricating a plurality of display devices, a significant number of pixels in the substrate will be included. Accordingly, even though there is no structural difference between the pixel at one end of the substrate and the pixel at the other end, minute differences such as color, brightness, and contrast may occur. Due to this difference, there is a fear that a defect is detected even in unit pixels without substantial (structural) defects. In general, there is a high probability that unit pixels having similar color, brightness, contrast, and the like are arranged in a specific area of the substrate. Accordingly, when the same reference image is selected as one end of the substrate, the unit pixels disposed at the other end of the substrate and the unit pixels disposed in the peripheral region are both different from the reference image and thus may be detected as defective. This exists. In order to prevent this problem, the controller 280 may replace the reference image of the unit pixel for each predetermined region. For example, the controller 280 may replace the reference image of the preset unit pixel with an image similar to the most reference image among the images having a difference from the reference image. As such, as the reference image of the unit pixel is replaced for each region of the substrate, the accuracy of defect detection is increased. The memory unit 240 may replace and store the reference image of the unit pixel or may additionally store the reference image under the control of the controller 280.

The preprocessor 250 preprocesses the reference image of the unit pixel. The preprocessor 250 performs preprocessing on the reference image of the unit pixel so that the contrast may be smoothly performed before the image collation unit 260 contrasts the image of each unit pixel on the substrate with the reference image of the unit pixel. For example, when the long axis of the image of each unit pixel is disposed in the x-axis direction, while the long axis of the reference image of the unit pixel stored in the memory unit 240 is disposed in the y-axis direction, the image and unit of each unit pixel are disposed. Discomfort arises in the contrast of the reference image of the pixels. In order to solve this inconvenience, the preprocessor 250 may change the direction of the reference image. The preprocessor 250 performs preprocessing such that the image contrast unit 260 smoothly collates the image of each unit pixel and the reference image of the unit pixel, such as changing the direction of the reference image.

The image contrast unit 260 contrasts the image of each unit pixel with the reference image of the unit pixel so as to determine whether there is a defect in each unit pixel. When the image contrast unit 260 contrasts the image of each unit pixel with the reference image of the unit pixel, the image contrast unit 260 contrasts only the image of the unit pixel whose area of the image of each unit pixel is equal to or larger than a preset value set by the controller 280. It can be carried out. For example, the image of the unit pixel disposed at each end in the image of the substrate may be generated with all areas not cut out in the image of the substrate generated by the image generator 220. As such, since the image of the unit pixel in which all the areas are not exposed is difficult to be completely contrasted with the reference image, the image contrast unit may perform the contrast only for the image of the unit pixel in which the area of the image of each unit pixel is equal to or larger than a predetermined value.

The defect detector 270 detects a defect existing in each unit pixel by using the collation result of the image collation unit 260. The defect detector 270 detects whether a defect is finally present through the brightness correction and binarization of the image background in the collation result of the image collation unit 260.

The controller 280 controls the operation of each component (210 to 270 and 290). The controller 280 controls the unit pixel recognition unit 230 to recognize the image of the substrate in both the horizontal and vertical directions so as to recognize the unit pixel in the image of the substrate. The controller 280 sets a numerical value for determining a unit pixel to be contrasted when the image collation unit 260 contrasts the image of each unit pixel with the reference image. The controller 280 allows the image contrast unit 260 to perform image contrast with the reference image only of unit pixels having an area greater than or equal to a predetermined value. When a defect is detected in too many unit pixels based on the detection result of the defect detector 270, the controller 280 may determine that the reference image stored in the memory unit 240 is the most among the image of the unit pixel having a difference from the currently stored reference image. The memory unit 240 may be controlled to be replaced with an image similar to the reference image or stored in addition to the reference image. As a result, the controller 280 may correct minute differences between the unit pixels according to the arrangement of the unit pixels in the substrate. In addition, the controller 280 may control the defect detection level of the defect detector 270. For example, when the defect detection apparatus 110 is used in an environment where even minute defects of the substrate cannot be tolerated, the controller 280 may also display minute differences (eg, differences in color, contrast, etc., not structural differences). The defect detector 270 may be controlled to detect a defect. On the other hand, when the defect detection apparatus 110 is used in an environment in which only a structural defect in a unit pixel needs to be detected, the controller 280 may control the defect detector 270 such that a minute difference is not detected as a defect. This is illustrated in FIG. 11.

FIG. 11 is a diagram illustrating a reference image of a unit pixel group that varies according to an embodiment of the present invention.

The memory unit 240 may replace or add the reference image 310 pre-stored by the controller 280 with one or more of the other images 1110, 1120, and 1130 and store the same. As shown in FIG. 11, the images 1110, 1120, and 1130 to be replaced or additionally stored with the reference image 310 are not structurally different from the reference image 310, and only minute differences such as contrast and color are shown. Have

The controller 280 controls the communicator 290 to transmit the coordinates of the unit pixel detected by the defect detector 270 to the presence of a defect to an external device (not shown). The controller 280 transmits the coordinates of the unit pixels in which the defect exists to the repair apparatus 130 that repairs the defect, thereby repairing the defect. Alternatively, the controller 280 transmits the coordinates of the unit pixel in which the defect exists to the defect determination device 120 that detects the defect more precisely, so that the defect existing in the substrate can be detected more precisely. There may be cases where defects in the substrate are present in a certain area from the center or the center of the substrate, so that they are all detected on the image of the substrate. However, in addition to this case, there may be a case in which defects in the substrate exist outside the substrate and thus are not all detected on the image of the substrate. In the latter case, since a defect existing in the substrate is not completely detected, it may be inconvenient to perform the same repair process again for the remaining defects later when a process for repairing the defect is performed. In order to prevent such inconvenience, the control unit 280 transmits the coordinates of the unit pixel to the defect discrimination apparatus 120 that detects the defect more precisely, so that the external device moves the coordinates to the center (at the center of the substrate) to a certain area. It allows the precise detection of the presence of a fault again. Accordingly, all regions of the defect present in the substrate can be detected.

The communication unit 290 transmits the coordinates of the unit pixel where the defect is detected to the external device.

3 is a diagram illustrating a reference image of a unit pixel and an image of a substrate to be inspected according to an embodiment of the present invention.

3A illustrates a reference image 310 of a unit pixel stored in the memory unit 240 according to an embodiment of the present invention. The reference image 310 is an image of a unit pixel in which no defect exists, and may be stored in the memory unit 240 before the defect detection apparatus 110 detects a defect of the substrate. ) Can be replaced in the process of detecting defects in the substrate.

3B illustrates an image 320 of a substrate generated by the image generator 220 according to an exemplary embodiment. The image 320 of the substrate includes an image 325 of each unit pixel.

As illustrated in FIG. 3, the reference image 310 and the image 325 of each unit pixel may be disposed in different directions. In this case, since it is difficult to substantially detect whether a defect exists in each unit pixel in the substrate, the preprocessor 250 converts the direction of the reference image 310 and arranges the same direction as the image of each unit pixel. According to the example shown in FIG. 2, the preprocessor 250 may rotate the reference image 310 by 90 degrees clockwise so that the long axis of the reference image 310 is disposed in the y-axis direction.

4 is a diagram illustrating an analysis of a reference image and an image of a substrate to be inspected according to an embodiment of the present invention.

The unit pixel recognition unit 230 analyzes the reference image and the image of the substrate, respectively. The unit pixel recognition unit 230 may analyze only a predetermined section of the reference image and calculate an average value for a predetermined direction. As a result, the unit pixel recognizer 230 may generate a line profile of the reference image. Meanwhile, the unit pixel recognition unit 230 generates the line profile 410 in the same manner with respect to the image of the substrate. However, since the substrate includes many unit pixels, the average value of the image of the substrate is calculated at predetermined intervals. Here, the predetermined interval may be set to the length of the unit pixel. As shown in FIG. 3, when the unit pixel recognition unit 230 analyzes an image of the substrate in the vertical direction to recognize the starting y-coordinate of each pixel, the predetermined interval may be set to the horizontal length of the unit pixel. have. When the unit pixel recognition unit 230 calculates an average value of the image of the substrate for one column, the unit pixel recognition unit 230 may move by a predetermined interval to calculate the average value of the image of the substrate. Accordingly, the unit pixel recognizer 230 generates a line profile 420 for each column of the image of the substrate.

The unit pixel recognition unit 230 re-analyzes the reference image and the image of the substrate in a direction perpendicular to the direction in which the reference image and the image of the substrate are analyzed. The unit pixel recognition unit 230 must recognize not only the starting y coordinate but also the starting x coordinate in order to recognize the coordinates of each unit pixel in the image of the substrate. Accordingly, the unit pixel recognition unit 230 re-analyzes the reference image and the image of the substrate in a direction perpendicular to the direction in which the reference image and the image of the substrate are previously analyzed. The unit pixel recognizer 230 generates line profiles 410 and 420 of the reference image analyzed in the vertical direction and the image of the substrate.

5 is a diagram illustrating a result of analyzing an image of a unit pixel according to an exemplary embodiment of the present invention.

The unit pixel recognition unit 230 subtracts the line profile 510 of the generated reference image and the line profile 520 of the image of the substrate. Since the line profile 510 of the reference image and the line profile 520 of the image of the substrate are different in length, the unit pixel recognition unit 230 may add the line profile 510 of the reference image to the line profile 520 of the image of the substrate. ) Is calculated repeatedly to calculate the subtraction line profile 510.

The subtraction line profile 510 has points 520, 523, 526, and 529 having values that are relatively much lower than the perimeter. This point appears at the boundary between the unit pixel and the unit pixel, and the subtraction line profile 510 has a very low value at the boundary point between each unit pixel.

As such, since the unit pixel recognition unit 230 calculates a cool line profile for both the reference image and the line profile generated in one direction with respect to the image of the substrate and the line profile generated in a direction perpendicular thereto, the unit pixel recognition unit 230 calculates the inside line image. It is possible to recognize the starting x and y coordinates of all included unit pixels. In addition, since the coordinates of all unit pixels can be recognized, the area of each unit pixel can also be known.

6 is a diagram illustrating an area of each unit pixel in a substrate according to an embodiment of the present invention.

When the unit pixel recognition unit 230 recognizes all the unit pixels in the image of the substrate, and the preprocessor 250 completes all the preprocessing necessary for the reference image stored in the memory unit 240, the image contrast unit 260 may perform the reference. Contrast with the image of each unit pixel in the image and the image of the substrate. In this case, the image contrast unit 260 checks the area of each unit pixel in the image of the substrate before performing the image contrast. The image contrast unit 260 performs image contrast with the reference image only on the unit pixels whose area of each unit pixel is greater than or equal to a predetermined value. For example, the unit pixel 610 or the unit pixel 615 is located at each end, so that all areas are not included in the image of the substrate. Since intact contrast is not performed on these unit pixels, the image contrast unit 260 does not perform image contrast on these unit pixels.

7 illustrates a reference image of a unit pixel, an image of a unit pixel, and a subtraction image according to an embodiment of the present invention.

Referring to FIG. 7A, the image contrast unit 260 contrasts the image 325 of each unit pixel remaining after the preprocessing process described with reference to FIG. 6 with the reference image 310. Since the image having no defect in the unit pixel image is substantially the same as the reference image 310, no image is derived as the subtraction image. On the other hand, as shown in FIG. 7, when the image contrast unit 260 subtracts the image 325 of the unit pixel in which the defect exists and the reference image 310, the subtraction image 710 in which only the defective portion exists is present. Is generated.

The image contrast unit 260 may generate a subtraction image 710 and calculate an average value of the subtraction image 710. Since the unit pixel image 225 and the reference image 310 include R, G, and B channels, respectively, the unit pixel image 225 and the reference image 310 are subtracted for each channel. There is a fear of increase. Therefore, in order to further improve the computation speed, the image contrast unit 260 may generate the average subtraction image 710 by obtaining the subtraction values for the R, G, and B channels, respectively, and averaging them.

Referring to FIG. 7B, the image collation unit 260 may similarly calculate an average value with respect to the reference image 310 to generate an average reference image 720. As described above, since the reference image 310 also includes R, G, and B channels, there is a concern that the amount of calculation increases when another configuration is used by the reference image 310 later. Therefore, the image contrast unit 260 may generate the average reference image 720 by calculating the average value of each channel with respect to the reference image 310 as well.

8 illustrates a mask generated according to an embodiment of the present invention.

The masks 810 and 820 are formed according to the pattern of the reference image, and are used to clearly identify where the subtraction image 710, in particular, the average subtraction image 710 is different from the reference image. The masks 810, 820 are in the mask 810 and the reference image 310, leaving only portions other than the pattern formed in the reference image 310 to binarize the subtraction image 710, in particular the average subtraction image 710. Each of the masks 820 leaving only the formed pattern portion may be used.

FIG. 9 illustrates a method of generating a binarized image by using a subtraction image and a mask according to an embodiment of the present invention.

The defect detector 270 generates a binarized image 910 of the subtraction image using the subtraction image 710 and the mask 810. The defect detector 270 applies the mask 810 to the subtraction image 710 so that only portions other than the pattern (parts in which defects exist) remain in the subtraction image 710. The defect detector 270 generates a binarized image 910 of the subtraction image by applying a threshold to the subtraction image to which the mask 810 is applied. The defect detector 270 performs binarization on the subtraction image to which the mask 810 is applied by applying a preset threshold.

FIG. 10 is a diagram illustrating a final binarized image from which noise existing in a binarized image is removed according to an embodiment of the present invention.

The defect detector 270 removes the noise 1010 existing in the binarized image 910. The defect detector 270 may classify the noise as a noise 1010 when the thickness of the defect detected in the binarization image 910 is smaller than or equal to a predetermined size or smaller than a predetermined area. In the process of the image contrast unit 260 contrasting the image and generating the subtracted image 710, or in the process of the defect detector 270 applying the mask 810 to generate the binarized image 910, the noise 1010 may be reduced. It is mainly caused by minute position error between internal patterns. Since the noise 1010 is not an object to be detected, the defect detector 270 removes the noise 1010 existing in the binarized image 910. The defect detector 270 detects a defect in the binarized image 910 from which the noise 1010 is removed.

In this case, the defect detector 270 may determine the type of the detected defect. Types of defects include residual defects, open defects, hole defects, dark defects, and seed defects. The residual defect refers to a defect in which the pattern of the substrate further includes an unnecessary pattern compared to the reference pattern of the reference image due to problems in the apparatus during the pattern generation process of the substrate. It means a defect that does not have a pattern to be provided. For example, a residual defect means that a pattern of 'ㅡ' shape should be generated but a pattern of '모양' shape is generated, and an open defect means a pattern of 'ㅗ' shape should be generated. This means that a pattern is created. A hole type defect means a defect in which a hole is not formed like a reference pattern in a situation in which a hole should be formed in a pattern of a substrate. Dark type defect refers to a defect that occurs as much as the area of the introduced factor when defects are generated due to the inflow of particles, etc. during the substrate generation process, and a seed type defect refers to a certain area at the periphery of the factor in addition to the area of the introduced factor. It means a defect occurred. Each kind of defects must be distinguished, so that processes for repairing the defects later may proceed differently depending on the defects. The defect detector 270 may determine the type of each defect, and in particular, the defect detector 270 may determine whether the defect is a dark defect or a seed defect in consideration of the ratio of the total area of the defect detected in the binarization image 910 and the area of the introduced factor. You can judge.

12 is a diagram illustrating a reference image of a unit pixel according to a second embodiment of the present invention.

In the reference image 1210, a plurality of pixels may be included in a unit pixel. The substrate includes a plurality of pixels, and the number of pixels configured for each layer of the pixels may be different. For example, one pixel may constitute a unit pixel in the active layer or the gate layer, but two or more pixels may constitute one unit pixel in the source and drain layers. As such, the unit pixels may be different for each layer, so that the memory unit 240 may store the reference image 1210 of each layer to detect defects existing in various layers in order to detect defects on all layers. Hereinafter, for convenience, two pixels in the reference image 1210 are described as being included in a unit pixel, but are not necessarily limited thereto.

The reference image 1210 is divided into a left pixel 1214 and a right pixel 1218, and each pixel 1214 and 1218 does not necessarily have the same area. The areas of each pixel 1214 and 1218 may be the same, but may not be the same. The area ratio of each pixel 1214 and 1218 in the reference image 1210 is stored together in the memory unit 240. For example, the pixel 1214 may have a size of (0.49, 1), the pixel 1218 may have a size of (0.51, 1), and a corresponding ratio in the memory unit 240 may be stored together.

FIG. 13 is a diagram illustrating a reference image of a unit pixel and an image of a substrate to be inspected according to a second exemplary embodiment of the present invention.

The unit pixel recognition unit 230 recognizes each unit pixel included in the image 1310 of the substrate, and after recognition, the image collation unit 260 may store the image of the substrate and the reference image 1210 stored in the memory unit 240. (1310) can be contrasted. Of course, the preprocessing process may be performed on the reference image 1210 while passing through the preprocessor 250 before the image contrast unit 260 is collated. The image contrast unit 260 contrasts the image 1320 of the unit pixel in the image 1310 of the substrate with the reference image 1210. The image contrast unit 260 contrasts each image 1210 and 1320 in correspondence with the position of each pixel included in the unit pixel. That is, the image contrast unit 260 contrasts the left pixel 1214 on the reference image 1210 with the left pixel 1324 on the unit pixel image 1320, and the right pixel 1218 on the reference image 1210 is unit Contrast with the right pixel 1328 on the pixel image 1320.

In this case, the area ratio of each pixel on the unit pixel image 1320 may be different from that of the reference image 1210. In this case, the image contrast unit 260 calculates the size of the unit pixel image by multiplying the area ratio of the reference image stored in the memory unit 240. Accordingly, the image collimator 260 may contrast the reference image 1210 and the unit pixel image 1320 having different area ratios without difficulty.

Thereafter, the defect detector 270 detects a defect existing in each unit pixel by using the image matching result.

14 is a diagram illustrating an area of each unit pixel in a substrate according to a second exemplary embodiment of the present invention.

When the image collation unit 260 collates each of the images 1210 and 1320, it is determined whether the area of each pixel in the image 1320 of the unit pixel is greater than or equal to a predetermined value set by the controller 280. If any of the pixels 1324 and 1328 included in the image 1320 of the unit pixel does not exceed a predetermined value, the image contrast unit 260 does not contrast with the reference image 1210. Since it is difficult to contrast the image of the unit pixel in which all the areas are not exposed, the image contrast unit 260 determines the area of all the pixels included in each unit pixel, respectively, and determines whether or not the predetermined resin or more is performed to perform the image contrast. Select the image of each pixel to be done.

15 is a flowchart illustrating a method of detecting a defect in a substrate by a defect detecting apparatus according to an embodiment of the present invention.

The image generator 220 generates an image of the substrate to be inspected (S1510).

The unit pixel recognition unit 230 recognizes each unit pixel included in the substrate in the substrate image (S1520). The unit pixel recognition unit 230 generates a line profile of the image of the substrate and the reference image by using the line profile method. In generating the line profile, the unit pixel recognition unit 230 generates the line profile in each direction (one direction and a direction perpendicular to each direction) for each of the image and the reference image of the substrate.

The unit pixel recognition unit 230 recognizes the information of each unit pixel included in the substrate by using the reference image (S1530). The unit pixel recognition unit 230 generates a subtraction line profile by subtracting the line profile of the reference image and the line profile of each unit pixel. The unit pixel recognition unit 230 recognizes a boundary of each unit pixel by using a subtraction linen profile to recognize a (start) coordinate of each unit pixel. In addition, since the coordinates of each unit pixel are recognized, the unit pixel recognition unit 230 may also recognize the length of each unit pixel in the x-y axis direction and the area of each unit pixel.

The image collation unit 260 contrasts the image of each unit pixel with the reference image of the unit pixel (S1540). When the unit pixel recognition unit 230 recognizes all the unit pixels in the image of the substrate, and the preprocessor 250 completes all the preprocessing necessary for the reference image stored in the memory unit 240, the image contrast unit 260 may perform the reference. Contrast with the image of each unit pixel in the image and the image of the substrate. The image collation unit 260 may perform image contrast to detect whether a defect exists in each unit pixel.

The defect detector 270 detects a defect existing in each unit pixel by using the matching result (S1550).

16 is a block diagram showing the configuration of a defect discrimination apparatus according to an embodiment of the present invention.

Referring to FIG. 16, a defect determining apparatus 120 according to an exemplary embodiment of the present invention may include a communication unit 1610, a target pixel selection unit 1620, a defect type determination unit 1630, a defect position determination unit 1640, The defect type determination unit 1650 and the memory unit 1660 are included.

The communication unit 1610 receives a subtraction image in which a defect exists and a binarization image of the subtraction image from the defect detection apparatus 110. The communication unit 1610 is connected to the defect detection apparatus 110 by wire or wireless communication, and receives a subtraction image and a binarization image of the subtraction image from the defect detection apparatus 110.

The communication unit 1610 may transmit the determination results of the defect type determination unit 1630 and the defect position determination unit 1640 to the repair apparatus 130.

The target pixel selector 1620 selects a target pixel in which the defect to be determined exists in the received subtraction image or the binarization image of the subtraction image. The defect may exist in only one pixel or may exist over a plurality of pixels. The target pixel selector 1620 selects a pixel in which a defect exists as a target pixel so as to determine a defect. Description of this will be described with reference to FIG. 17.

17 illustrates a target pixel according to an embodiment of the present invention.

Fig. 17A shows the case where a defect exists in a single pixel. When the intra-pixel defect 1710 exists only within a single pixel in the binarization image 910 of the subtraction image, the target pixel selector 1620 selects the pixel as a target pixel for determining the defect.

Fig. 17B shows the case where a defect exists in a plurality of pixels. When the intra-pixel defect 1710 is present in a plurality of pixels in the binarization image 910 of the subtraction image, the target pixel selector 1620 may select all or some pixels in which the defect exists as the target pixel. In this case, the target pixel selector 1620 may select the first target pixel 1720 to determine a pixel closest to the center in the image 910 with the largest defect area among the pixels in which the defect exists. Thereafter, the target pixel selector 1620 determines whether a defect exists in a pixel adjacent to a predetermined direction such as a clockwise or counterclockwise direction with respect to the first target pixel 1720. If the defect is present in the plurality of pixels, the target pixel selector 1620 further selects the target pixel 1725.

 Referring back to FIG. 16, the defect type determiner 1630 determines a type of a defect in the selected target pixel. The defect type determination unit 1630 determines a type of a defect using a mask formed according to the average reference image or the pattern of the reference image stored in the memory unit 1660. The following types of defects exist. Types of defects include a first defect in which the area of the defect lies on the mask area, a second defect in which the area of the defect lies outside the mask area, a third defect in which the area of the defect contacts the mask area, and the area of the defect. Not only this mask region but also the fourth defect in contact with the mask region of the neighboring pixel. Since the determination of the defect type is usually performed for each target pixel, it cannot be reflected when a defect is formed between the pixel and the pixel. Accordingly, the defect type determination unit 1630 determines and classifies the fourth defect. The defect type determination unit 1630 determines the fourth defect as follows. First, the defect type determiner 1630 determines a defect with respect to a first target pixel, and arranges a mask in a neighboring pixel in an appropriate direction according to a position of a defect existing in the first target pixel. For example, when the defect is located below the first target pixel, the defect type determiner 1630 may place a mask on a neighboring pixel in a downward direction with respect to the first target pixel. The defect type determination unit 1630 determines whether the defect corresponds to the fourth defect by determining whether the defect contacts the neighboring pixel. Accordingly, the defect type determiner 1630 may clearly determine whether the defect exists in each target pixel and whether the defect spans the target pixel and the target pixel.

In addition, the defect type determination unit 1630 determines whether the determined defects are connected to each other. Even when there are defects in one target pixel, one defect may be formed, but a plurality of defects may be formed, respectively. In the latter case, the defect type determination unit 1630 determines whether each defect is connected to each other. When each defect is connected, a separate complementary method is required, so the defect type determination unit 1630 determines whether each defect is connected to each other separately from the type of the defect.

The defect position determiner 1640 determines where the defect is in the pixel by using the subtraction image. The defect location determiner 1640 determines which layer in the pixel is specifically located by using the color of the subtraction image. As described above, each layer in each pixel has a color. Using this feature, the defect position determining unit 1640 compares the color of the subtraction image with the color of each layer to determine which layer in the pixel is present and from which layer to which layer. Determine the location.

Based on the determination result of the defect type determination unit 1630 and the determination result of the defect position determination unit 1640, the defect determination apparatus 120 may accurately determine detailed information of a defect existing in the pixel. The defect determining apparatus 120 provides the repair apparatus 130 with detailed information of the determined defect, so that the apparatus for compensating for the defect can be correctly compensated according to the defect.

The defect type determination unit 1650 determines the type of the defect. Types of defects include residual defects, open defects, hole defects, dark defects, and seed defects. Residual defects refer to defects in which the pattern of the substrate additionally includes unnecessary patterns compared to the reference pattern due to problems in the apparatus during the pattern generation process of the substrate. On the contrary, open defects should be provided in the pattern of the substrate compared to the reference pattern. It means a defect having no pattern to do. A hole type defect means a defect in which a hole is not formed like a reference pattern in a situation in which a hole should be formed in a pattern of a substrate. Dark type defect refers to a defect that occurs as much as the area of the introduced factor when defects are generated due to the inflow of particles, etc. during the substrate generation process, and a seed type defect refers to a certain area at the periphery of the factor in addition to the area of the introduced factor. It means a defect occurred. The defect type determiner 1650 easily determines the residual defect and the open defect by comparing the reference image with the pixel image, and considers the ratio of the total area of the defect and the area of the introduced factor to determine whether the defect is a dark defect or a seed defect. Determine if it is.

The memory unit 1660 stores a reference image or an average reference image and a mask necessary for determining a defect. The mask is formed in accordance with the pattern of the reference image along with the reference image. The memory unit 1660 provides the stored information to the defect type determination unit 1630, so that the defect type determination unit 1630 can determine the type of the defect.

The defect determining apparatus 120 illustrated in FIG. 16 includes a communication unit 1610 and a memory unit 1660, but is not necessarily limited thereto. As described above, when the defect detecting apparatus 110 and the defect determining apparatus 120 are implemented in the form of a module in one apparatus, the defect determining apparatus 120 is separated from the defect detecting apparatus 110 without a separate communication unit. The image can be received. In addition, a memory unit in one device may be implemented, and the memory unit may be implemented in a form in which the defect detection apparatus 110 and the defect determination apparatus 120 share the memory unit.

18 is a diagram illustrating a method of determining a type of a defect by a defect type determining unit according to an embodiment of the present invention.

The defect type determination unit 1630 determines a type of a defect in the target pixel by using a mask stored in the memory unit 1660. The defect type determiner 1630 places masks 1810 and 1815 on each target pixel 1720 and 1725 in which the defect 1710 exists. The defect type determination unit 1630 determines whether the defect area in each target pixel 1720 and 1725 is located with the mask area by determining the type of the defect. Referring to FIG. 18, since the region of the defect 1710 is in contact with the regions of each of the masks 1810 and 1815, the defect type determination unit 1630 identifies a defect in each target pixel 1720 and 1725 as a third defect. Classify as

19 is a diagram illustrating a method for analyzing defects in detail according to an embodiment of the present invention.

There is a possibility that some defects are detected to be smaller than the original shape due to blur or failure of noise removal in the defect detection apparatus 110. In this case, there exists a case where the defect which should be determined as the third defect is not determined as the third defect because the region of the defect does not contact the region of the mask. The above-described example is shown in Fig. 19A.

Referring to FIG. 19A, the defect 1710 may not be determined as a third defect because the defect 1710 does not contact the mask 1810 according to the aforementioned various reasons.

In order to solve this problem, when the defect is located very close to the mask, the defect type determination unit 1630 expands the area by a predetermined ratio. The preset ratio may be set respectively according to the possibility that the area of the defect is detected small. The defect type determination unit 1630 expands an area by a preset ratio and determines whether the defect corresponds to a third defect. As such, the defect type determination unit 1630 may derive an accurate determination result of the defect type by analyzing the defect in more detail in some cases.

20 is a diagram illustrating a method for analyzing a second type of defect according to an embodiment of the present invention.

The defect in the substrate is present only within a particular target pixel, where there may be a fourth defect in contact with the mask of the neighboring target pixel. The defect type determination unit 1630 determines the fourth defect as follows.

The defect type determiner 1630 determines the type of the defect using the mask 1810 with respect to the first target pixel 1720 having the defect. If the defect 1710 exists only in the first target pixel 1720 and is disposed on one side of the first target pixel 1720, the defect type is determined because there is a possibility that the defect is determined to be the fourth defect. The unit 1630 does not directly determine the third defect but additionally analyzes the type of the defect.

The defect type determination unit 1630 arranges the mask 1815 in the neighboring pixel 1725 in the direction in which the defect 1710 is disposed in the first target pixel 1720, so that the area of the defect 1710 is masked 1815. Determine if it is in contact with the area. When the defect 1710 is in contact with the mask 1815 of the neighboring pixel, the defect type determination unit 1630 makes the defect 1710 a fourth defect, otherwise, the defect type determination unit 1630 determines the defect 1710. ) Is determined as a third defect. Accordingly, the defect type determination unit 1630 can classify various types of defects in detail and efficiently.

21 is a diagram illustrating a method of analyzing a location of a defect according to an embodiment of the present invention.

Referring to FIG. 21A, the defect location determining unit 1640 determines a location of a defect by comparing a color of the subtraction image 710 with a color of a reference image. The subtraction image 710 has a different color depending on which layer within the pixel the defect is located. Using this characteristic, the defect location determiner 1640 determines which layer in the pixel the defect is located in using the color of the defect area in the subtraction image 710. The defect position determiner 1640 generates the image 2140 of the mask area of the reference image by using the reference image 2120 and the binarization mask 2130 stored in the memory 1660. The defect location determiner 1640 compares the color of the defect area in the subtraction image 710 with the color of the image 2140 of the mask area of the reference image to determine the similarity of the color. The defect position determiner 1640 determines a mask region similar to the color of the defect region and determines the position of the defect region. Accordingly, the defect location determiner 1640 may determine which layer the defect area is located on and from which layer to which layer.

22 is a diagram illustrating a method of analyzing a region of a defect, according to an embodiment of the present invention.

The defect type determination unit 1630 determines whether the determined defects are connected to each other.

Referring to FIG. 22, there may be a defect 1710a occurring in a specific region 810 (eg, an emission line) and a defect 1710b occurring in another specific region 820 (eg, a capacitor). As described above, the case where the defects are present and the case where the defects are connected to each other require different complementary methods, and therefore, each case should be distinguished from each other. The defect type determination unit 1630 may separately determine whether each defect is connected to each other separately from the process of determining the type of the defect. Accordingly, the defect type determiner 1630 may determine whether the defects exist and the cases where the defects are connected to each other.

FIG. 23 is a flowchart illustrating a method of determining a defect detected in a substrate by a defect determining apparatus according to an embodiment of the present invention.

The defect determination apparatus 120 receives a subtraction image in which a defect exists and a binarized image of the subtraction image from the defect detection apparatus 110 (S2310).

The defect determining apparatus 120 selects a target pixel for analyzing a defect (S2320).

The defect determining apparatus 120 determines the type of the defect in the target pixel (S2330).

The defect determining apparatus 120 determines the position of the defect in which layer the defect is present in the target pixel (S2340).

The defect determining apparatus 120 determines the type of the defect (S2350).

24 is a diagram illustrating a configuration of a repair apparatus according to an embodiment of the present invention.

Referring to FIG. 24, the repair apparatus 130 according to an embodiment of the present invention includes a communication unit 2410, a memory unit 2420, a controller 2430, a repair unit 2440, and a defect detection unit 2450.

The communication unit 2410 receives the determined defect information from the defect determining apparatus 120. The communication unit 2410 is connected to the defect determining apparatus 120 by wire or wireless communication, and receives information of the defect including the type, the location, and the type of the defect from the defect determining apparatus 120.

The memory unit 2420 stores a reference image, information on each defect, and a repair method corresponding thereto.

The memory unit 2420 stores the reference image, so that when the defect is to be repaired, the memory unit 2420 may finally decide in what form the repair should be performed. When storing the reference image, the memory unit 2420 may separately store each layer in the reference image. Accordingly, when the controller 2430 analyzes the defect information, it is possible to more easily identify the position of the defect.

The memory unit 2420 stores information about all types of defects that may occur in the substrate and a repair method corresponding to each defect. The defects may occur at various locations as the types of the first to fourth defects, and may variously occur as residual defects, open defects, hole defects, dark defects, or seed defects. In order to repair various defects generated in this manner, the memory unit 2420 stores a repair method corresponding to each defect. Repair methods include Digital Micromirror Device (DMD), Cutting, Laser Chemical Vapor Deposition (LCVD) or laser irradiation. The DMD grasps the position of the defect received by the communication unit 2410 and pattern-processes the defect and the region in the vicinity where the defect exists in accordance with the reference image in the vicinity where the defect exists. Mainly, when the defect is the fourth defect or the seed type defect, the DMD type repair may be performed. The cutting locates the defect received by the communication unit 2410 and cuts and removes only the defect. Cutting is mainly used when the defects are the first to third defects, the dark defects or the residual defects, when the defects are finely removed. The LCVD detects the position of the defect received by the communication unit 2410 and chemically deposits the image according to the reference image to compensate for the defect. This is mainly used when the defect is an open defect or a hole defect. Laser irradiation is mainly used for repairing hole-like defects, in which a laser is irradiated to a specific portion of the substrate to form a hole. The hole type defect may be repaired by performing LCVD on a corresponding area after laser irradiation. The memory unit 2420 stores defect information and a repair method corresponding thereto to repair the defect.

The controller 2430 analyzes the information of the defect received from the defect determining apparatus 120, selects an appropriate repair method, and controls the repair unit 2440 to repair the defect using the selected repair method.

The controller 2430 analyzes the information on the defect received by the communication unit 2410. The control unit 2430 analyzes at which position the defect occurred, what type of defect occurred, and what kind of defect occurred.

The controller 2430 selects an appropriate repair method based on the analyzed information. The controller 2430 compares the analyzed defect information with the reference image stored in the memory 2420 to determine how to repair defects generated in the substrate and how to repair them, and based on the determined information, the memory unit 2420. ) Select the appropriate repair method among the saved repair methods in. The controller 2430 transmits repair information, such as a selected repair position, a repair type, and a repair method, to the repair unit 2440.

The repair unit 2440 repairs a defect in the substrate under the control of the controller 2430. The repair unit 2440 performs the repair according to repair information received from the controller 2430, such as a repair position, a repair type, and a repair method. If the defect is the fourth defect or the seed type defect (or residual type defect), the repair unit 2440 repairs the portion where the defect is generated in the DMD method as in the reference image. When the defects are the first to third defects, the dark defects, or the residual defects, the repair unit 2440 repairs a portion where the defects are generated in a cutting manner as in the reference image. If the defect is an open defect, the repair unit 2440 repairs a portion in which the pattern is not normally formed by the LCVD method as in the reference image. In addition, when the defect is a hole type defect, the repair unit 2440 may form a hole at an appropriate position such as a reference image by performing laser irradiation or laser irradiation together with the LCVD method.

The defect detector 2450 redetects the defect in the substrate to reconfirm whether the defect in the substrate repaired by the repair unit 2440 is completely repaired. The repair of the defect is performed by the repair unit 2440, but there is a possibility that a sufficient repair has not been performed, and there is a possibility that the repair is performed at a position other than the defect. In this case, the defects in the substrate remain, so the repair must be performed again. The defect detection unit 2450 checks whether the repair is sufficiently performed to completely repair the defect in the substrate. The defect detector 2450 may include the same configuration as that of the defect detection apparatus 110, or may include only a configuration for generating an image of the substrate and detecting a defect through image contrast among the components in the defect detection apparatus 110.

25 is a flowchart illustrating a method of repairing a defect of a substrate by a repair apparatus according to an embodiment of the present invention.

The repair apparatus 130 receives the defect information from the defect determination apparatus 120 (S2510). Information on defects includes the type, type and location of the defect.

The repair apparatus 130 selects a repair method according to the defect information (S2520). The repair apparatus 130 analyzes the information of the defect received from the defect determining apparatus 120. The repair apparatus 130 compares the analyzed defect information with the reference image to determine how to repair defects generated on the substrate and how to repair them, and among the repair methods stored in the memory unit 2420 based on the determined contents. Choose the appropriate repair method.

The repair apparatus 130 repairs the defect according to the selected repair method (S2530). The repair apparatus 130 repairs a defect according to repair information such as a repair position, a repair type, and a repair method.

The repair apparatus 130 checks again whether the defect is completely repaired (S2540).

15, 23 and 25 are described as sequentially executing each process, which is merely illustrative of the technical idea of an embodiment of the present invention. In other words, a person of ordinary skill in the art to which an embodiment of the present invention belongs may change the order of the processes described in each drawing or execute one or more of the processes without departing from the essential characteristics of the embodiment of the present invention. 15 and 23 and 25 are not limited to the time series since the processes may be applied in various ways.

15, 23, and 25 may be embodied as computer readable codes on a computer readable recording medium. The computer-readable recording medium includes all kinds of recording devices in which data that can be read by a computer system is stored. That is, the computer-readable recording medium may be a magnetic storage medium (for example, a ROM, a floppy disk, a hard disk, etc.), an optical reading medium (for example, a CD-ROM, DVD, etc.) and a carrier wave (for example, the Internet Storage medium). The computer readable recording medium can also be distributed over network coupled computer systems so that the computer readable code is stored and executed in a distributed fashion.

The above description is merely illustrative of the technical idea of the present embodiment, and those skilled in the art to which the present embodiment belongs may make various modifications and changes without departing from the essential characteristics of the present embodiment. Therefore, the present embodiments are not intended to limit the technical idea of the present embodiment but to describe the present invention, and the scope of the technical idea of the present embodiment is not limited by these embodiments. The scope of protection of the present embodiment should be interpreted by the following claims, and all technical ideas within the scope equivalent thereto should be construed as being included in the scope of the present embodiment.

100: auto repair system
110: defect detection device
120: defect determination device
130: repair device
140: control unit
210: substrate transfer portion
220: image generating unit
230: unit pixel recognition unit
240: memory
250: preprocessing unit
260: image contrast
270: defect detection unit
280: control unit
290: communication unit
310, 1110, 1120, 1130: reference image of unit pixel
320: substrate image
325: image of unit pixels
410, 420: line profile
510: deduction profile
710: deduction image
910 binarization image of subtraction image
1610: communication
1620: target pixel selector
1630: Defect Type Determination Unit
1640: defect location determination unit
1650: defect type determination unit
1660: memory
1710: Defect
1720, 1725: target pixel
1810, 1815: mask
2120: reference image
2130: binarization mask
2140: Image of mask area of base image

Claims (6)

Defects are generated in each unit pixel by generating an image of a substrate to be inspected, recognizing unit pixels included in the substrate from the image of the substrate, and comparing a reference image of a previously stored unit pixel with an image of each generated unit pixel. A defect detection device for detecting whether or not it is;
A defect determination device for receiving an image of a pixel in which a defect exists, selecting a target pixel for analyzing a defect in the received image, and determining information of a defect existing in the target pixel; And
A repair apparatus for selecting a repair method corresponding to the defect information based on the defect information determined by the defect determination apparatus, and repairing the defect according to the selected repair method;
The defect detecting apparatus may include a substrate transfer unit for transferring the substrate in a predetermined direction, an image generator for generating an image of the substrate, a unit pixel recognition unit for recognizing unit pixels included in the substrate from the image of the substrate, A memory unit for storing a reference image, an image contrast unit for contrasting an image of each generated unit pixel with a reference image of a unit pixel stored in the memory unit, and a defect for detecting whether a defect exists in each unit pixel according to a contrast result A detection unit, a control unit for controlling each component in the defect detection device, and a preprocessing unit for converting a direction of the long axis of the reference image,
The unit pixel recognition unit generates a line profile of the reference image of the unit pixel and the image of the substrate, and generates a subtraction line profile by subtracting each generated line profile, and the predetermined subtraction line profile is less than or equal to a predetermined value. Recognize the point having as a boundary between unit pixels,
Before the image contrast unit collates the image of the unit pixel and the reference image of the unit pixel, when the long axes of the reference image of the unit pixel and the image of the unit pixel are different directions, the long axes of the respective images are the same direction. The preprocessing unit converts the direction of the reference image of the unit pixel to be,
The controller replaces the reference image of the unit pixel stored in the memory unit with one of the image of each unit pixel generated by the image generator for each predetermined area in order to improve the accuracy of defect detection.
The replaced unit pixel image is an auto repair system, wherein the image of the unit pixel having the smallest difference in color, brightness, and contrast from the reference image within a predetermined area. The method of claim 1,
The defect information is
The type of defect relating to how the defect present in the target pixel exists in the target pixel and the position of the defect regarding which position of the layer the defect in the target pixel exists in. Repair system. The method of claim 1,
The repair method,
An auto repair system comprising some or all of a digital micromirror device (DMD), cutting, laser chemical vapor deposition (LCVD), and laser irradiation.

delete delete delete

Images