WO2011114449A1 - Tft array inspection method and tft array inspection device - Google Patents

Tft array inspection method and tft array inspection device Download PDF

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WO2011114449A1
WO2011114449A1 PCT/JP2010/054523 JP2010054523W WO2011114449A1 WO 2011114449 A1 WO2011114449 A1 WO 2011114449A1 JP 2010054523 W JP2010054523 W JP 2010054523W WO 2011114449 A1 WO2011114449 A1 WO 2011114449A1
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shape
registered
defect
shapes
target shape
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PCT/JP2010/054523
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French (fr)
Japanese (ja)
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正道 永井
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株式会社島津製作所
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Priority to PCT/JP2010/054523 priority Critical patent/WO2011114449A1/en
Priority to JP2012505357A priority patent/JP5408333B2/en
Priority to CN201080065328.1A priority patent/CN102803940B/en
Publication of WO2011114449A1 publication Critical patent/WO2011114449A1/en

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    • G—PHYSICS
    • G02—OPTICS
    • G02F—OPTICAL DEVICES OR ARRANGEMENTS FOR THE CONTROL OF LIGHT BY MODIFICATION OF THE OPTICAL PROPERTIES OF THE MEDIA OF THE ELEMENTS INVOLVED THEREIN; NON-LINEAR OPTICS; FREQUENCY-CHANGING OF LIGHT; OPTICAL LOGIC ELEMENTS; OPTICAL ANALOGUE/DIGITAL CONVERTERS
    • G02F1/00—Devices or arrangements for the control of the intensity, colour, phase, polarisation or direction of light arriving from an independent light source, e.g. switching, gating or modulating; Non-linear optics
    • G02F1/01—Devices or arrangements for the control of the intensity, colour, phase, polarisation or direction of light arriving from an independent light source, e.g. switching, gating or modulating; Non-linear optics for the control of the intensity, phase, polarisation or colour 
    • G02F1/13—Devices or arrangements for the control of the intensity, colour, phase, polarisation or direction of light arriving from an independent light source, e.g. switching, gating or modulating; Non-linear optics for the control of the intensity, phase, polarisation or colour  based on liquid crystals, e.g. single liquid crystal display cells
    • G02F1/133—Constructional arrangements; Operation of liquid crystal cells; Circuit arrangements
    • G02F1/136—Liquid crystal cells structurally associated with a semi-conducting layer or substrate, e.g. cells forming part of an integrated circuit
    • G02F1/1362—Active matrix addressed cells
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N23/00—Investigating or analysing materials by the use of wave or particle radiation, e.g. X-rays or neutrons, not covered by groups G01N3/00 – G01N17/00, G01N21/00 or G01N22/00
    • G01N23/22—Investigating or analysing materials by the use of wave or particle radiation, e.g. X-rays or neutrons, not covered by groups G01N3/00 – G01N17/00, G01N21/00 or G01N22/00 by measuring secondary emission from the material
    • G01N23/225—Investigating or analysing materials by the use of wave or particle radiation, e.g. X-rays or neutrons, not covered by groups G01N3/00 – G01N17/00, G01N21/00 or G01N22/00 by measuring secondary emission from the material using electron or ion
    • G01N23/2255—Investigating or analysing materials by the use of wave or particle radiation, e.g. X-rays or neutrons, not covered by groups G01N3/00 – G01N17/00, G01N21/00 or G01N22/00 by measuring secondary emission from the material using electron or ion using incident ion beams, e.g. proton beams
    • G—PHYSICS
    • G02—OPTICS
    • G02F—OPTICAL DEVICES OR ARRANGEMENTS FOR THE CONTROL OF LIGHT BY MODIFICATION OF THE OPTICAL PROPERTIES OF THE MEDIA OF THE ELEMENTS INVOLVED THEREIN; NON-LINEAR OPTICS; FREQUENCY-CHANGING OF LIGHT; OPTICAL LOGIC ELEMENTS; OPTICAL ANALOGUE/DIGITAL CONVERTERS
    • G02F1/00—Devices or arrangements for the control of the intensity, colour, phase, polarisation or direction of light arriving from an independent light source, e.g. switching, gating or modulating; Non-linear optics
    • G02F1/01—Devices or arrangements for the control of the intensity, colour, phase, polarisation or direction of light arriving from an independent light source, e.g. switching, gating or modulating; Non-linear optics for the control of the intensity, phase, polarisation or colour 
    • G02F1/13—Devices or arrangements for the control of the intensity, colour, phase, polarisation or direction of light arriving from an independent light source, e.g. switching, gating or modulating; Non-linear optics for the control of the intensity, phase, polarisation or colour  based on liquid crystals, e.g. single liquid crystal display cells
    • G02F1/133—Constructional arrangements; Operation of liquid crystal cells; Circuit arrangements
    • G02F1/136—Liquid crystal cells structurally associated with a semi-conducting layer or substrate, e.g. cells forming part of an integrated circuit
    • G02F1/1362—Active matrix addressed cells
    • G02F1/136254—Checking; Testing

Definitions

  • the present invention relates to a TFT array inspection for inspecting an array of a TFT substrate such as a liquid crystal substrate, and more particularly to data processing of detection intensity used for detecting a defect in the TFT array.
  • an optical image obtained by optical imaging or a charged beam such as an electron beam or an ion beam is used as an image obtained by imaging a substrate such as a liquid crystal substrate.
  • a scanning image obtained by two-dimensionally scanning the substrate on the substrate can be used.
  • Patent Documents 1 and 2 In the manufacturing process of the TFT array substrate used in the TFT display device, an inspection is performed to check whether the manufactured TFT array substrate is driven correctly (Patent Documents 1 and 2).
  • an inspection signal is applied to an array of substrates to be inspected to bring the array into a predetermined potential state, and the substrate is scanned by two-dimensionally irradiating a charged beam such as an electron beam or an ion beam.
  • An array inspection apparatus that inspects an array of TFTs based on a scanning image obtained is known.
  • TFT array inspection for example, secondary electrons emitted by irradiation with an electron beam are converted into an analog signal by a photomultiplier or the like and detected, and an array defect is determined based on the signal intensity of the detection signal.
  • the array and pixels of the TFT substrate are formed correspondingly, and a specific pixel can be driven by applying a drive signal to the array.
  • a drive signal of a predetermined pattern is applied to the array to drive each pixel of the panel formed in the substrate with a predetermined pattern, and these pixels are irradiated with an electron beam and emitted from the irradiation point. Secondary electrons detected. A detection signal is acquired from each pixel in the panel by performing this electron beam irradiation in the panel.
  • each pixel is irradiated with, for example, 4 ⁇ 4 points or 4 ⁇ 3 points of a charged beam, and the irradiation point is set as a sampling point.
  • the signal intensity for detecting the defect of the array corresponding to the pixel is calculated using the detected signal.
  • FIG. 14 is a schematic diagram for explaining a conventional sampling example.
  • a total of 16 charged beams of 4 ⁇ 4 points are irradiated to one pixel, and each irradiation point is set as a sampling point, and a detection signal detected at each sampling point is used to detect a defect.
  • the detection signal is acquired.
  • a voltage pattern inspection signal is applied to each pixel by generating different potentials between adjacent pixels.
  • the signal intensity for defect detection is calculated from the detection signal of 4 ⁇ 4 points or 4 ⁇ 3 sampling points in the pixel, and this signal intensity is compared with a predetermined threshold value.
  • detection signals are acquired for a plurality of sampling points such as 4 ⁇ 4 points or 4 ⁇ 3 points.
  • Defect determination is performed in units of pixels. By detecting a defective pixel, it is possible to detect that there is a defect such as a short circuit or an open in the array portion that drives the pixel and perform an array inspection.
  • the determination of the defect type of the array can be changed by changing the voltage pattern of each pixel on the panel.
  • the voltage pattern of each pixel can be changed, for example, by changing the voltage pattern applied to the vertical or horizontal array.
  • Defect determination in units of pixels is performed by calculating the signal intensity for defect determination based on a plurality of detection signals detected at the sampling points of each pixel, and the threshold for defect determination in which this signal intensity is determined in advance. It is done by comparing with the value.
  • the detection signal detected at the sampling point of each pixel may contain noise. This noise component shifts the signal intensity of the detection signal from the original value. For this reason, if defect determination is performed based on the signal strength of the detection signal including noise, there is a risk of erroneous detection such as determining a normal pixel as a defective pixel or determining a defective pixel as a normal pixel.
  • an object of the present invention is to solve the above-described problems and to perform an array inspection by detecting defective pixels without being affected by noise added to a detection signal.
  • the inventors of the present application show that a defect shape peculiar to the defect type caused by the defect and a noise shape due to noise appear in the signal image obtained by scanning the charged beam on the panel. It was found that they can be distinguished by their shapes.
  • the present invention detects a defect shape by distinguishing it from a noise shape from shapes appearing in a signal image, and detects the defect pixel and an array corresponding to the defect pixel by detecting the defect shape.
  • the array is inspected by detecting defects.
  • the present invention applies an inspection signal of a predetermined voltage to a panel of a TFT substrate to drive the array, scans the panel by irradiating a charged beam, and based on a detection signal detected by the charged beam scanning, the TFT
  • This is a TFT array inspection for inspecting an array of substrates, and can be an aspect of an array inspection method and an aspect of an array inspection apparatus.
  • the array inspection method includes a detection step of detecting a signal intensity at a sampling point on a panel by irradiation with a charged beam, and binarizing the signal intensity of the sampling point detected in the detection step to obtain a binary image.
  • the binarization step to be obtained and the shape included in the binarized image obtained in the binarization step are set as the shape to be collated, and the collation is performed by comparing the shape of the collation target shape with the registered shape registered in advance.
  • Discriminator Preparative provided to detect the array corresponding to the defect and determine pixels in the defect determination process as a defect array.
  • the aspect of the array inspection apparatus of the present invention includes a detection unit that detects the signal intensity of a sampling point on a panel by irradiation of a charged beam, and a binarized image obtained by binarizing the signal intensity of the sampling point detected in the detection process.
  • the binarization unit to be obtained and the shape included in the binarized image obtained by the binarization unit are set as the shape to be collated, and the collation is performed by comparing the shape of the collation target shape with the registered shape registered in advance.
  • an electron beam is used as a charged beam, the electron beam is irradiated onto the panel, secondary electrons emitted from a sampling point on the panel are detected, and a detection signal of the secondary electron is detected.
  • Detect signal strength The signal strength obtained in the detection process varies depending on the voltage of the sampling point on the panel, and if the pixel is defective due to an array defect, the signal strength obtained at the sampling point on this pixel is normal pixel. Therefore, the normal pixel and the defective pixel are discriminated based on the signal intensity.
  • the binarization step and the binarization unit binarize the signal by comparing the signal strength at the sampling point with a predetermined threshold value and associating the binary value with the position corresponding to the sampling point according to the comparison result. Form an image.
  • the signal intensity obtained in the detection step and the detection unit has an intensity distribution corresponding to each state in the normal pixel and the defective pixel, and the signal intensity includes variations. For this reason, when a signal image is formed with this signal intensity, the shape changes due to variations in the signal intensity, so the shape cannot be specified, and it is difficult to distinguish between normal and defective pixels based on the shape. Become. Therefore, in the present invention, by binarizing the signal intensity of the detection signal, it is possible to avoid the indefinite shape due to variations in signal intensity, and to distinguish between a normal pixel and a defective pixel based on the shape.
  • the collation process and the collation device have a plurality of registered shapes, and compare the shape with the shape to be collated for each registered shape selected from the plurality of registered shapes.
  • the shape due to the defect appearing on the signal image differs depending on the type of defect and the position of the defect on the pixel, and the shape can be obtained in advance.
  • the shape due to this defect is obtained in advance and prepared as a registered shape.
  • the registered shape is binarized data, and is compared with the target shape of the binarized image obtained in the binarization process.
  • a selection process for selecting a registered shape from a plurality of registered shapes and a shape comparison process for comparing the shape of the registered shape selected in this selection process with the matching target shape. The process is repeated until the defect is determined as a defect.
  • the collation between the shape to be collated and the registered shape can be performed by binarized image data processing, and various processing modes can be used.
  • the image is superimposed on the data while moving the window with respect to the binarized image, and whether or not the data of the binarized image in this window matches the shape of the window.
  • Data processing for discrimination data processing for discrimination by passing the binary image data through a matching filter corresponding to the registered shape, a square matrix corresponding to the matching target shape and a square matrix corresponding to the registered shape are formed, Data processing that determines the product of the inverse matrix of the square matrix and the other square matrix and determines whether the product is a unit matrix can be used.
  • the present invention it is possible to detect a defective pixel and perform an array inspection without being affected by noise added to the detection signal.
  • FIG. 1 the flowchart for explaining the TFT array inspection step of the present invention in FIG. 1 and the steps until forming the signal image of the TFT array inspection of the present invention in FIG. 3 and 4 are flowcharts for explaining the binarized image of the TFT array inspection of the present invention
  • FIG. 5 is an explanatory diagram for explaining the binarized image of the TFT array inspection of the present invention. Description will be made with reference to FIGS. 6 and 7 for explaining the collation of the TFT array inspection of the present invention, and FIGS. 8 to 10 for explaining the collation processing example of the TFT array inspection of the present invention. .
  • the detection step (S1) for detecting the signal intensity at the sampling point on the panel by irradiation of the charged beam and the signal intensity at the sampling point detected in the detection step (S1) are binarized to 2
  • an inspection signal of a predetermined voltage is applied to the TFT substrate panel to drive the array, and scanning is performed by irradiating the panel with a charged beam, and a signal emitted from the irradiation point is detected by this charged beam scanning.
  • a secondary electron detection signal is detected.
  • the irradiation point of the charged beam corresponds to a sampling point for detecting the detection signal.
  • FIG. 2 (a) schematically shows sampling points.
  • the sampling point is a point where a detection signal is obtained, and corresponds to a point where a charged beam is irradiated on the panel (S2).
  • the position of the sampling point obtained by scanning is unknown in the positional relationship with the pixel formed on the panel, and if it remains as it is, the sampling point corresponding to the pixel cannot be specified, and the array defect can be detected. Can not.
  • the present invention obtains sampling points included in each pixel by associating the sampling points with the pixels of the panel in order to identify the relationship of the sampling points to the pixels.
  • the position of the sampling point is a position on the panel to be inspected, and this correspondence can be obtained from the position on the stage that supports the substrate on which the panel is formed and the irradiation position of the charged beam.
  • a predetermined voltage pattern in the pixel By forming a predetermined voltage pattern in the pixel, detecting the signal intensity between adjacent points, obtaining a boundary between the pixels based on the difference in signal intensity, and obtaining a sampling point correspondence relationship with the pixel based on the boundary. it can. Thereby, the correspondence between the sampling points and the pixels is obtained, and the pixels are identified in the detection data.
  • FIG. 2B shows the correspondence between sampling points and pixels (S3).
  • the detection data can form a signal image from its position and signal intensity.
  • this signal intensity has an intensity distribution corresponding to each state in the normal pixel and the defective pixel, and the signal intensity includes variations.
  • FIG. 2C schematically shows the relationship between the pixel and the signal image obtained from the signal intensity of the detection signal at the sampling point.
  • Binary image is formed from signal image by binarization process.
  • the binarization process is performed by comparing the signal intensity at the sampling point with a predetermined threshold value. Two values are determined according to the comparison result, and are associated with the positions corresponding to the sampling points. Thereby, a binarized image is formed.
  • FIG. 3 is a diagram for explaining binarization. Pixel defects appear in two ways in the pixel voltage. One aspect is when the defective pixel voltage appears at a lower voltage than the normal pixel voltage and is called a black defect. The other aspect is when the defective pixel voltage appears at a higher voltage than the normal pixel voltage, which is called a white defect.
  • Fig. 3 (a) shows binarization in the case of a black defect.
  • the defect strength max is determined in advance as a threshold value for binarizing the signal strength, the position of the signal image whose signal strength is lower than the defect strength max is associated with the defect, and the signal strength is the defect strength max. The signal image position higher than that is normally associated.
  • FIG. 3B shows binarization in the case of a white defect.
  • a defect intensity min ( ⁇ defect intensity max) is determined in advance as a threshold value for binarizing the signal intensity, and the position of the signal image whose signal intensity is higher than the defect intensity min is associated with the defect. The position of the signal image whose signal intensity is lower than the defect intensity min is normally associated.
  • FIG. 4 is a flowchart showing the black defect binarization procedure.
  • the signal intensity at the sampling point stored in S2 is read (S4a), and the read signal intensity is compared with the defect intensity max which is the threshold value of the black defect (S4b).
  • the signal intensity When the signal intensity is larger than the defect intensity max, the signal intensity is assumed to be a normal level, and a value representing a normal pixel is set at the position of the signal image corresponding to the sampling point (S4c). On the other hand, when the signal intensity is equal to or lower than the defect intensity max, the signal intensity is assumed to be the defect level, and a value representing the defective pixel is set at the position of the signal image corresponding to the sampling point. Values set in correspondence with normal pixels and defective pixels by binarization can be arbitrarily determined, for example, “0” and “1” (S4d).
  • FIG. 5 is a flowchart showing the binarization procedure for white defects.
  • the signal intensity at the sampling point stored in S2 is read (S4A), and the read signal intensity is compared with the defect intensity min, which is the threshold value for white defects (S4B).
  • the signal intensity is assumed to be the defect level, and a value representing the defective pixel is set at the position of the signal image corresponding to the sampling point (S4C).
  • the signal intensity is assumed to be a normal level, and a value representing a normal pixel is set at the position of the signal image corresponding to the sampling point.
  • Values set in correspondence with normal pixels and defective pixels by binarization can be arbitrarily determined, for example, “0” and “1” (S4D).
  • ⁇ S4A to S4D processing is performed on the signal intensity at all sampling points to form a binary signal image from the signal image (S4E).
  • the binarized data can be, for example, the value set in the binarization process and the position in the pixel (S5).
  • the collation target shape appearing in the binarized image is compared with the registered shape, and it is determined whether or not the registered shape is included in the collation target shape.
  • the shape to be collated is a shape formed by a set of points determined as a defect level by binarization processing, a shape formed by a set of points caused by defects, or a shape formed by a set of points due to noise Is included. If it is determined that the registered shape is included in the verification target shape, the pixel is determined as a defective pixel.
  • the shape in the binary image that appears in the defective pixel is obtained in advance.
  • This registered shape can be configured by recording data representing the shape when the collating process is performed by software, and by element arrangement representing the shape when the collating process is performed by hardware.
  • FIG. 6A and FIG. 7A show an example of collation.
  • FIG. 6A and FIG. 7A show an example of a binarized image of a black defect, and a white portion in the figure indicates a normal level and a black portion indicates a defect level. Since the defect level includes a portion due to a defect and a portion due to noise, the shape due to the defect is discriminated regardless of noise by collating the shape to be collated with the registered shape.
  • the pixels shown in FIGS. 6B to 6G show an example of matching between the matching target shape in the binarized image and the registered shape.
  • the registered shape is not included in the binarized image, so these pixels are normal. Discriminated as a pixel.
  • the pixel matching shown in FIG. 6F since it is determined that the registered shape is included in the binarized image, this pixel is determined as a defective pixel.
  • FIG. 7 shows an example in which after a defective pixel is detected by collation using one registered shape shown in FIG. 6, collation is performed using another registered shape.
  • the pixels shown in FIGS. 7B to 7G show an example of matching between the matching target shape in the binarized image and the registered shape.
  • the pixel matching shown in FIGS. 7B to 7E since the registered shape is not included in the binarized image, these pixels are determined as normal pixels. Since the registered shape of the pixel shown in FIG. 7 (f) is detected by the above-described pixel matching in FIG. 6 (f), the matching of the registered shape here is unnecessary and is omitted.
  • the collation shown in FIG. 7G it is determined that a registered shape is included in the binarized image, and this pixel is determined as a defective pixel.
  • the matching between the matching target shape and the registered shape can be performed by data processing of a binarized image, and various processing modes can be used.
  • FIG. 8 shows that the registered shape is a window and is superimposed on the data while moving the window with respect to the binarized image, and whether the data of the binarized image in this window matches the shape of the window. This shows an example of data processing for determining whether or not.
  • FIG. 8A shows an example of a binarized image of one pixel, where a white part in the figure indicates a normal level and a black part indicates a defect level.
  • FIG. 8B shows an example of a registered shape. In this collation example, the registration shape is used as a window to overlap the binarized image on the data, and collation is performed by determining whether the data of the binarized image in the window matches the shape of the window.
  • FIGS. 8C to 8H schematically show an example of superimposing the binarized image while sequentially shifting the windows. In the superposition shown in FIG. 8C and FIG. 8E to FIG.
  • the superimposition of the binarized image, the window, and the image can be performed by extracting data corresponding to the registered shape window from the binarized image of the pixels and comparing the binary values of the corresponding pixel positions. it can.
  • FIG. 9 shows an example of data processing that is determined by passing binarized image data through a matching filter corresponding to a registered shape.
  • the configuration of the matching filter shown in FIG. 9 forms a square matrix including a registered shape, and is configured by a delay element, an AND circuit, and an OR circuit corresponding to this square matrix.
  • delay elements are arranged between the values of the respective signals, and among the outputs of the respective delay elements, "1"
  • An AND circuit is arranged at the output of the delay element corresponding to ", and an AND circuit is arranged at the output of all AND circuits included in the registered shape. “1” is input to the other input terminal of the AND circuit.
  • square matrices P, Q, and R are formed for the binary signal of the registered shape. Elements other than the binary signal of the registered shape in the square matrix are indicated by “x”.
  • the AND circuits 200 to 203 are formed corresponding to “1” of the binarized signals of the square matrix P, and the outputs of the AND circuits 200 to 203 are input to the AND circuit 204.
  • AND circuits 300 to 303 are formed corresponding to “1” in the binarized signal of the square matrix Q, the outputs of the AND circuits 300 to 303 are input to the AND circuit 304, and the binary of the square matrix R AND circuits 400 to 403 are formed corresponding to “1” of the digitized signals, the outputs of the AND circuits 400 to 403 are input to the AND circuit 404, and the outputs are input to the AND circuits 204, 304, 404. To do.
  • an output is obtained from the OR circuit 500 when the registered shape is included in the shape to be matched.
  • a signal is output only from the AND circuit 304 corresponding to the square matrix Q, and an output is obtained from the OR circuit 500.
  • a matching filter corresponding to a predetermined registered shape is configured by hardware, and defect determination is performed by sequentially inputting a binary signal of a binary image of each pixel. It can be carried out.
  • FIG. 10A shows an example of forming a square matrix corresponding to the shape to be collated
  • FIG. 10B shows an example of forming a square matrix corresponding to the registered shape.
  • the corresponding square matrix is 3 rows ⁇ 3 columns.
  • the square matrix A1 corresponding to this registered shape is formed by adding [000] to the third column.
  • defect determination is performed including the case where the element array of “0” is “1” in addition to the element array of “1” included in the registered shape. Therefore, in addition to the square matrix A1, square matrices A2, A3, and A4 obtained by inverting the element array “0” to “1” are also prepared.
  • a 3 ⁇ 3 square matrix is formed from the shape to be verified.
  • 3 ⁇ 3 square matrices B1 to B6 are formed from a 4 ⁇ 4 square matrix B formed from the matching target shape.
  • [000] is added to the third column to form a square matrix.
  • the square matrices A1 to A4 formed from the registered shapes are regular matrices, the inverse matrices A1 ⁇ 1 to A4 ⁇ 1 are formed, respectively, and the products of the square matrices B1 to B6 formed from the matching target shapes are obtained.
  • FIG. 10C shows the product of the square matrix B and the inverse matrix A ⁇ 1 of the square matrix A.
  • the product of the square matrix B and the inverse matrix A ⁇ 1 is a unit matrix, it indicates that the square matrix B and the square matrix A match. This indicates that the verification target shape matches the registered shape.
  • the product of the square matrix B and the inverse matrix A3 ⁇ 1 of the square matrix A3 becomes the unit matrix E, which indicates that the registered shape is included in the matching target shape.
  • FIG. 11 is a diagram for explaining a configuration example of an inspection apparatus for performing the TFT array inspection of the present invention.
  • a TFT substrate such as a liquid crystal substrate is irradiated with an electron beam, secondary electrons emitted from the TFT substrate are detected, and a signal image is formed from a detection signal of the secondary electrons.
  • the example of a structure which performs defect detection based on this is shown.
  • the substrate to be inspected is not limited to a liquid crystal substrate, and substrate scanning is not limited to an electron beam, and a charged beam such as an ion beam can be used.
  • the detection signal depends on the charged beam to be irradiated and is not limited to secondary electrons.
  • a TFT array inspection apparatus 1 includes a stage 2 on which a TFT substrate 100 such as a liquid crystal substrate is placed and can be conveyed in the XY directions, and an electron gun 3 disposed above the stage 2 and spaced from the stage 2 And a detector 4 for detecting secondary electrons emitted from a pixel (not shown) of the panel 101 of the TFT substrate 100.
  • the electron gun 3 and the detector 4 can be provided with a plurality of sets.
  • the stage drive control unit 6 controls the driving of the stage 2, and the electron beam scanning control unit 5 controls the scanning direction of the electron beam on the TFT substrate 100 by controlling the irradiation direction of the electron beam irradiated by the electron gun 3.
  • the signal processing unit 10 performs signal processing on the detection signal of the secondary electrons detected by the detector 4 and sends it to the defect detection unit 11.
  • the defect detection unit 11 detects a pixel defect based on the detection signal sent from the signal processing unit 10, and detects a defective pixel and a corresponding defect array based on the detection position.
  • the pixels and the array are formed on the panel of the TFT substrate, and each pixel is driven by applying a voltage to the array. Therefore, the defect detection of the pixel corresponds to the array inspection for the pixel.
  • the driving operation of each of the electron beam scanning control unit 5, the stage drive control unit 6, the signal processing unit 10, and the defect detection unit 11 is controlled by the control unit 7.
  • the control unit 7 has a function of performing control including the entire operation of the TFT array inspection apparatus 1, and can be configured by a CPU that performs these controls and a memory that stores a program that controls the CPU.
  • the stage 2 mounts the TFT substrate 100 and is movable in the X-axis direction and the Y-axis direction by the stage drive control unit 6, and the electron beam irradiated from the electron gun G is an electron beam scanning control unit 5. Can be swung in the X-axis direction or the Y-axis direction.
  • the stage drive control unit 6 and the electron beam scanning control unit 5 can scan the electron beam on the TFT substrate 100 and irradiate each pixel on the panel 101 of the TFT substrate 100 by single or cooperative operation.
  • FIG. 12 is a diagram for explaining a configuration example of the defect detection unit 20, and shows a configuration in which defect detection is performed by data processing by software.
  • the detection unit 21 forms a signal image from the detection signal sent from the signal processing unit 10, and stores the signal strength and detection position of the obtained signal image in the storage unit 25 as detection data 25a.
  • the binarization unit 22 binarizes the signal intensity at the sampling points detected by the detection unit 21 to obtain a binarized image.
  • the obtained binarized image data is stored in the storage unit 25 as binarized data 25b.
  • the collation unit 23 uses the shape included in the binarized image obtained by the binarization unit 22 as a collation target shape, and collates the collation target shape with a registered shape registered in advance. . In this verification, the binarized data 25b and the registered shape data 25c are read from the storage unit 25.
  • the defect discriminating unit 24 discriminates whether or not the registered shape is included in the verification target shape based on the verification result of the verification unit 23, and when at least one registered shape is included in the verification target shape. A pixel including the matching target shape is determined as a defect. On the other hand, if none of the registered shapes of all registered shapes is included in the matching target shape, the pixel including the matching target shape is determined to be normal.
  • the defect determination unit 24 detects an array corresponding to a pixel determined as a defect as a defect array.
  • defect detection based on a comparison between a matching target shape and a registered shape is not limited to determination within one pixel.
  • Defect determination can be performed in a plurality of adjacent pixels.
  • FIG. 13 shows an example in which defect determination is performed on a plurality of adjacent pixels.
  • FIG. 13A an example in which a defect occurs between two pixels adjacent in the horizontal direction, an example in which a defect occurs between two pixels adjacent in the vertical direction, and a horizontal direction and a vertical direction An example in which a defect occurs between four adjacent pixels is shown, and a registered shape is detected at these locations.
  • FIG. 13B shows an example in which a registered shape is detected when a defect occurs between two adjacent pixels in the horizontal direction.
  • two pixels adjacent in the horizontal direction are set as a determination range, and defect detection is performed by detecting a registered shape in the same manner as described above for a verification target shape within the determination range.
  • FIG. 13C shows an example in which a registered shape is detected when a defect occurs between two pixels adjacent in the vertical direction.
  • two pixels adjacent in the vertical direction are used as a determination range, and defect detection is performed by detecting a registered shape in the same manner as described above for a verification target shape within the determination range.
  • FIG. 13D shows an example in which a registered shape is detected when a defect occurs between four pixels adjacent in the horizontal and vertical directions.
  • four pixels adjacent in the horizontal direction and the vertical direction are set as the determination range, and the defect detection is performed by detecting the registered shape in the same manner as described above with respect to the verification target shape within the determination range.
  • the TFT substrate can be a liquid crystal substrate or an organic EL, and can be applied to a film forming apparatus for forming various semiconductor substrates in addition to a film forming apparatus for forming a liquid crystal substrate or an organic EL.

Abstract

Provided is an arrangement equipped with a detection process wherein signal strengths at sampling points on panels are detected by emitting charged beams; a binarization process wherein those signal strengths at sampling points which are detected in the detection process are binarized, thereby obtaining binarized images; a comparison process wherein shapes included in binarized images obtained in the binarization process are regarded as shapes to be compared, and wherein the aforementioned shapes to be compared are compared with preliminarily registered shapes, thereby performing comparisons; and a defect determination process wherein, from comparison results in the comparison process, it is determined whether registered shapes are included in compared shapes, wherein if at least one registered shape is included in the compared shapes, it is determined that the pixels which include the aforementioned compared shapes are defective, and wherein if none of the registered shapes whatsoever are included in the compared shapes, it is determined that the pixels which include the aforementioned compared shapes are normal. In the aforementioned arrangement, without being affected by noise contents added to detected signals, defects are detected, thereby conducting array inspection.

Description

ＴＦＴアレイ検査方法およびＴＦＴアレイ検査装置TFT array inspection method and TFT array inspection apparatus
　本発明は、液晶基板等のＴＦＴ基板のアレイを検査するＴＦＴアレイ検査に関し、特に、ＴＦＴアレイの欠陥検出に用いる検出強度のデータ処理に関する。 The present invention relates to a TFT array inspection for inspecting an array of a TFT substrate such as a liquid crystal substrate, and more particularly to data processing of detection intensity used for detecting a defect in the TFT array.
　液晶アレイ検査装置等のアレイ検査装置において、液晶基板等の基板上を撮像して得られる撮像画像として、光学的に撮像して得られる光学撮像画像、あるいは、電子ビームやイオンビーム等の荷電ビームを基板上で二次元的に走査して得られる走査画像を用いることができる。 In an array inspection apparatus such as a liquid crystal array inspection apparatus, an optical image obtained by optical imaging or a charged beam such as an electron beam or an ion beam is used as an image obtained by imaging a substrate such as a liquid crystal substrate. A scanning image obtained by two-dimensionally scanning the substrate on the substrate can be used.
　ＴＦＴディスプレイ装置に用いるＴＦＴアレイ基板の製造工程では、製造されたＴＦＴアレイ基板が正しく駆動するかの検査が行われる（特許文献１，２）。 In the manufacturing process of the TFT array substrate used in the TFT display device, an inspection is performed to check whether the manufactured TFT array substrate is driven correctly (Patent Documents 1 and 2).
　例えば、検査対象である基板のアレイに検査信号を印加してアレイを所定電位状態とし、基板上に電子ビームやイオンビーム等の荷電ビームを二次元的に照射して走査し、このビーム走査で得られる走査画像に基づいてＴＦＴのアレイを検査するアレイ検査装置が知られている。ＴＦＴアレイ検査では、例えば、電子線の照射によって放出される二次電子をフォトマルチプライヤなどによってアナログ信号に変換して検出し、この検出信号の信号強度に基づいてアレイ欠陥を判定している。 For example, an inspection signal is applied to an array of substrates to be inspected to bring the array into a predetermined potential state, and the substrate is scanned by two-dimensionally irradiating a charged beam such as an electron beam or an ion beam. An array inspection apparatus that inspects an array of TFTs based on a scanning image obtained is known. In the TFT array inspection, for example, secondary electrons emitted by irradiation with an electron beam are converted into an analog signal by a photomultiplier or the like and detected, and an array defect is determined based on the signal intensity of the detection signal.
　ＴＦＴ基板のアレイとピクセルは対応して形成されており、アレイに駆動信号を印加することによって特定のピクセルを駆動することができる。ＴＦＴアレイ検査において、一般に、アレイに所定パターンの駆動信号を印加して基板内に形成されたパネルの各ピクセルを所定パターンで駆動し、これらのピクセルに電子線を照射し、照射点から放出される二次電子を検出する。この電子線照射をパネル内で走査して行うことによって、パネル内の各ピクセルから検出信号を取得している。 The array and pixels of the TFT substrate are formed correspondingly, and a specific pixel can be driven by applying a drive signal to the array. In TFT array inspection, generally, a drive signal of a predetermined pattern is applied to the array to drive each pixel of the panel formed in the substrate with a predetermined pattern, and these pixels are irradiated with an electron beam and emitted from the irradiation point. Secondary electrons detected. A detection signal is acquired from each pixel in the panel by performing this electron beam irradiation in the panel.
　ピクセルに対する荷電ビームの走査において、従来、各ピクセルに対して例えば４×４点あるいは４×３点の荷電ビームを照射して照射点をサンプリング点とし、一ピクセルについて複数のサンプリング点の検出信号を検出し、この検出信号を用いてピクセルに対応するアレイの欠陥を検出するための信号強度を算出している。 In scanning of a charged beam on a pixel, conventionally, each pixel is irradiated with, for example, 4 × 4 points or 4 × 3 points of a charged beam, and the irradiation point is set as a sampling point. The signal intensity for detecting the defect of the array corresponding to the pixel is calculated using the detected signal.
　図１４は、従来のサンプリング例を説明するための概略図である。図１４において、一つのピクセルに対して４×４点の合計１６点の荷電ビームを照射して各照射点をサンプリング点とし、各サンプリング点で検出される検出信号を用いて欠陥検出のための検出信号を取得している。図１４において、各ピクセルには隣接するピクセル間で異なる電位を生じさせ電圧パターンの検査信号が印加されている。 FIG. 14 is a schematic diagram for explaining a conventional sampling example. In FIG. 14, a total of 16 charged beams of 4 × 4 points are irradiated to one pixel, and each irradiation point is set as a sampling point, and a detection signal detected at each sampling point is used to detect a defect. The detection signal is acquired. In FIG. 14, a voltage pattern inspection signal is applied to each pixel by generating different potentials between adjacent pixels.
　各ピクセルの欠陥検出は、ピクセル内の４×４点あるいは４×３点のサンプリング点の検出信号から欠陥検出用の信号強度を算出し、この信号強度とあらかじめ定めておいたしきい値と比較することによって行う。 For the defect detection of each pixel, the signal intensity for defect detection is calculated from the detection signal of 4 × 4 points or 4 × 3 sampling points in the pixel, and this signal intensity is compared with a predetermined threshold value. By doing.
特開２００４－２７１５１６号公報JP 2004-271516 A 特開２００４－３０９４８８号公報JP 2004-309488 A 特開２００２－２６０９３号公報JP 2002-26093 A
　基板のアレイ検査を行うには、パネル上に形成された各ピクセルについて荷電ビーム走査によって検出信号を検出する必要がある。従来、各ピクセルにおいて、前記したように例えば４×４点あるいは４×３点等の複数のサンプリング点について検出信号を取得している。 In order to perform an array inspection of a substrate, it is necessary to detect a detection signal by scanning a charged beam for each pixel formed on the panel. Conventionally, in each pixel, as described above, detection signals are acquired for a plurality of sampling points such as 4 × 4 points or 4 × 3 points.
　欠陥判定はピクセルを単位として行う。欠陥ピクセルを検出することによって、そのピクセルを駆動するアレイ部分に短絡や開放等の欠陥があることを検出してアレイ検査を行うことができる。アレイの欠陥種の判定は、パネル上の各ピクセルの電圧パターンを変えることによって変更することができる。各ピクセルの電圧パターンは、例えば、縦方向あるいは横方向のアレイに印加する電圧パターンを変えることで変更することができる。 Defect determination is performed in units of pixels. By detecting a defective pixel, it is possible to detect that there is a defect such as a short circuit or an open in the array portion that drives the pixel and perform an array inspection. The determination of the defect type of the array can be changed by changing the voltage pattern of each pixel on the panel. The voltage pattern of each pixel can be changed, for example, by changing the voltage pattern applied to the vertical or horizontal array.
　ピクセルを単位とする欠陥判定は、各ピクセルのサンプリング点で検出して複数の検出信号に基づいて欠陥判定用の信号強度を算出し、この信号強度をあらかじめ定めておいた欠陥判定用のしきい値と比較することによって行っている。 Defect determination in units of pixels is performed by calculating the signal intensity for defect determination based on a plurality of detection signals detected at the sampling points of each pixel, and the threshold for defect determination in which this signal intensity is determined in advance. It is done by comparing with the value.
　この欠陥判定用の信号強度を算出する際、各ピクセルのサンプリング点で検出される検出信号にノイズ分が含まれる場合がある。このノイズ分は検出信号の信号強度を本来の値からずらすことになる。そのため、ノイズ分を含む検出信号の信号強度に基づいて欠陥判定を行うと、正常ピクセルを欠陥ピクセルとして判定したり、あるいは欠陥ピクセルを正常ピクセルとして判定するといった誤検出を行うおそれがある。 When calculating the signal strength for defect determination, the detection signal detected at the sampling point of each pixel may contain noise. This noise component shifts the signal intensity of the detection signal from the original value. For this reason, if defect determination is performed based on the signal strength of the detection signal including noise, there is a risk of erroneous detection such as determining a normal pixel as a defective pixel or determining a defective pixel as a normal pixel.
　そこで、本発明は上記課題を解決して、検出信号に付加されるノイズ分に影響されることなく欠陥ピクセルを検出してアレイ検査を行うことを目的とする。 Therefore, an object of the present invention is to solve the above-described problems and to perform an array inspection by detecting defective pixels without being affected by noise added to a detection signal.
　本願の発明者は、パネル上に荷電ビームを走査して得られる信号画像には、欠陥により生じる当該欠陥種に特有な欠陥形状と、ノイズによってノイズ形状とが現れ、欠陥形状とノイズ形状とはそれらの形状によって峻別することができることを見出した。 The inventors of the present application show that a defect shape peculiar to the defect type caused by the defect and a noise shape due to noise appear in the signal image obtained by scanning the charged beam on the panel. It was found that they can be distinguished by their shapes.
　本発明は、この新たに見出した知見に基づいて、信号画像に現れる形状の中から欠陥形状をノイズ形状から峻別して検出し、この欠陥形状の検出によって欠陥ピクセルおよびこの欠陥ピクセルに対応するアレイ欠陥を検出してアレイを検査するものである。 Based on the newly found knowledge, the present invention detects a defect shape by distinguishing it from a noise shape from shapes appearing in a signal image, and detects the defect pixel and an array corresponding to the defect pixel by detecting the defect shape. The array is inspected by detecting defects.
　本発明は、ＴＦＴ基板のパネルに所定電圧の検査信号を印加してアレイを駆動し、このパネル上に荷電ビームを照射して走査し、この荷電ビーム走査で検出される検出信号に基づいてＴＦＴ基板のアレイを検査するＴＦＴアレイ検査であり、アレイ検査方法の態様およびアレイ検査装置の態様とすることができる。 The present invention applies an inspection signal of a predetermined voltage to a panel of a TFT substrate to drive the array, scans the panel by irradiating a charged beam, and based on a detection signal detected by the charged beam scanning, the TFT This is a TFT array inspection for inspecting an array of substrates, and can be an aspect of an array inspection method and an aspect of an array inspection apparatus.
　本発明のアレイ検査方法の態様は、荷電ビームの照射によってパネル上のサンプリング点の信号強度を検出する検出工程と、検出工程で検出したサンプリング点の信号強度を２値化して２値化画像を求める２値化工程と、２値化工程で求めた２値化画像に含まれる形状を照合対象形状とし、この照合対象形状と予め登録しておいた登録形状との形状を比較して照合を行う照合工程と、照合工程の照合結果により、照合対象形状の中に登録形状が含まれるか否かを判別し、照合対象形状の中に、登録形状が少なくとも一つ含まれている場合に当該照合対象形状を含むピクセルを欠陥と判別し、照合対象形状の中に、登録された全ての登録形状の何れの登録形状も含まれていない場合に照合対象形状を含むピクセルを正常と判別する欠陥判別工程とを備え、欠陥判別工程で欠陥と判別されたピクセルに対応するアレイを欠陥アレイとして検出する。 The array inspection method according to the present invention includes a detection step of detecting a signal intensity at a sampling point on a panel by irradiation with a charged beam, and binarizing the signal intensity of the sampling point detected in the detection step to obtain a binary image. The binarization step to be obtained and the shape included in the binarized image obtained in the binarization step are set as the shape to be collated, and the collation is performed by comparing the shape of the collation target shape with the registered shape registered in advance. It is determined whether or not the registered shape is included in the verification target shape based on the verification process to be performed and the verification result of the verification process, and when at least one registered shape is included in the verification target shape A defect that identifies a pixel that includes a matching target shape as a defect, and determines that a pixel that includes a matching target shape is normal when none of the registered shapes of all registered shapes are included in the matching target shape Discriminator Preparative provided to detect the array corresponding to the defect and determine pixels in the defect determination process as a defect array.
　本発明のアレイ検査装置の態様は、荷電ビームの照射によってパネル上のサンプリング点の信号強度を検出する検出部と、検出工程で検出したサンプリング点の信号強度を２値化して２値化画像を求める２値化部と、２値化部で求めた２値化画像に含まれる形状を照合対象形状とし、この照合対象形状と予め登録しておいた登録形状との形状を比較して照合を行う照合部と、照合部の照合結果により、照合対象形状の中に登録形状が含まれるか否かを判別し、照合対象形状の中に、登録形状が少なくとも一つ含まれている場合に当該照合対象形状を含むピクセルを欠陥と判別し、照合対象形状の中に、登録された全ての登録形状の何れの登録形状も含まれていない場合に照合対象形状を含むピクセルを正常と判別する欠陥判別部とを備え、欠陥判別部で欠陥と判別されたピクセルに対応するアレイを欠陥アレイとして検出する。 The aspect of the array inspection apparatus of the present invention includes a detection unit that detects the signal intensity of a sampling point on a panel by irradiation of a charged beam, and a binarized image obtained by binarizing the signal intensity of the sampling point detected in the detection process. The binarization unit to be obtained and the shape included in the binarized image obtained by the binarization unit are set as the shape to be collated, and the collation is performed by comparing the shape of the collation target shape with the registered shape registered in advance. It is determined whether the registered shape is included in the verification target shape based on the verification unit to be performed and the verification result of the verification unit, and if at least one registered shape is included in the verification target shape A defect that identifies a pixel that includes a matching target shape as a defect, and determines that a pixel that includes a matching target shape is normal when none of the registered shapes of all registered shapes are included in the matching target shape A determination unit, The array corresponding to the Recessed discriminator defects and discriminated pixels detected as defects array.
　検出工程および検出部において、荷電ビームとして電子線を用いて、この電子線をパネル上に照射し、パネル上のサンプリング点から放出される二次電子を検出し、この二次電子の検出信号の信号強度を検出する。検出工程で得られる信号強度は、パネル上のサンプリング点の電圧に依存して変化し、アレイ欠陥によってピクセルに欠陥がある場合には、このピクセル上のサンプリング点で得られる信号強度は正常なピクセルから得られる信号強度と異なる値となり、この信号強度によって正常ピクセルと欠陥ピクセルとを判別する。 In the detection step and the detection unit, an electron beam is used as a charged beam, the electron beam is irradiated onto the panel, secondary electrons emitted from a sampling point on the panel are detected, and a detection signal of the secondary electron is detected. Detect signal strength. The signal strength obtained in the detection process varies depending on the voltage of the sampling point on the panel, and if the pixel is defective due to an array defect, the signal strength obtained at the sampling point on this pixel is normal pixel. Therefore, the normal pixel and the defective pixel are discriminated based on the signal intensity.
　２値化工程および２値化部は、サンプリング点の信号強度と予め定めておいたしきい値とを比較し、サンプリング点に対応する位置に比較結果に応じて２値を対応付けることにより２値化画像を形成する。 The binarization step and the binarization unit binarize the signal by comparing the signal strength at the sampling point with a predetermined threshold value and associating the binary value with the position corresponding to the sampling point according to the comparison result. Form an image.
　検出工程および検出部で得られる信号強度は、正常ピクセルおよび欠陥ピクセルにおいて各状態に応じた強度分布を有し、それぞれ信号強度はばらつきを含んでいる。そのため、この信号強度により信号画像を形成すると、信号強度がばらつくことによって形状が変化するため、形状を特定することができず、形状に基づいて正常ピクセルと欠陥ピクセルとを判別することが困難となる。そこで、本発明では、検出信号の信号強度を２値化することによって、信号強度のばらつきによる形状が不定となることを避け、形状による正常ピクセルと欠陥ピクセルとの判別を可能とする。 The signal intensity obtained in the detection step and the detection unit has an intensity distribution corresponding to each state in the normal pixel and the defective pixel, and the signal intensity includes variations. For this reason, when a signal image is formed with this signal intensity, the shape changes due to variations in the signal intensity, so the shape cannot be specified, and it is difficult to distinguish between normal and defective pixels based on the shape. Become. Therefore, in the present invention, by binarizing the signal intensity of the detection signal, it is possible to avoid the indefinite shape due to variations in signal intensity, and to distinguish between a normal pixel and a defective pixel based on the shape.
　照合工程および照合装置は、複数の登録形状を備え、これら複数の登録形状の中から選択した登録形状毎に照合対象形状との形状を比較する。 The collation process and the collation device have a plurality of registered shapes, and compare the shape with the shape to be collated for each registered shape selected from the plurality of registered shapes.
　信号画像上に現れる欠陥による形状は、欠陥の種類や欠陥のピクセル上の位置によって異なり、その形状を予め求めておくことができる。本発明は、この欠陥による形状を予め求めて登録形状として用意しておく。登録形状は２値化したデータとすることで、２値化工程で求めた２値化画像の照合対象形状と比較する。 The shape due to the defect appearing on the signal image differs depending on the type of defect and the position of the defect on the pixel, and the shape can be obtained in advance. In the present invention, the shape due to this defect is obtained in advance and prepared as a registered shape. The registered shape is binarized data, and is compared with the target shape of the binarized image obtained in the binarization process.
　この形状比較において、同一の照合対象形状について、複数の登録形状からの登録形状を選択する選択処理と、この選択処理で選択した登録形状と照合対象形状との形状を比較する形状比較処理とを、欠陥判別において欠陥と判別されるまで繰り返す。 In this shape comparison, for the same matching target shape, a selection process for selecting a registered shape from a plurality of registered shapes, and a shape comparison process for comparing the shape of the registered shape selected in this selection process with the matching target shape. The process is repeated until the defect is determined as a defect.
同一のピクセル内に複数の欠陥が存在する場合も考えられるが、複数の登録形状の内の少なくとも一つの登録形状が検出されれば、そのピクセルは欠陥ピクセルであることが判別され、さらに別の欠陥を検出する必要はない。そこで、この形状比較では、欠陥判別工程において欠陥と判別された場合には、そのピクセルを欠陥ピクセルとし、次のピクセルの形状比較を行う。 There may be a case where a plurality of defects exist in the same pixel. However, if at least one registered shape among a plurality of registered shapes is detected, it is determined that the pixel is a defective pixel. There is no need to detect defects. Therefore, in this shape comparison, when a defect is determined in the defect determination step, the pixel is set as a defective pixel, and the shape comparison of the next pixel is performed.
　照合対象形状と登録形状との照合は、２値化画像のデータ処理によって行うことができ、種々の処理態様とすることができる。 The collation between the shape to be collated and the registered shape can be performed by binarized image data processing, and various processing modes can be used.
　例えば、登録形状の形状を窓とし、２値化画像に対して窓を移動させながらデータ上で重ね合わせ、この窓内にある２値化画像のデータが窓の形状と一致するか否かを判別するデータ処理、登録形状に対応するマッチングフィルタに２値化画像のデータを通すことによって判別するデータ処理、照合対象形状に対応する正方行列および登録形状に対応する正方行列を形成し、一方の正方行列の逆行列と他方の正方行列との積を求め、この積が単位行列であるか否かによって判別するデータ処理等を用いることができる。 For example, if the registered shape is a window, the image is superimposed on the data while moving the window with respect to the binarized image, and whether or not the data of the binarized image in this window matches the shape of the window. Data processing for discrimination, data processing for discrimination by passing the binary image data through a matching filter corresponding to the registered shape, a square matrix corresponding to the matching target shape and a square matrix corresponding to the registered shape are formed, Data processing that determines the product of the inverse matrix of the square matrix and the other square matrix and determines whether the product is a unit matrix can be used.
　本発明によれば、検出信号に付加されるノイズ分に影響されることなく欠陥ピクセルを検出してアレイ検査を行うことができる。 According to the present invention, it is possible to detect a defective pixel and perform an array inspection without being affected by noise added to the detection signal.
本発明のＴＦＴアレイ検査の工程を説明するためのフローチャートである。It is a flowchart for demonstrating the process of the TFT array test | inspection of this invention. 本発明のＴＦＴアレイ検査の信号画像を形成するまでの工程を説明するための説明図である。It is explanatory drawing for demonstrating the process until it forms the signal image of the TFT array test | inspection of this invention. 本発明のＴＦＴアレイ検査の２値化画像を説明するためのフローチャートである。It is a flowchart for demonstrating the binarized image of the TFT array test | inspection of this invention. 本発明のＴＦＴアレイ検査の２値化画像を説明するためのフローチャートである。It is a flowchart for demonstrating the binarized image of the TFT array test | inspection of this invention. 本発明のＴＦＴアレイ検査の２値化画像を説明するための説明図である。It is explanatory drawing for demonstrating the binarized image of the TFT array test | inspection of this invention. 本発明のＴＦＴアレイ検査の照合を説明するための説明図である。It is explanatory drawing for demonstrating collation of the TFT array test | inspection of this invention. 本発明のＴＦＴアレイ検査の照合を説明するための説明図である。It is explanatory drawing for demonstrating collation of the TFT array test | inspection of this invention. 本発明のＴＦＴアレイ検査の照合処理例を説明するための説明図である。It is explanatory drawing for demonstrating the collation processing example of the TFT array test | inspection of this invention. 本発明のＴＦＴアレイ検査の照合処理例を説明するための説明図である。It is explanatory drawing for demonstrating the collation processing example of the TFT array test | inspection of this invention. 本発明のＴＦＴアレイ検査の照合処理例を説明するための説明図である。It is explanatory drawing for demonstrating the collation processing example of the TFT array test | inspection of this invention. 本発明のＴＦＴアレイ検査を行う検査装置の一構成例を説明するための図である。It is a figure for demonstrating one structural example of the test | inspection apparatus which performs TFT array test | inspection of this invention. 欠陥検出部の一構成例を説明するための図である。It is a figure for demonstrating the example of 1 structure of a defect detection part. 隣接する複数のピクセルにおける欠陥判別を行う例を説明するための図である。It is a figure for demonstrating the example which performs the defect discrimination | determination in a some adjacent pixel. 従来のサンプリング例を説明するための概略図である。It is the schematic for demonstrating the example of the conventional sampling.
　以下、本発明の実施の形態について図を参照しながら詳細に説明する。以下では、図１～１０を用いて本発明のＴＦＴアレイ検査の各工程を説明し、図１１，１２を用いて本発明のＴＦＴアレイ検査による装置構成例を説明し、図１３を用いて欠陥形状が複数のピクセル間に跨る例を説明する。 Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings. In the following, each step of the TFT array inspection according to the present invention will be described with reference to FIGS. 1 to 10, an example of a device configuration by the TFT array inspection according to the present invention will be described with reference to FIGS. An example in which the shape extends between a plurality of pixels will be described.
　はじめに、本発明のＴＦＴアレイ検査の各工程について、図１の本発明のＴＦＴアレイ検査の工程を説明するためのフローチャート、図２の本発明のＴＦＴアレイ検査の信号画像を形成するまでの工程を説明するための説明図、図３，４の本発明のＴＦＴアレイ検査の２値化画像を説明するためのフローチャート、図５の本発明のＴＦＴアレイ検査の２値化画像を説明するための説明図、図６，７の本発明のＴＦＴアレイ検査の照合を説明するための説明図、図８～１０の本発明のＴＦＴアレイ検査の照合処理例を説明するための説明図を用いて説明する。 First, for each step of the TFT array inspection of the present invention, the flowchart for explaining the TFT array inspection step of the present invention in FIG. 1 and the steps until forming the signal image of the TFT array inspection of the present invention in FIG. 3 and 4 are flowcharts for explaining the binarized image of the TFT array inspection of the present invention, and FIG. 5 is an explanatory diagram for explaining the binarized image of the TFT array inspection of the present invention. Description will be made with reference to FIGS. 6 and 7 for explaining the collation of the TFT array inspection of the present invention, and FIGS. 8 to 10 for explaining the collation processing example of the TFT array inspection of the present invention. .
　本発明のＴＦＴアレイ検査は、荷電ビームの照射によってパネル上のサンプリング点の信号強度を検出する検出工程(S1)と、検出工程（S1）で検出したサンプリング点の信号強度を２値化して２値化画像を求める２値化工程(S4)と、２値化工程(S4)で求めた２値化画像に含まれる形状を照合対象形状とし、この照合対象形状と予め登録しておいた登録形状との形状を比較して照合を行う照合工程(S8)と、照合工程の照合結果により、照合対象形状の中に登録形状が含まれるか否かを判別し、照合対象形状の中に、登録形状が少なくとも一つ含まれている場合に当該照合対象形状を含むピクセルを欠陥と判別し、照合対象形状の中に、登録された全ての登録形状の何れの登録形状も含まれていない場合に照合対象形状を含むピクセルを正常と判別する欠陥判別工程(S9～S12)とを備える。欠陥判別工程(S9～S12)で欠陥と判別されたピクセルに対応するアレイを欠陥アレイとして検出する。 In the TFT array inspection of the present invention, the detection step (S1) for detecting the signal intensity at the sampling point on the panel by irradiation of the charged beam and the signal intensity at the sampling point detected in the detection step (S1) are binarized to 2 A binarization step (S4) for obtaining a binarized image, and a shape included in the binarized image obtained in the binarization step (S4) is used as a collation target shape, and a registration registered in advance with the collation target shape The matching step (S8) for comparing the shape with the shape and matching, and by checking the matching result of the matching step, it is determined whether or not the registered shape is included in the matching target shape, When at least one registered shape is included, the pixel containing the matching target shape is determined as a defect, and the registered shape does not include any registered shapes of all registered registered shapes Determines that the pixel that contains the matching target shape is normal And a defect determination step (S9 ~ S12). An array corresponding to the pixel determined to be a defect in the defect determination step (S9 to S12) is detected as a defect array.
　はじめに、ＴＦＴ基板のパネルに所定電圧の検査信号を印加してアレイを駆動し、このパネル上に荷電ビームを照射して走査し、この荷電ビーム走査によって照射点から放出される信号を検出する。荷電ビームとして電子線を用いた場合には、二次電子の検出信号が検出される。ここで、荷電ビームの照射点は、検出信号を検出するサンプリング点に対応することになる。図２（ａ）はサンプリング点を模式的に示している。 First, an inspection signal of a predetermined voltage is applied to the TFT substrate panel to drive the array, and scanning is performed by irradiating the panel with a charged beam, and a signal emitted from the irradiation point is detected by this charged beam scanning. When an electron beam is used as the charged beam, a secondary electron detection signal is detected. Here, the irradiation point of the charged beam corresponds to a sampling point for detecting the detection signal. FIG. 2 (a) schematically shows sampling points.
　荷電ビームとして電子線を用いた場合には、二次電子が放出され、この二次電子を検出して得られる検出信号に取得する(S1)。 When an electron beam is used as the charged beam, secondary electrons are emitted and acquired as a detection signal obtained by detecting the secondary electrons (S1).
　検出した検出信号をサンプリング点と共に検出データとして記録する。ここで、サンプリング点は、検出信号が得られる点であり、パネル上において荷電ビームが照射される点に対応している(S2)。 記録 Record the detected detection signal as detection data along with the sampling points. Here, the sampling point is a point where a detection signal is obtained, and corresponds to a point where a charged beam is irradiated on the panel (S2).
　走査によって得られるサンプリング点の位置は、パネル上に形成されたピクセルとの位置関係が不明であり、このままではピクセルに対応するサンプリング点を特定することができず、アレイの欠陥検出を行うことができない。 The position of the sampling point obtained by scanning is unknown in the positional relationship with the pixel formed on the panel, and if it remains as it is, the sampling point corresponding to the pixel cannot be specified, and the array defect can be detected. Can not.
　本発明は、サンプリング点をピクセルに対する関係を識別するために、パネルのピクセルに対してサンプリング点を対応付けることによって、各ピクセル内に含まれるサンプリング点を求める。 The present invention obtains sampling points included in each pixel by associating the sampling points with the pixels of the panel in order to identify the relationship of the sampling points to the pixels.
　この対応付けは、例えば、サンプリング点の位置は検査対象であるパネル上の位置であり、このパネルが形成されている基板を支持するステージ上の位置と荷電ビームの照射位置から求めることができる他、ピクセルに所定の電圧パターンを形成し、隣接する点間の信号強度を検出し、信号強度の差異によってピクセル間の境界を求め、この境界によってピクセルに対するサンプリング点対応関係を求めることで行うことができる。これによって、サンプリング点とピクセルとの対応関係を求め、検出データにおいてピクセルを識別する。図２（ｂ）はサンプリング点とピクセルとの対応関係を示している (S3)。 For example, the position of the sampling point is a position on the panel to be inspected, and this correspondence can be obtained from the position on the stage that supports the substrate on which the panel is formed and the irradiation position of the charged beam. , By forming a predetermined voltage pattern in the pixel, detecting the signal intensity between adjacent points, obtaining a boundary between the pixels based on the difference in signal intensity, and obtaining a sampling point correspondence relationship with the pixel based on the boundary. it can. Thereby, the correspondence between the sampling points and the pixels is obtained, and the pixels are identified in the detection data. FIG. 2B shows the correspondence between sampling points and pixels (S3).
　前記検出データは、その位置と信号強度から信号画像を形成することができる。しかしながら、この信号強度は、正常ピクセルおよび欠陥ピクセルにおいて各状態に応じた強度分布を有し、それぞれ信号強度はばらつきを含んでいる。図２（ｃ）はサンプリング点における検出信号の信号強度から求めた信号画像と、ピクセルとの関係を模式的に示している。このように、ばらつきを含む信号強度により信号画像を形成すると、信号強度のばらつきによって形状が変化するため、形状を特定することが困難であり、ピクセルの正常および欠陥の判別に利用することは難しい。 The detection data can form a signal image from its position and signal intensity. However, this signal intensity has an intensity distribution corresponding to each state in the normal pixel and the defective pixel, and the signal intensity includes variations. FIG. 2C schematically shows the relationship between the pixel and the signal image obtained from the signal intensity of the detection signal at the sampling point. As described above, when a signal image is formed with signal strength including variation, the shape changes due to variation in signal strength, so that it is difficult to specify the shape, and it is difficult to use it for pixel normality and defect discrimination. .
　そこで、検出信号の信号強度を２値化することによって、信号強度のばらつきによる形状が不定となることを避け、形状に基づいてピクセルの正常と欠陥との判別が可能となるようにする。 Therefore, by binarizing the signal intensity of the detection signal, it is possible to avoid the indefinite shape due to variations in the signal intensity and to determine whether the pixel is normal or defective based on the shape.
　２値化工程によって信号画像から２値化画像を形成する。２値化の処理は、サンプリング点の信号強度と予め定めておいたしきい値とを比較して行う。比較結果に応じて２値を定め、サンプリング点に対応する位置に対応付ける。これによって２値化画像を形成する。 Binary image is formed from signal image by binarization process. The binarization process is performed by comparing the signal intensity at the sampling point with a predetermined threshold value. Two values are determined according to the comparison result, and are associated with the positions corresponding to the sampling points. Thereby, a binarized image is formed.
　図３は２値化を説明するための図である。ピクセルの欠陥は、ピクセルの電圧において二つの態様で現れる。一つの態様は、欠陥ピクセルの電圧が正常ピクセルの電圧よりも低い電圧で現れる場合であり、黒欠陥と呼ばれる。他方の態様は、欠陥ピクセルの電圧が正常ピクセルの電圧よりも高い電圧で現れる場合であり、白欠陥と呼ばれる。 FIG. 3 is a diagram for explaining binarization. Pixel defects appear in two ways in the pixel voltage. One aspect is when the defective pixel voltage appears at a lower voltage than the normal pixel voltage and is called a black defect. The other aspect is when the defective pixel voltage appears at a higher voltage than the normal pixel voltage, which is called a white defect.
　図３（ａ）は黒欠陥の場合の２値化を表している。この場合には、信号強度を２値化するしきい値として欠陥強度maxを予め定めておき、信号強度が欠陥強度maxよりも低い信号画像の位置を欠陥に対応付け、信号強度が欠陥強度maxよりも高い信号画像の位置を正常に対応付ける。 Fig. 3 (a) shows binarization in the case of a black defect. In this case, the defect strength max is determined in advance as a threshold value for binarizing the signal strength, the position of the signal image whose signal strength is lower than the defect strength max is associated with the defect, and the signal strength is the defect strength max. The signal image position higher than that is normally associated.
　図３（ｂ）は白欠陥の場合の２値化を表している。この場合には、信号強度を２値化するしきい値として欠陥強度min（＜欠陥強度max）を予め定めておき、信号強度が欠陥強度minよりも高い信号画像の位置を欠陥に対応付け、信号強度が欠陥強度minよりも低い信号画像の位置を正常に対応付ける。 FIG. 3B shows binarization in the case of a white defect. In this case, a defect intensity min (<defect intensity max) is determined in advance as a threshold value for binarizing the signal intensity, and the position of the signal image whose signal intensity is higher than the defect intensity min is associated with the defect. The position of the signal image whose signal intensity is lower than the defect intensity min is normally associated.
　図４は黒欠陥の２値化の手順を表すフローチャートである。黒欠陥の２値化は、S2で記憶しておいたサンプリング点の信号強度を読み出し(S4a)、読み出した信号強度と黒欠陥のしきい値である欠陥強度maxと比較する(S4b)。 FIG. 4 is a flowchart showing the black defect binarization procedure. In binarization of black defects, the signal intensity at the sampling point stored in S2 is read (S4a), and the read signal intensity is compared with the defect intensity max which is the threshold value of the black defect (S4b).
　信号強度が欠陥強度maxよりも大きい場合には、その信号強度は正常レベルであるとして、そのサンプリング点に対応する信号画像の位置に正常ピクセルを表す値を設定する（S4c)。一方、信号強度が欠陥強度max以下である場合には、その信号強度は欠陥レベルであるとして、そのサンプリング点に対応する信号画像の位置に欠陥ピクセルを表す値を設定する。２値化により正常ピクセルおよび欠陥ピクセルに対応つけて設定する値は、例えば"０"および"１"など任意に定めることができる（S4d)。 When the signal intensity is larger than the defect intensity max, the signal intensity is assumed to be a normal level, and a value representing a normal pixel is set at the position of the signal image corresponding to the sampling point (S4c). On the other hand, when the signal intensity is equal to or lower than the defect intensity max, the signal intensity is assumed to be the defect level, and a value representing the defective pixel is set at the position of the signal image corresponding to the sampling point. Values set in correspondence with normal pixels and defective pixels by binarization can be arbitrarily determined, for example, “0” and “1” (S4d).
　全サンプリング点の信号強度についてS4a～S4dの処理を行って、信号画像から２値信号画像を形成する（S4e）。 信号 Processes S4a to S4d for the signal intensities at all sampling points to form a binary signal image from the signal image (S4e).
　図５は白欠陥の２値化の手順を表すフローチャートである。白欠陥の２値化は、S2で記憶しておいたサンプリング点の信号強度を読み出し(S4A)、読み出した信号強度と白欠陥のしきい値である欠陥強度minと比較する(S4B)。 FIG. 5 is a flowchart showing the binarization procedure for white defects. In binarization of white defects, the signal intensity at the sampling point stored in S2 is read (S4A), and the read signal intensity is compared with the defect intensity min, which is the threshold value for white defects (S4B).
　信号強度が欠陥強度min以上である場合には、その信号強度は欠陥レベルであるとして、そのサンプリング点に対応する信号画像の位置に欠陥ピクセルを表す値を設定する（S4C)。一方、信号強度が欠陥強度minよりも小さい場合には、その信号強度は正常レベルであるとして、そのサンプリング点に対応する信号画像の位置に正常ピクセルを表す値を設定する。２値化により正常ピクセルおよび欠陥ピクセルに対応つけて設定する値は、例えば"０"および"１"など任意に定めることができる（S4D)。 If the signal intensity is not less than the defect intensity min, the signal intensity is assumed to be the defect level, and a value representing the defective pixel is set at the position of the signal image corresponding to the sampling point (S4C). On the other hand, when the signal intensity is smaller than the defect intensity min, the signal intensity is assumed to be a normal level, and a value representing a normal pixel is set at the position of the signal image corresponding to the sampling point. Values set in correspondence with normal pixels and defective pixels by binarization can be arbitrarily determined, for example, “0” and “1” (S4D).
　全サンプリング点の信号強度についてS4A～S4Dの処理を行って、信号画像から２値信号画像を形成する（S4E）。 信号 S4A to S4D processing is performed on the signal intensity at all sampling points to form a binary signal image from the signal image (S4E).
　２値化処理によって得られた２値化データを記録する。２値化データは、例えば２値化処理で設定した値およびピクセル内における位置とすることができる（S5）。 Record the binarized data obtained by the binarization process. The binarized data can be, for example, the value set in the binarization process and the position in the pixel (S5).
　２値化画像から欠陥を検出するために、２値化画像中に現れる照合対象形状と登録形状と比較して照合し、照合対象形状内に登録形状が含まれているか否かを判別する。照合対象形状は、２値化処理によって欠陥レベルと判別された点の集合によって形成される形状であり、欠陥によって生じる点の集合により形成される形状、あるいはノイズによる点の集合により形成される形状を含んでいる。照合対象形状内に登録形状が含まれていると判別された場合には、そのピクセルは欠陥ピクセルと判別する。 In order to detect a defect from the binarized image, the collation target shape appearing in the binarized image is compared with the registered shape, and it is determined whether or not the registered shape is included in the collation target shape. The shape to be collated is a shape formed by a set of points determined as a defect level by binarization processing, a shape formed by a set of points caused by defects, or a shape formed by a set of points due to noise Is included. If it is determined that the registered shape is included in the verification target shape, the pixel is determined as a defective pixel.
　登録形状は、欠陥ピクセルに現れる２値画像中の形状を予め求めておく。この登録形状は、照合処理をソフトウエアで行う場合にはその形状を表すデータを記録しておく他、照合処理をハードウエアで行う場合にはその形状を表す素子配置によって構成することができる。 As the registered shape, the shape in the binary image that appears in the defective pixel is obtained in advance. This registered shape can be configured by recording data representing the shape when the collating process is performed by software, and by element arrangement representing the shape when the collating process is performed by hardware.
　記録しておいた２値化画像から２値化データを読み出し（S6）、読み出した２値化データと登録形状の２値化データとを比較し（S7）、照合対象形状の中に登録形状が含まれているか否かを判別する（S8）。登録形状が含まれている場合にはその形状が含まれるピクセルを欠陥ピクセルとして判別する(S9)。登録形状が含まれていない場合には、登録されている別の登録形状についてS7,S8の処理を繰り返して登録形状の有無を判別し、登録された全登録形状について含まれていない場合には(S10)、そのピクセルは正常ピクセルとして判別する(S11)。S6～S11の処理を全照合対象形状について行って、２値化画像から欠陥ピクセルを検出する(S12)。 Read the binarized data from the recorded binarized image (S6), compare the read binarized data with the binarized data of the registered shape (S7), and register the registered shape among the shapes to be verified It is determined whether or not is included (S8). If the registered shape is included, the pixel including the shape is determined as a defective pixel (S9). If the registered shape is not included, repeat the processing of S7 and S8 for another registered shape to determine the presence or absence of the registered shape, and if not all registered shapes are included (S10), the pixel is determined as a normal pixel (S11). The processes from S6 to S11 are performed for all the shapes to be collated, and defective pixels are detected from the binarized image (S12).
　図６，図７は照合の一例を示している。図６（ａ）,図７（ａ）は黒欠陥の２値化画像の一例を示し、図中の白い部分は正常レベルを示し、黒い部分は欠陥レベルを示している。欠陥レベルには、欠陥による部分とノイズによる部分が含まれるため、照合対象形状と登録形状とを照合することによってノイズによらず欠陥による形状を判別する。 6 and 7 show an example of collation. FIG. 6A and FIG. 7A show an example of a binarized image of a black defect, and a white portion in the figure indicates a normal level and a black portion indicates a defect level. Since the defect level includes a portion due to a defect and a portion due to noise, the shape due to the defect is discriminated regardless of noise by collating the shape to be collated with the registered shape.
　図６（ｂ）～図６（ｇ）に示すピクセルは、２値化画像中の照合対象形状と登録形状との照合例を示している。図６（ｂ）～図６（ｅ）に示すピクセルの照合、および図６（ｇ）に示すピクセルの照合では、２値化画像中に登録形状が含まれていないため、これらのピクセルは正常ピクセルと判別する。一方、図６（ｆ）に示すピクセルの照合では、２値化画像中に登録形状が含まれていると判別されるため、このピクセルは欠陥ピクセルと判別する。 The pixels shown in FIGS. 6B to 6G show an example of matching between the matching target shape in the binarized image and the registered shape. In the pixel matching shown in FIGS. 6B to 6E and the pixel matching shown in FIG. 6G, the registered shape is not included in the binarized image, so these pixels are normal. Discriminated as a pixel. On the other hand, in the pixel matching shown in FIG. 6F, since it is determined that the registered shape is included in the binarized image, this pixel is determined as a defective pixel.
　図７は、図６で示した一つの登録形状による照合によって欠陥ピクセルを検出した後、別の登録形状によって照合を行う例を示している。 FIG. 7 shows an example in which after a defective pixel is detected by collation using one registered shape shown in FIG. 6, collation is performed using another registered shape.
　図７（ｂ）～図７（ｇ）に示すピクセルは、２値化画像中の照合対象形状と登録形状との照合例を示している。図７（ｂ）～図７（ｅ）に示すピクセルの照合では、２値化画像中に登録形状が含まれていないため、これらのピクセルは正常ピクセルと判別する。図７（ｆ）に示すピクセルは、前記した図６（ｆ）のピクセルの照合によって登録形状が検出されているため、ここでの登録形状の照合は不要であり省略される。図７（ｇ）に示す照合では、２値化画像中に登録形状が含まれていると判別し、このピクセルは欠陥ピクセルと判別する。 The pixels shown in FIGS. 7B to 7G show an example of matching between the matching target shape in the binarized image and the registered shape. In the pixel matching shown in FIGS. 7B to 7E, since the registered shape is not included in the binarized image, these pixels are determined as normal pixels. Since the registered shape of the pixel shown in FIG. 7 (f) is detected by the above-described pixel matching in FIG. 6 (f), the matching of the registered shape here is unnecessary and is omitted. In the collation shown in FIG. 7G, it is determined that a registered shape is included in the binarized image, and this pixel is determined as a defective pixel.
　次に、図８～図１０を用いて照合処理の一例を示す。照合対象形状と登録形状との照合は、２値化画像のデータ処理によって行うことができ、種々の処理態様とすることができる。 Next, an example of the collation process will be described with reference to FIGS. The matching between the matching target shape and the registered shape can be performed by data processing of a binarized image, and various processing modes can be used.
　図８は、登録形状の形状を窓とし、２値化画像に対して窓を移動させながらデータ上で重ね合わせ、この窓内にある２値化画像のデータが窓の形状と一致するか否かを判別するデータ処理例を示している。 FIG. 8 shows that the registered shape is a window and is superimposed on the data while moving the window with respect to the binarized image, and whether the data of the binarized image in this window matches the shape of the window. This shows an example of data processing for determining whether or not.
　図８（ａ）は一ピクセルの２値化画像例を示し、図中の白い部分は正常レベルを示し、黒い部分は欠陥レベルを示している。図８（ｂ）は登録形状の例を示している。この照合例では、登録形状を窓として２値化画像とデータ上で重ね合わせ、この窓内にある２値化画像のデータが窓の形状と一致するか否かを判別することで照合を行う。図８（ｃ）～図８（ｈ）は、２値化画像に対して窓を順にずらしながら重ね合わせる例を模式的に示している。図８（ｃ）、図８（ｅ）～図８（ｈ）に示す重ね合わせでは、２値化画像は登録形状の窓と一致しない部分があるため、照合対象形状は欠陥形状でないと判別する。一方、図８（ｄ）に示す重ね合わせでは、２値化画像は登録形状の窓と一致するため、照合対象形状は欠陥形状であると判別する。 FIG. 8A shows an example of a binarized image of one pixel, where a white part in the figure indicates a normal level and a black part indicates a defect level. FIG. 8B shows an example of a registered shape. In this collation example, the registration shape is used as a window to overlap the binarized image on the data, and collation is performed by determining whether the data of the binarized image in the window matches the shape of the window. . FIGS. 8C to 8H schematically show an example of superimposing the binarized image while sequentially shifting the windows. In the superposition shown in FIG. 8C and FIG. 8E to FIG. 8H, since the binarized image has a portion that does not match the registered shape window, it is determined that the verification target shape is not a defect shape. . On the other hand, in the superposition shown in FIG. 8D, since the binarized image matches the window of the registered shape, it is determined that the verification target shape is a defect shape.
　２値化画像と窓と画像の重ね合わせは、ピクセルの２値化画像の中から登録形状の窓に対応するデータを抽出し、それぞれ対応する画素位置の２値を比較することで行うことができる。 The superimposition of the binarized image, the window, and the image can be performed by extracting data corresponding to the registered shape window from the binarized image of the pixels and comparing the binary values of the corresponding pixel positions. it can.
　図９は、登録形状に対応するマッチングフィルタに２値化画像のデータを通すことによって判別するデータ処理例を示している。 FIG. 9 shows an example of data processing that is determined by passing binarized image data through a matching filter corresponding to a registered shape.
　図９に示すマッチングフィルタの構成は、登録形状を含む正方行列を形成し、この正方行列に対応して遅延素子、アンド回路、およびオア回路によって構成するものである。例えば、正方行列の左上から右下に向かって、行方向と列方向とによって信号が入力するものとして、各信号の値の間に遅延素子を配置し、各遅延素子の出力の内で"１"に対応する遅延素子の出力にアンド回路を配置し、さらに、登録形状が備える全アンド回路の出力にアンド回路を配置する。アンド回路の他方の入力端には"１"を入力する。 The configuration of the matching filter shown in FIG. 9 forms a square matrix including a registered shape, and is configured by a delay element, an AND circuit, and an OR circuit corresponding to this square matrix. For example, assuming that signals are input in the row direction and the column direction from the upper left to the lower right of the square matrix, delay elements are arranged between the values of the respective signals, and among the outputs of the respective delay elements, "1" An AND circuit is arranged at the output of the delay element corresponding to ", and an AND circuit is arranged at the output of all AND circuits included in the registered shape. “1” is input to the other input terminal of the AND circuit.
　例えば、図９では、登録形状の２値化信号に対して正方行列Ｐ，Ｑ，Ｒを形成する。正方行列内で登録形状の２値化信号以外の要素は"×"で示している。正方行列Ｐの２値化信号の内"１"に対応してアンド回路２００～２０３を形成し、アンド回路２００～２０３の出力をアンド回路２０４に入力する。同様に、正方行列Ｑの２値化信号の内"１"に対応してアンド回路３００～３０３を形成し、アンド回路３００～３０３の出力をアンド回路３０４に入力し、正方行列Ｒの２値化信号の内"１"に対応してアンド回路４００～４０３を形成し、アンド回路４００～４０３の出力をアンド回路４０４に入力し、アンド回路２０４，３０４，４０４に出力をオア回路５００に入力する。 For example, in FIG. 9, square matrices P, Q, and R are formed for the binary signal of the registered shape. Elements other than the binary signal of the registered shape in the square matrix are indicated by “x”. The AND circuits 200 to 203 are formed corresponding to “1” of the binarized signals of the square matrix P, and the outputs of the AND circuits 200 to 203 are input to the AND circuit 204. Similarly, AND circuits 300 to 303 are formed corresponding to “1” in the binarized signal of the square matrix Q, the outputs of the AND circuits 300 to 303 are input to the AND circuit 304, and the binary of the square matrix R AND circuits 400 to 403 are formed corresponding to “1” of the digitized signals, the outputs of the AND circuits 400 to 403 are input to the AND circuit 404, and the outputs are input to the AND circuits 204, 304, 404. To do.
　このマッチングフィルタに照合対象形状の２値化信号を順に入力すると、照合対象形状内に登録形状が含まれる場合には、オア回路５００から出力が得られる。図９の例では、正方行列Ｑに対応したアンド回路３０４からのみ信号が出力され、オア回路５００から出力が得られる。オア回路５００から出力が得られることによって、欠陥判別を行うことができる。 When the binarized signals of the shape to be matched are sequentially input to this matching filter, an output is obtained from the OR circuit 500 when the registered shape is included in the shape to be matched. In the example of FIG. 9, a signal is output only from the AND circuit 304 corresponding to the square matrix Q, and an output is obtained from the OR circuit 500. By obtaining an output from the OR circuit 500, defect determination can be performed.
　オア回路５００から出力が得られない場合には、ピクセルは正常であると判別することができる。 If no output is obtained from the OR circuit 500, it can be determined that the pixel is normal.
　このマッチングフィルタによる場合には、予め定めておいた登録形状に対応したマッチングフィルタをハードウエアで構成しておき、各ピクセルの２値化画像の２値化信号を順に入力することで欠陥判別を行うことができる。 In the case of using this matching filter, a matching filter corresponding to a predetermined registered shape is configured by hardware, and defect determination is performed by sequentially inputting a binary signal of a binary image of each pixel. It can be carried out.
　次に、図１０を用いて行列式の演算によって欠陥判別を行う例を示す。この欠陥判別では、照合対象形状に対応する正方行列を形成すると共に、登録形状に対応する正方行列を形成し、一方の正方行列の逆行列と他方の正方行列との積を求め、この積が単位行列であるか否かによって判別する。 Next, an example of performing defect determination by determinant calculation using FIG. In this defect determination, a square matrix corresponding to the shape to be matched is formed and a square matrix corresponding to the registered shape is formed, and a product of an inverse matrix of one square matrix and a square matrix of the other is obtained, and this product is Judgment is made based on whether or not it is a unit matrix.
　図１０（ａ）は照合対象形状に対応する正方行列を形成する例を示し、図１０（ｂ）は登録形状に対応する正方行列を形成する例を示している。 FIG. 10A shows an example of forming a square matrix corresponding to the shape to be collated, and FIG. 10B shows an example of forming a square matrix corresponding to the registered shape.
　図１０（ｂ）に示した登録形状の例は３行であるため、対応する正方行列は３行×３列となる。この登録形状に対応する正方行列Ａ１は３列目に［000］を追加して形成する。照合対象形状内の登録形状が含まれるか否かの判定では、登録形状が備える"１"の要素配列の他に、"０"の要素配列が"１"である場合も含んで欠陥判別するため、上記の正方行列Ａ１に加えて、要素配列"０"を"１"に反転させた正方行列Ａ２，Ａ３，Ａ４も用意する。 Since the example of the registered shape shown in FIG. 10B is 3 rows, the corresponding square matrix is 3 rows × 3 columns. The square matrix A1 corresponding to this registered shape is formed by adding [000] to the third column. In determining whether or not the registered shape in the verification target shape is included, defect determination is performed including the case where the element array of “0” is “1” in addition to the element array of “1” included in the registered shape. Therefore, in addition to the square matrix A1, square matrices A2, A3, and A4 obtained by inverting the element array “0” to “1” are also prepared.
　この登録形状から形成した正方行列Ａ１～Ａ４との積を演算するために、照合対象形状から３行×３列の正方行列を形成する。図１０（ａ）では、照合対象形状から形成される４行×４列の正方行列Ｂから３行×３列の正方行列Ｂ１～Ｂ６を形成する。このとき、３列目に［000］を追加して正方行列を形成する。 In order to calculate the product of the square matrices A1 to A4 formed from this registered shape, a 3 × 3 square matrix is formed from the shape to be verified. In FIG. 10 (a), 3 × 3 square matrices B1 to B6 are formed from a 4 × 4 square matrix B formed from the matching target shape. At this time, [000] is added to the third column to form a square matrix.
　登録形状から形成した正方行列Ａ１～Ａ４は正則行列であるので、それぞれ逆行列Ａ１－１～Ａ４－１を形成し、照合対象形状から形成した正方行列Ｂ１～Ｂ６との積を求める。 Since the square matrices A1 to A4 formed from the registered shapes are regular matrices, the inverse matrices A1 −1 to A4 −1 are formed, respectively, and the products of the square matrices B1 to B6 formed from the matching target shapes are obtained.
　図１０（ｃ）は正方行列Ｂと正方行列Ａの逆行列Ａ－１との積を示している。正方行列Ｂと逆行列Ａ－１との積が単位行列である場合には、正方行列Ｂと正方行列Ａとが一致していることを示している。このことは、照合対象形状と登録形状とが一致していることを示している。 FIG. 10C shows the product of the square matrix B and the inverse matrix A −1 of the square matrix A. When the product of the square matrix B and the inverse matrix A −1 is a unit matrix, it indicates that the square matrix B and the square matrix A match. This indicates that the verification target shape matches the registered shape.
　図１０（ｃ）では、正方行列Ｂと正方行列Ａ３の逆行列Ａ３－１との積が単位行列Ｅとなり、照合対象形状内に登録形状が含まれることを示している。 In FIG. 10C, the product of the square matrix B and the inverse matrix A3 −1 of the square matrix A3 becomes the unit matrix E, which indicates that the registered shape is included in the matching target shape.
　次に、本発明のＴＦＴアレイ検査を行う検査装置の一構成例について図１１を用いて説明する。 Next, a configuration example of an inspection apparatus that performs the TFT array inspection of the present invention will be described with reference to FIG.
　図１１は、本発明のＴＦＴアレイ検査を行う検査装置の一構成例を説明するための図である。図１１に示す構成例では、液晶基板等のＴＦＴ基板に電子線を照射し、ＴＦＴ基板から放出される二次電子を検出し、二次電子の検出信号から信号画像を形成し、この信号画像に基づいて欠陥検出を行う構成例を示している。本発明は、検査対象の基板は液晶基板に限らず、また、基板走査は電子線に限らずイオンビーム等の荷電ビームとすることができる。また、検出信号は照射する荷電ビームに依存し、二次電子に限られるものではない。 FIG. 11 is a diagram for explaining a configuration example of an inspection apparatus for performing the TFT array inspection of the present invention. In the configuration example shown in FIG. 11, a TFT substrate such as a liquid crystal substrate is irradiated with an electron beam, secondary electrons emitted from the TFT substrate are detected, and a signal image is formed from a detection signal of the secondary electrons. The example of a structure which performs defect detection based on this is shown. In the present invention, the substrate to be inspected is not limited to a liquid crystal substrate, and substrate scanning is not limited to an electron beam, and a charged beam such as an ion beam can be used. The detection signal depends on the charged beam to be irradiated and is not limited to secondary electrons.
　図１１において、ＴＦＴアレイ検査装置１は、液晶基板等のＴＦＴ基板１００を載置しＸＹ方向に搬送自在とするステージ２と、ステージ２の上方位置にステージ２から離して配置された電子銃３と、ＴＦＴ基板１００のパネル１０１のピクセル（図示していない）から放出される二次電子を検出する検出器４とを備える。電子銃３および検出器４は複数の組みを設けることができる。 In FIG. 11, a TFT array inspection apparatus 1 includes a stage 2 on which a TFT substrate 100 such as a liquid crystal substrate is placed and can be conveyed in the XY directions, and an electron gun 3 disposed above the stage 2 and spaced from the stage 2 And a detector 4 for detecting secondary electrons emitted from a pixel (not shown) of the panel 101 of the TFT substrate 100. The electron gun 3 and the detector 4 can be provided with a plurality of sets.
　ステージ駆動制御部６はステージ２の駆動を制御し、電子線走査制御部５は電子銃３が照射する電子線の照射方向を制御して、ＴＦＴ基板１００上の電子線の走査を制御する。信号処理部１０は、検出器４で検出して二次電子の検出信号を信号処理して欠陥検出部１１に送る。欠陥検出部１１は、信号処理部１０から送られた検出信号に基づいてピクセルの欠陥を検出し、検出位置によって欠陥ピクセルおよび対応する欠陥アレイを検出する。 The stage drive control unit 6 controls the driving of the stage 2, and the electron beam scanning control unit 5 controls the scanning direction of the electron beam on the TFT substrate 100 by controlling the irradiation direction of the electron beam irradiated by the electron gun 3. The signal processing unit 10 performs signal processing on the detection signal of the secondary electrons detected by the detector 4 and sends it to the defect detection unit 11. The defect detection unit 11 detects a pixel defect based on the detection signal sent from the signal processing unit 10, and detects a defective pixel and a corresponding defect array based on the detection position.
　なお、ピクセルおよびアレイはＴＦＴ基板のパネルに形成され、各ピクセルはアレイに対して電圧を印加することによって駆動されるため、ピクセルの欠陥検出は、そのピクセルに対するアレイ検査に対応している。 The pixels and the array are formed on the panel of the TFT substrate, and each pixel is driven by applying a voltage to the array. Therefore, the defect detection of the pixel corresponds to the array inspection for the pixel.
　電子線走査制御部５，ステージ駆動制御部６，信号処理部１０、欠陥検出部１１の各部の駆動動作は制御部７によって制御される。また、制御部７は、ＴＦＴアレイ検査装置１の全体の動作を含む制御を行う機能を有し、これらの制御を行うＣＰＵおよびＣＰＵを制御するプログラム記憶するメモリ等によって構成することができる。 The driving operation of each of the electron beam scanning control unit 5, the stage drive control unit 6, the signal processing unit 10, and the defect detection unit 11 is controlled by the control unit 7. The control unit 7 has a function of performing control including the entire operation of the TFT array inspection apparatus 1, and can be configured by a CPU that performs these controls and a memory that stores a program that controls the CPU.
　ステージ２は、ＴＦＴ基板１００を載置するとともに、ステージ駆動制御部６によってＸ軸方向およびＹ軸方向に移動自在であり、また、電子銃Ｇから照射される電子線は電子線走査制御部５によってＸ軸方向あるいはＹ軸方向に振らせることができる。ステージ駆動制御部６および電子線走査制御部５は単独あるいは協働動作によって、電子線をＴＦＴ基板１００上で走査させ、ＴＦＴ基板１００のパネル１０１の各ピクセルに照射させることができる。 The stage 2 mounts the TFT substrate 100 and is movable in the X-axis direction and the Y-axis direction by the stage drive control unit 6, and the electron beam irradiated from the electron gun G is an electron beam scanning control unit 5. Can be swung in the X-axis direction or the Y-axis direction. The stage drive control unit 6 and the electron beam scanning control unit 5 can scan the electron beam on the TFT substrate 100 and irradiate each pixel on the panel 101 of the TFT substrate 100 by single or cooperative operation.
　図１２は、欠陥検出部２０の一構成例を説明するための図であり、ソフトウエアによるデータ処理で欠陥検出を行う構成について示している。 FIG. 12 is a diagram for explaining a configuration example of the defect detection unit 20, and shows a configuration in which defect detection is performed by data processing by software.
　図１２において、検出部２１は、信号処理部１０から送られた検出信号から信号画像を形成し、得られた信号画像の信号強度や検出位置を検出データ２５ａとして記憶部２５に記憶する。２値化部２２は、検出部２１で検出したサンプリング点の信号強度を２値化し、２値化画像を求める。求めた２値化画像のデータは、２値化データ２５ｂとして記憶部２５に記憶する。 12, the detection unit 21 forms a signal image from the detection signal sent from the signal processing unit 10, and stores the signal strength and detection position of the obtained signal image in the storage unit 25 as detection data 25a. The binarization unit 22 binarizes the signal intensity at the sampling points detected by the detection unit 21 to obtain a binarized image. The obtained binarized image data is stored in the storage unit 25 as binarized data 25b.
　照合部２３は、２値化部２２で求めた２値化画像に含まれる形状を照合対象形状とし、この照合対象形状と予め登録しておいた登録形状との形状を比較して照合を行う。この照合において、記憶部２５から２値化データ２５ｂと登録形状データ２５ｃを読み出す。 The collation unit 23 uses the shape included in the binarized image obtained by the binarization unit 22 as a collation target shape, and collates the collation target shape with a registered shape registered in advance. . In this verification, the binarized data 25b and the registered shape data 25c are read from the storage unit 25.
　欠陥判別部２４は、照合部２３の照合結果により、照合対象形状の中に登録形状が含まれるか否かを判別し、照合対象形状の中に登録形状が少なくとも一つ含まれている場合にその照合対象形状を含むピクセルを欠陥と判別する。一方、照合対象形状の中に、登録された全ての登録形状の何れの登録形状も含まれていない場合には、その照合対象形状を含むピクセルを正常と判別する。欠陥判別部２４は、欠陥と判別されたピクセルに対応するアレイを欠陥アレイとして検出する。 The defect discriminating unit 24 discriminates whether or not the registered shape is included in the verification target shape based on the verification result of the verification unit 23, and when at least one registered shape is included in the verification target shape. A pixel including the matching target shape is determined as a defect. On the other hand, if none of the registered shapes of all registered shapes is included in the matching target shape, the pixel including the matching target shape is determined to be normal. The defect determination unit 24 detects an array corresponding to a pixel determined as a defect as a defect array.
　上記の説明では、主に一ピクセル内に登録形状が含まれているか否かを判別しているが、照合対象形状と登録形状との比較による欠陥検出は、一ピクセル内での判別に限らず、隣接する複数のピクセルにおいて欠陥判別を行うことができる。 In the above description, it is mainly determined whether or not a registered shape is included in one pixel. However, defect detection based on a comparison between a matching target shape and a registered shape is not limited to determination within one pixel. , Defect determination can be performed in a plurality of adjacent pixels.
　図１３は、隣接する複数のピクセルにおける欠陥判別を行う例を示している。図１３（ａ）において、横方向に隣接する２つのピクセル間に跨って欠陥が発生する例、縦方向に隣接する２つのピクセル間に跨って欠陥が発生する例、および横方向および縦方向に隣接する４つのピクセル間に跨って欠陥が発生する例を示し、これらの箇所に登録形状が検出される。 FIG. 13 shows an example in which defect determination is performed on a plurality of adjacent pixels. In FIG. 13A, an example in which a defect occurs between two pixels adjacent in the horizontal direction, an example in which a defect occurs between two pixels adjacent in the vertical direction, and a horizontal direction and a vertical direction An example in which a defect occurs between four adjacent pixels is shown, and a registered shape is detected at these locations.
　図１３（ｂ）は、横方向に隣接する２つのピクセル間に跨って欠陥が発生する場合に登録形状を検出する例を示している。この場合には、横方向に隣接する２つのピクセルを判定範囲とし、この判定範囲内にある照合対象形状について前記したと同様に登録形状を検出することで欠陥検出を行う。 FIG. 13B shows an example in which a registered shape is detected when a defect occurs between two adjacent pixels in the horizontal direction. In this case, two pixels adjacent in the horizontal direction are set as a determination range, and defect detection is performed by detecting a registered shape in the same manner as described above for a verification target shape within the determination range.
　図１３（ｃ）は、縦方向に隣接する２つのピクセル間に跨って欠陥が発生する場合に登録形状を検出する例を示している。この場合には、縦方向に隣接する２つのピクセルを判定範囲とし、この判定範囲内にある照合対象形状について前記したと同様に登録形状を検出することで欠陥検出を行う。 FIG. 13C shows an example in which a registered shape is detected when a defect occurs between two pixels adjacent in the vertical direction. In this case, two pixels adjacent in the vertical direction are used as a determination range, and defect detection is performed by detecting a registered shape in the same manner as described above for a verification target shape within the determination range.
　図１３（ｄ）は、横方向および縦方向に隣接する４つのピクセル間に跨って欠陥が発生する場合に登録形状を検出する例を示している。この場合には、横方向および縦方向に隣接する４つのピクセルを判定範囲とし、この判定範囲内にある照合対象形状について前記したと同様に登録形状を検出することで欠陥検出を行う。 FIG. 13D shows an example in which a registered shape is detected when a defect occurs between four pixels adjacent in the horizontal and vertical directions. In this case, four pixels adjacent in the horizontal direction and the vertical direction are set as the determination range, and the defect detection is performed by detecting the registered shape in the same manner as described above with respect to the verification target shape within the determination range.
　本発明は、ＴＦＴ基板は液晶基板や有機ＥＬとすることができ、液晶基板や有機ＥＬを形成する成膜装置の他、種々の半導体基板を形成する成膜装置に適用することができる。 In the present invention, the TFT substrate can be a liquid crystal substrate or an organic EL, and can be applied to a film forming apparatus for forming various semiconductor substrates in addition to a film forming apparatus for forming a liquid crystal substrate or an organic EL.
　１　　アレイ検査装置
　２　　ステージ
　３　　電子銃
　４　　検出器
　５　　電子線走査制御部
　６　　ステージ駆動制御部
　７　　制御部
　１０　　信号処理部
　１１　　欠陥検出部
　２０　　欠陥検出部
　２１　　検出部
　２２　　値化部
　２３　　照合部
　２４　　欠陥判別部
　２５　　記憶部
　２５ａ　　検出データ
　２５ｂ　　２値化データ
　２５ｃ　　登録形状データ
　１００　　基板
　１０１　　パネル
　２００-２０４　　アンド回路
　３００-３０４　　アンド回路
　４００-４０４　　アンド回路
　５００　　オア回路 DESCRIPTION OF SYMBOLS 1 Array inspection apparatus 2 Stage 3 Electron gun 4 Detector 5 Electron beam scanning control part 6 Stage drive control part 7 Control part 10 Signal processing part 11 Defect detection part 20 Defect detection part 21 Detection part 22 Quantification part 23 Verification part 24 Defect Discrimination unit 25 Storage unit 25a Detection data 25b Binary data 25c Registered shape data 100 Substrate 101 Panel 200-204 AND circuit 300-304 AND circuit 400-404 AND circuit 500 OR circuit

Claims (8)

  1. 　ＴＦＴ基板のパネルに所定電圧の検査信号を印加してアレイを駆動し、前記パネル上に荷電ビームを照射して走査し、当該荷電ビーム走査で検出される検出信号に基づいてＴＦＴ基板のアレイを検査するＴＦＴアレイ検査において、
    　前記荷電ビームの照射によってパネル上のサンプリング点の信号強度を検出する検出工程と、
    　前記検出工程で検出したサンプリング点の信号強度を２値化し、２値化画像を求める２値化工程と、
    　前記２値化工程で求めた２値化画像に含まれる形状を照合対象形状とし、当該照合対象形状と予め登録しておいた登録形状との形状を比較して照合を行う照合工程と、
    　前記照合工程の照合結果により、前記照合対象形状の中に前記登録形状が含まれるか否かを判別し、
    　前記照合対象形状の中に、前記登録形状が少なくとも一つ含まれている場合に当該照合対象形状を含むピクセルを欠陥と判別し、
    　前記照合対象形状の中に、登録された全ての登録形状の何れの登録形状も含まれていない場合に当該照合対象形状を含むピクセルを正常と判別する欠陥判別工程とを備え、
    　前記欠陥判別工程で欠陥と判別されたピクセルに対応するアレイを欠陥アレイとして検出することを特徴とする、ＴＦＴアレイ検査方法。     The array is driven by applying an inspection signal of a predetermined voltage to the panel of the TFT substrate, irradiating the panel with a charged beam, and scanning the array of the TFT substrate based on the detection signal detected by the charged beam scanning. In TFT array inspection to inspect,
    A detection step of detecting a signal intensity at a sampling point on the panel by irradiation of the charged beam;
    A binarization step for binarizing the signal intensity at the sampling point detected in the detection step to obtain a binarized image;
    A collation step in which the shape included in the binarized image obtained in the binarization step is a collation target shape, and the collation is performed by comparing the shape of the collation target shape with a registered shape registered in advance;
    According to the verification result of the verification process, it is determined whether or not the registered shape is included in the verification target shape,
    When at least one of the registered shapes is included in the matching target shape, a pixel including the matching target shape is determined as a defect,
    A defect determining step of determining that a pixel including the matching target shape is normal when none of the registered shapes of all registered shapes is included in the matching target shape;
    A TFT array inspection method, wherein an array corresponding to a pixel determined to be a defect in the defect determination step is detected as a defect array.
  2. 　前記２値化工程は、サンプリング点の信号強度と予め定めておいたしきい値とを比較し、前記サンプリング点に対応する位置に前記比較の結果に応じて２値を対応付けることにより２値化画像を形成することを特徴とする、請求項１に記載のＴＦＴアレイ検査方法。 The binarization step compares the signal intensity at the sampling point with a predetermined threshold value, and associates the binary value with the position corresponding to the sampling point according to the result of the comparison. The TFT array inspection method according to claim 1, wherein:
  3. 　前記照合工程は、
    　複数の登録形状を備え、当該複数の登録形状の中から選択した登録形状毎に照合対象形状との形状を比較することを特徴とする、請求項１又は２に記載のＴＦＴアレイ検査方法。     The verification process includes
    3. The TFT array inspection method according to claim 1, comprising a plurality of registered shapes, and comparing a shape with a matching target shape for each registered shape selected from the plurality of registered shapes. 4.
  4. 　前記照合工程は、
    　同一の照合対象形状について、前記複数の登録形状からの登録形状を選択する選択工程と、当該選択工程で選択した登録形状と照合対象形状との形状を比較する形状比較工程とを、欠陥判別工程において欠陥と判別されるまで繰り返すことを特徴とする、請求項３に記載のＴＦＴアレイ検査方法。     The verification process includes
    For the same matching target shape, a defect determination step includes a selection step of selecting a registered shape from the plurality of registered shapes, and a shape comparison step of comparing the registered shape selected in the selection step with the shape of the verification target shape. The TFT array inspection method according to claim 3, wherein the method is repeated until it is determined as a defect.
  5. 　ＴＦＴ基板のパネルに所定電圧の検査信号を印加してアレイを駆動し、前記パネル上に荷電ビームを照射して走査し、当該荷電ビーム走査で検出される検出信号に基づいてＴＦＴ基板のアレイを検査するＴＦＴアレイ検査において、
    　前記荷電ビームの照射によってパネル上のサンプリング点の信号強度を検出する検出部と、
    　前記検出部で検出したサンプリング点の信号強度を２値化し、２値化画像を求める２値化部と、
    　前記２値化部で求めた２値化画像に含まれる形状を照合対象形状とし、当該照合対象形状と予め登録しておいた登録形状との形状を比較して照合を行う照合部と、
    　前記照合部の照合結果により、前記照合対象形状の中に前記登録形状が含まれるか否かを判別し、
    　前記照合対象形状の中に、前記登録形状が少なくとも一つ含まれている場合に当該照合対象形状を含むピクセルを欠陥と判別し、

    　前記照合対象形状の中に、登録された全ての登録形状の何れの登録形状も含まれていない場合に当該照合対象形状を含むピクセルを正常と判別する欠陥判別部とを備え、
    　前記欠陥判別部で欠陥と判別されたピクセルに対応するアレイを欠陥アレイとして検出することを特徴とする、ＴＦＴアレイ検査装置。     The array is driven by applying an inspection signal of a predetermined voltage to the panel of the TFT substrate, irradiating the panel with a charged beam, and scanning the array of the TFT substrate based on the detection signal detected by the charged beam scanning. In TFT array inspection to inspect,
    A detection unit for detecting a signal intensity at a sampling point on the panel by irradiation of the charged beam;
    A binarization unit for binarizing a signal intensity of a sampling point detected by the detection unit to obtain a binarized image;
    A collation unit that performs collation by comparing a shape included in the binarized image obtained by the binarization unit as a collation target shape and comparing the collation target shape with a registered shape registered in advance;
    According to the verification result of the verification unit, it is determined whether or not the registered shape is included in the verification target shape,
    When at least one of the registered shapes is included in the matching target shape, a pixel including the matching target shape is determined as a defect,

    A defect discriminating unit that discriminates that a pixel including the target shape for comparison is normal when none of the registered shapes of all registered shapes are included in the target shape for verification;
    A TFT array inspection apparatus, wherein an array corresponding to a pixel determined to be a defect by the defect determination unit is detected as a defect array.
  6. 　前記２値化工程は、サンプリング点の信号強度と予め定めておいたしきい値とを比較し、前記サンプリング点に対応する位置に前記比較の結果に応じて２値を対応付けることにより２値化画像を形成することを特徴とする、請求項５に記載のＴＦＴアレイ検査装置。 The binarization step compares the signal intensity at the sampling point with a predetermined threshold value, and associates the binary value with the position corresponding to the sampling point according to the result of the comparison. The TFT array inspection apparatus according to claim 5, wherein the TFT array inspection apparatus is formed.
  7. 　前記照合部は、
    　複数の登録形状を備え、当該複数の登録形状の中から選択した登録形状毎に照合対象形状との形状を比較することを特徴とする、請求項５又は６に記載のＴＦＴアレイ検査装置。     The collation unit
    The TFT array inspection apparatus according to claim 5 or 6, wherein a plurality of registered shapes are provided, and a shape with a matching target shape is compared for each registered shape selected from the plurality of registered shapes.
  8. 　前記照合部は、
    　同一の照合対象形状について、前記複数の登録形状からの登録形状を選択する選択工程と、当該選択工程で選択した登録形状と照合対象形状との形状を比較する形状比較工程とを、欠陥判別工程において欠陥と判別されるまで繰り返すことを特徴とする、請求項７に記載のＴＦＴアレイ検査装置。     The collation unit
    For the same matching target shape, a defect determination step includes a selection step of selecting a registered shape from the plurality of registered shapes, and a shape comparison step of comparing the registered shape selected in the selection step with the shape of the verification target shape. The TFT array inspection apparatus according to claim 7, wherein the TFT array inspection apparatus repeats until it is determined as a defect in step 8.
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