Mura detection apparatus and method
First Claim
1. A method for detecting Mura defects on a substrate for a flat panel display, the method comprising the steps of:
- a) acquiring an image of a first plurality of pixels in at least a portion of the substrate, the image including values of pixels from the first plurality of pixels;
b) enhancing differences in the values of pixels in the first plurality of pixels to form an enhanced image, the enhanced image including values of pixels from the first plurality of pixels;
c) thresholding the enhanced values of pixels from the first plurality of pixels to form a thresholded image, the thresholded image including thresholded values of pixels from the first plurality of pixels;
d) identifying a second plurality of pixels from the first plurality of pixels corresponding to at least one blob within the thresholded image;
e) identifying a third plurality of pixels from the first plurality of pixels corresponding to an annular region around at least one blob within the thresholded image;
f) comparing values of the second plurality of pixels to values of the third plurality of pixels;
g) determining a Mura defect in response to the comparison step.
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Abstract
A method and apparatus for identifying and classifying pixel defects, and in particular Mura defects using digital processing techniques. The present method includes steps of acquiring an image with a Mura defect, and performing a Laplacian convolution on the image to enhance the Mura defect against background illumination. A step of thresholding the Mura defect against the background illumination is also provided. The thresholded Mura defect is compared against the original Mura defect to define statistical parameters of the original Mura defect. An annular region is defined around the periphery of the Mura defect. Statistics of the annular region defines statistics for background illumination as compared to the original Mura defect. The statistics from the Mura defect are then compared to the background illumination statistics for Mura defect classification and analysis.
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Citations
45 Claims
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1. A method for detecting Mura defects on a substrate for a flat panel display, the method comprising the steps of:
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a) acquiring an image of a first plurality of pixels in at least a portion of the substrate, the image including values of pixels from the first plurality of pixels; b) enhancing differences in the values of pixels in the first plurality of pixels to form an enhanced image, the enhanced image including values of pixels from the first plurality of pixels; c) thresholding the enhanced values of pixels from the first plurality of pixels to form a thresholded image, the thresholded image including thresholded values of pixels from the first plurality of pixels; d) identifying a second plurality of pixels from the first plurality of pixels corresponding to at least one blob within the thresholded image; e) identifying a third plurality of pixels from the first plurality of pixels corresponding to an annular region around at least one blob within the thresholded image; f) comparing values of the second plurality of pixels to values of the third plurality of pixels; g) determining a Mura defect in response to the comparison step. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 44, 45)
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17. A method identifying a Mura defect on a substrate, comprising steps of:
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acquiring an image comprising a blob defined onto a background image and storing the image as frame data, the blob being defined by first pixels and the background image being defined by second pixels; thresholding the image to create a binary representation of the blob and the background image, the binary representation being defined by the first pixels at a first value and the second pixels at a second value; calculating an average blob pixel value of the blob from pixels in the image corresponding to the blob; dilating the binary representation of the blob by converting a portion of the second pixels at the second value adjacent to the first pixels at the first value to second pixels at the first value, the dilating step defining a dilated binary representation of the blob; performing an XOR of the binary representation of the blob with the dilated binary representation of the blob to define an annular region comprising the second pixels at the first value; calculating an average background image pixel value of the background image from pixels in the image corresponding to the annular region; and comparing the average background image pixel value with the average blob pixel value to identify a Mura defect.
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18. A computer system for detecting Mura defects on a substrate for a flat panel display, the substrate including a first plurality of pixels, the computer system comprising:
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an image acquisition device for acquiring an image of at least a portion of the substrate, the portion including a second plurality of pixels, the image including values of pixels in the second plurality of pixels; an enhancer for enhancing differences in the values of pixels in the second plurality of pixels to form an enhanced image, the enhanced image including enhanced values of pixels in the second plurality of pixels; a thresholder for thresholding the enhanced values of pixels in the second plurality of pixels to form a thresholded image, the thresholded image including thresholded values of pixels in the second plurality of pixels; an identifier for identifying a third plurality of pixels forming at least one blob within the portion of the substrate in response to the thresholded image; a comparator for comparing values of the third plurality of pixels to values of pixels corresponding to an annular region around the at least one blob; and a determiner coupled to the comparator for determining a Mura defect. - View Dependent Claims (19, 20)
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21. A computer system for detecting Mura defects on a substrate for a flat panel display, the substrate including a first plurality of pixels, the computer system comprising:
a computer-readable memory including; code that directs an image acquisition device to acquire an image of at least a portion of the substrate, the portion including a second plurality of pixels, the image including values of pixels in the second plurality of pixels; code that enhances differences in the values of pixels in the second plurality of pixels to form an enhanced image, the enhanced image including enhanced values of pixels in the second plurality of pixels; code that thresholds the enhanced values of pixels in the second plurality of pixels to form a thresholded image, the thresholded image including thresholded values of pixels in the second plurality of pixels; code that identifies a third plurality of pixels forming at least one blob within the portion of the substrate in response to the thresholded image; code that compares values of the third plurality of pixels to values of pixels corresponding to an annular region around the at least one blob; and code that determines a Mura defect in response to the comparison step. - View Dependent Claims (22, 23)
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24. A method for detecting Mura defects in a substrate for a liquid crystal display, the substrate having a plurality of pixels, the method comprising the steps of:
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acquiring an image of the substrate; creating a plurality of subsampled images from the image; determining locations of potential Mura defects in the substrate in response to locations of Mura defects in each of the plurality of subsampled images; and determining Mura defects in the substrate in response to the locations of potential Mura defects in each of the plurality of subsampled images. - View Dependent Claims (25, 26, 27, 28, 29, 30, 31, 41, 42, 43)
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32. A method for detecting Mura defects in a substrate for a liquid crystal display, the substrate having a plurality of pixels, the method comprising the steps of:
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acquiring an image of the substrate; applying a plurality of filters individually to the image to form a plurality of filtered images, the plurality of filters having different frequency cut-offs; thresholding each of the plurality of filtered images to form a plurality of thresholded images; and determining locations of potentially defective pixels in the substrate in response to locations of pixels in each of the plurality of thresholded images exceeding a threshold value; and detecting Mura defects in the substrate in response to the locations of the potentially defective pixels in the substrate. - View Dependent Claims (33, 34, 35, 36, 37)
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38. A computer system for detecting Mura defects in a substrate for a liquid crystal display, the substrate having a plurality of pixels, the computer system comprising:
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an image acquiring device for acquiring an image of the substrate; a sampler for creating a plurality of subsampled images from the image; a pixel determiner for determining locations of potentially defective pixels in the substrate in response to locations of pixels in each of the plurality of subsampled images having anomalous values; and a Mura determiner for determining Mura defects in the substrate in response to the locations of potentially defective pixels determined in the substrate. - View Dependent Claims (39)
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40. A computer system including a computer program for detecting Mura defects in a substrate for a liquid crystal display, the substrate having a plurality of pixels, the computer system comprising:
a computer-readable memory including; code that directs an image acquisition device to acquire an image of the substrate; code that creates a plurality of subsampled images from the image; code that determines locations of potentially defective pixels in the substrate in response to locations of pixels in each of the plurality of subsampled images having anomalous values; and code that determines Mura defects in the substrate in response to the locations of potentially defective pixels determined in the substrate.
Specification