Mura detection apparatus and method

A method identifying a Mura defect on a substrate, comprising steps of:

• 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.

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:

• 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.

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.

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:

• 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.

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:

• 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.

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:

• 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.

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.