Machine vision method and apparatus for thresholding images of non-uniform materials
First Claim
1. In a machine vision method of thresholding a first image, the improvement comprising the step offor each of at least selected neighborhoods of plural pixels in the first image:
- generating a defocused value that is a statistical function of values of the plural pixels in that neighborhood,comparing that defocused value with one or more first thresholds and generating, based on that comparison, a first neighborhood threshold result for that neighborhood, wherein the one or more first thresholds are held constant for all neighborhoods,comparing that defocused value with one or more second thresholds and generating, based on that comparison, a second neighborhood threshold result for that neighborhood, and wherein the one or more second thresholds vary in accord with a region of the image in which that neighborhood is located, andgenerating a threshold image comprising any of the first and second neighborhood threshold results.
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Abstract
Machine vision inspection methods and systems according to the invention take an average (or other statistical measure) of pixel values within neighborhoods or groups of pixels within an image. The averages are compared with one or more thresholds and a result generated for each neighborhood. The results generated for all such neighborhoods can, for example, be used to identify defective regions in the acquired image, notwithstanding a high degree of intensity, brightness, color or contrast variation at the pixel level—e.g., of the type commonly occurring when imaging non-woven materials. Such methods and systems are advantageous because an originally acquired, high-resolution (non-defocused) image can be preserved and processed in parallel with a neighborhood-based defocused and thresholded image. Systems employing these methods achieve the thresholding capability of traditional defocused systems, while providing clear, detailed, high-resolution images for display or other analysis. Such systems provide this dual capability using image data acquired from a single camera or camera array.
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Citations
25 Claims
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1. In a machine vision method of thresholding a first image, the improvement comprising the step of
for each of at least selected neighborhoods of plural pixels in the first image: -
generating a defocused value that is a statistical function of values of the plural pixels in that neighborhood, comparing that defocused value with one or more first thresholds and generating, based on that comparison, a first neighborhood threshold result for that neighborhood, wherein the one or more first thresholds are held constant for all neighborhoods, comparing that defocused value with one or more second thresholds and generating, based on that comparison, a second neighborhood threshold result for that neighborhood, and wherein the one or more second thresholds vary in accord with a region of the image in which that neighborhood is located, and generating a threshold image comprising any of the first and second neighborhood threshold results. - View Dependent Claims (2, 3, 4, 5, 6)
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7. In a machine vision method of thresholding a first image, the improvement comprising the step of
for each of at least selected groups of plural image pixels in the first image; -
generating a defocused value that is a statistical function of values of the plural pixels in that group, comparing that defocused value with one or more thresholds and generating, based on that comparison, a group threshold result for that group, and generating a threshold image comprising the group threshold results for a plurality of groups of the first image. - View Dependent Claims (8, 9, 10, 11, 12, 13, 14)
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15. In a machine vision system of the type that thresholds a first image, the improvement comprising a filter used to calculate an average pixel value of an M-column by N-row neighborhood within the first image, the filter including
a down delay memory that holds each new image pixel value entering the filter for a specified period before outputting it, a down accumulator having J storage elements, where J is a number of columns in the first image, each element maintaining a sum of N rows of pixel values for a corresponding column of the first image, down accumulator logic, coupled with the down delay memory and with the down accumulator, the down accumulator logic adding each new pixel value to a sum maintained by the down accumulator for the column with which the new pixel value is associated, subtracting therefrom a pixel value output by the down delay memory, and storing a new down-sum result back into the down accumulator, a cross delay memory, coupled with the down accumulator logic, that holds each new down-sum for a specified period before outputting it, a cross accumulator that maintains a sum of a current M-column by N-row rectangular neighborhood, cross accumulator logic, coupled with the cross delay memory and with the cross accumulator, that adds each newly calculated down-sum to a sum maintained in the cross accumulator, subtracts therefrom a down-sum output by the cross delay memory, and stores a new cross-sum result back to the cross accumulator.
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20. In a machine vision inspection method that includes acquiring a first image and thresholding at least selected pixels in the image on a per pixel basis, the improvement comprising the steps of:
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digitally defocusing the image by generating, for each of at least selected neighborhoods of plural image pixels in the first image, a defocused, value that is an average of values of the plural pixels in that neighborhood, comparing that defocused value with one or more thresholds, and generating, based on that comparison, a neighborhood threshold result for that neighborhood, generating for each of at least selected pixels in the first image an additional result that is a function of (i) a neighborhood threshold result for a neighborhood which includes that pixel, (ii) a result determined by thresholding that pixel on a per pixel basis. - View Dependent Claims (21, 22, 23, 24, 25)
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Specification