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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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First Claim