Patent ID: 8750637

Claim:
A computer implemented method of processing a blurred barcode image comprising multiple pixels, said method comprising the steps of: a) providing an image representation of said blurred barcode image comprising multiple grayscale values associated with different pixel positions of said blurred barcode image; b) providing a kernel having a kernel length; c) deconvoluting said image representation based on said kernel to get a deconvoluted representation of said blurred barcode image; d) calculating a barcode similarity measure for said deconvoluted representation, whereby said barcode similarity measure is indicative of how close a distribution of said grayscale values of said deconvoluted representation is to an optimal distribution of grayscale values for a barcode image, in which said grayscale values for said barcode image are distributed among a first value set and a second value set where said first value set and said second value said have minimum variance and an average grayscale value of said first value set has maximally large distance to an average grayscale value of said second value set; e) repeating said steps b) to d) for multiple different kernels; and f) selecting a kernel, among said multiple different kernels, resulting in the deconvoluted representation that is closest to a barcode image as determined based on said barcode similarity measures; wherein said calculating step d) comprises the steps of: calculating an average value of said grayscale values of said deconvoluted representation; organizing said grayscale values of said deconvoluted representation into a first set comprising grayscale values of said deconvoluted representation that are smaller than said average value of said grayscale values of said deconvoluted representation and a second set comprising grayscale values of said deconvoluted representation that are larger than said average value of said grayscale values of said deconvoluted representation; calculating a distribution representative parameter for said first set and a distribution representative parameter for said second set; calculating an average grayscale value of said first set and an average grayscale value of said second set; and calculating said barcode similarity measure based on said distribution representative parameter of said first set and said distribution representative parameter of said second set and based on a magnitude representation of a difference between said average grayscale value of said first set and said average grayscale value of said second set.