Abstract
Aiming at an efficient edge extraction method for blurry digital radiography (DR) image of large size, local binary pattern (LBP) is improved by embedding an H function and a counting scheme, so-called H-LBP. With the aid of similarity distance and the H function, H-LBP can extract surrounding information discriminatively. With the help of counting scheme that records the number of pixels whose values are equal to or greater than that of the centric one, H-LBP can reduce noises and blurring. Experiments on blurry DR images and other images show that, compared with the Canny method, a fusion method called FL-fusion in this paper, and LBP operator, H-LBP extracts edges containing much more details.
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