X. Liang and T. Asano (Japan)
ordinary morphological operator (OMO), generalized morphological operator (GMO), structuring element (SE),strictness, Euclidean distance transform, useless component.
In this paper we propose a fast method for binary finger print image denoising that employs the generalized and ordinary morphological operators based on Euclidian dis tance transform. This method avoids quite a number of computational redundance. In particular, the computations of denosing step are restricted to a minimum number of pixels. The results show that applying this method on fin gerprint image with impulsive noise and useless compo nents yields a segmentation much closer to that of an expect for extracting the minutia accurately.
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