Skeletonization of Fingerprint Based-on Modulus Minima of Wavelet Transform
This paper presents a direct and general algorithm based on the local minima of wavelet transform moduli for computing skeletons of fingerprint objects. The development of the method is inspired by some desirable characteristics of the local minimum of wavelet transform moduli. These significant properties are substantially investigated and corresponding results are mathematically proven with respect to a special wavelet function. A minima-modulus-theoretic algorithm is developed to extract skeletons of the fingerprint with a wide variety of width structures. We tested the algorithm on the natural fingerprint image with a variety of widths structures in gray image and binary image. Experimental results show that the skeletons of object obtained from the proposed algorithm overcome greatly some of the undesirable effects and limitations of previous methods, moreover, the proposed algorithm is insensitive to noise as well as efficient computability.
KeywordsWavelet Transform Wavelet Function Single Pixel Fingerprint Image Skeleton Curve
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