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15 November 2007 Fingerprint image segmentation based on multi-features histogram analysis
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Proceedings Volume 6786, MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition; 678640 (2007) https://doi.org/10.1117/12.750687
Event: International Symposium on Multispectral Image Processing and Pattern Recognition, 2007, Wuhan, China
Abstract
An effective fingerprint image segmentation based on multi-features histogram analysis is presented. We extract a new feature, together with three other features to segment fingerprints. Two of these four features, each of which is related to one of the other two, are reciprocals with each other, so features are divided into two groups. These two features' histograms are calculated respectively to determine which feature group is introduced to segment the aim-fingerprint. The features could also divide fingerprints into two classes with high and low quality. Experimental results show that our algorithm could classify foreground and background effectively with lower computational cost, and it can also reduce pseudo-minutiae detected and improve the performance of AFIS.
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Peng Wang and Youguang Zhang "Fingerprint image segmentation based on multi-features histogram analysis", Proc. SPIE 6786, MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition, 678640 (15 November 2007); https://doi.org/10.1117/12.750687
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