A Combination Fingerprint Classifier
IEEE Transactions on Pattern Analysis and Machine Intelligence - Graph Algorithms and Computer Vision
Handbook of Fingerprint Recognition
Handbook of Fingerprint Recognition
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Automatic fingerprint classification provides an important indexing scheme to facilitate efficient matching in large-scale fingerprint databases Fingerprints are classified mainly based on their print textures A fingerprint texture pattern across a predefined path on the finger surface can be viewed as a Markov chain The orientation field of a fingerprint can be modeled with a pseudo 2D Hidden Markov Model (HMM), which can also be called embedded Hidden Markov Model A novel method of fingerprint classification based on embedded HMM is described in this paper., Compared with conventional method, the novel fingerprint classification approach is simpler and more robust, since it is less sensitive to the noise and distortions in fingerprint images and the pretreatment processes such as image enhancement and thinning, minutiae and singular point extraction etc can be skipped.