Abstract
AFIS (automated fingerprint identification system) is very popular now days for biometric security. Fingerprint classification plays a key role in identifying fingerprints and also helps in fingerprint matching. This paper presents a new classification technique based on the detection of singular points (core and delta points). This fingerprint classification technique consists of four steps. In the first step, preprocessing (segmentation and normalization) of input fingerprint image is done. In the second step, fine orientation field of image is estimated. In the third step, singular points are located using modified Poincare index technique. In the fourth step, classification is done on the basis of singular points. The proposed technique was tested on FVC2004 database and the results show a significant improvement in reducing the misclassification errors.
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