Fingerprint Recognition System based on Orientation and Texture Features

Abstract

Fingerprint recognition is one of the most well-known and publicized biometrics for personal identification. Fingerprints exhibit oriented texture-like patterns. The texture information of the fingerprint can be used for fingerprint matching. Gabor filters can optimally capture global and local texture information even from poor-quality or incomplete images. But Gabor filterbank-based approach use only texture information for fingerprint recognition and it is not robust to image distortion and rotation. In this paper, a hybrid fingerprint matching algorithm is developed for identifying the low quality fingerprint images by combining orientation features and the local texture pattern obtained using a bank of Gabor filters. The proposed matching approach is compared with the filterbank-based approach, and the proposed system produces a much improved matching performance by combining the orientation features to the filterbank-based features.