A fingerprint indexing scheme with robustness against sample translation and rotation

Abstract

Automatic fingerprint identification systems (AFIS) are getting prevalent around the world, and the size of fingerprint databases involved in AFIS is continuously growing. Thus, studying fingerprint indexing algorithms is desirable in order to facilitate the search process in a large-scale database. In this paper, we firstly propose a feature extraction method to generate a binary template based on minutia information. A fingerprint indexing is designed by combining this binary template and Locality Sensitive Hashing indexing algorithm developed in a state-of-the-art fingerprint indexing method (minutia cylinder-code based indexing method). Experiments have been conducted on several public databases with different settings. The results show that the proposed approach achieves competitive performance or even better performance when benchmarked to the state-of-the-art fingerprint indexing methods.