Co-occurrence matrix features for fingerprint verification

Abstract

In this paper, an enhanced image-based fingerprint verification algorithm is presented that improves matching accuracy by overcoming the shortcomings of previous methods due to poor image quality. It reduces multi-spectral noise by enhancing a fingerprint image to accurately and reliably determine a reference point and then extracts a 129 X 129 block, making the reference point its center. From the 12 co-occurrence matrices, four statistical descriptors are computed. Experimental results show that the proposed method has more accurate and performance than other methods the average false acceptance rate (FAR) is 0.48% and the average false rejection rate (FRR) is 0.18%.