Detecting fingerprint minutiae by run length encoding scheme

Many approaches to minutiae extraction have already been proposed for automatic fingerprint matching, and most transform fingerprint images into binary images through state-of-the-art algorithms and submit the binary image to a thinning process. However, this paper proposes an original technique for extracting minutiae based on representing the ridge structure of a fingerprint image as a run length code (RLC). The essential idea is to detect minutiae by searching for the termination points or bifurcation points of ridges in the RLC, rather than in a fingerprint image. Experimental results and a comparative analysis show that the proposed method is fairly reliable and faster than a conventional thinning-based method.