Fingerprint segmentation based on PCNN and morphology

As an important step in an automatic fingerprint recognition system, fingerprint segmentation aims to extract the foreground of a fingerprint image in an efficient way. In this paper, an initiative algorithm for fingerprint segmentation is presented. First, the model of Pulse Coupled Neural Networks (PCNN) is utilized to binarize the fingerprint image. Then, morphological methods are adopted to obtain compact clusters of the binary fingerprint image. Since there might be other interfering regions after morphological operation, we also use the labeling method to find the largest compact cluster as the foreground region of the fingerprint image. Experimental results show that this method is robust to the complicated backgrounds of fingerprint images while keeping a smooth contour of the foreground region.