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.
Zheng Ma Mei Xie Chengpu Yu
School of Communication and Information Engineering, University of Electronic Science and Technology of China, Chengdu, China
国际会议
2009国际通信电路与系统学术会议(ICCCAS 2009)(2009 International Conference on Communications，Circuits and Systems)
成都
英文
566-568
2009-07-23（万方平台首次上网日期，不代表论文的发表时间）