A Novel Dynamic Fingerprint Segmentation Method Based on Fuzzy C-Means and Genetic Algorithm

Abstract

In automatic fingerprint identification system (AFIS), fingerprint segmentation plays a crucial role in improving detection accuracy and reducing the computation time of feature extraction. With the goal of refining performance of AFIS, in this paper, we investigate a novel dynamic fingerprint segmentation algorithm. The proposed algorithm is based on the existed dynamic image segmentation algorithm using fuzzy c-means (FCM) and genetic algorithm. Specifically, relying on different gray level of histogram and improved post-processing method, we establish a well-performed fingerprint segmentation system. The extensive results from our empirical experiments demonstrate the high performance of our proposed dynamic fingerprint segmentation algorithm, and its better performance than other competing approaches.