Segmentation and enhancement of fingerprint images using K-means, fuzzy C-mean algorithm and statistical features

Fingerprint segmentation is a crucial and important step of image processing in automatic fingerprint´s identification. The aim of the segmentation of fingerprint is to extract the region of interest; foreground; and to exclude the background regions, in order to reduce the time of subsequent processing and to avoid detecting false features. This paper presents a new approach of segmentation and enhancement of fingerprints. This approach is based on the fuzzy c-means algorithm (FCM), statistical features and frame differences Experimental results show the effectiveness and robustness of the proposed methods. We have tested this technique on 100 images taken from database FVC2004.