Possibilistic fuzzy c-means algorithm for fingerprint image

Abstract

In this work, we proposed a method for fingerprint image segmentation based on possibilistic fuzzy c-means (PFCM) algorithm with an adaptive level set (ALS) method. In fingerprint recognition system, fingerprint segmentation is an important step. PFCM algorithm is a mixer of possibilistic c-means clustering (PCM) and fuzzy c-means clustering (FCM) algorithm. PFCM overcomes the noise sensitivity defect in FCM and coincident cluster problem in PCM. PFCM was used to generate an initial contour curve for level set method. PFCM algorithm is used to compute the fuzzy membership values of each pixel. Based on the above fuzzy membership values edge indicator function is redefined. By using the edge indicator function fingerprint segmentation was performed to extract the required regions for advance processing. Experimental results of proposed method showed significant improvement in the evolution of the level set function.