Title :
Possibilistic fuzzy c-means algorithm for fingerprint image
Author :
Raghotham, R.G. ; Yugander, P. ; Sheshagiri, B.J. ; Rameshwar, R.R.
Author_Institution :
Dept. of Electron. & Commun. Eng., Kakatiya Univ., Warangal, India
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.
Keywords :
computational geometry; feature extraction; fingerprint identification; fuzzy set theory; image segmentation; pattern clustering; possibility theory; ALS; PFCM algorithm; adaptive level set method; coincident cluster problem; edge indicator function fingerprint segmentation; fingerprint image segmentation; fingerprint recognition system; fuzzy membership value computation; initial contour curve generation; level set function method; noise sensitivity defect; possibilistic fuzzy c-means clustering algorithm; Bridges; Image recognition; Image segmentation; Mixers; FCM; Image segmentation; PCM; Possibilistic FCM; adaptive level set (ALS) method;
Conference_Titel :
Devices, Circuits and Systems (ICDCS), 2012 International Conference on
Conference_Location :
Coimbatore
Print_ISBN :
978-1-4577-1545-7
DOI :
10.1109/ICDCSyst.2012.6188738
