GLCM-based fingerprint recognition algorithm

• Published in: 2011 4th IEEE International Conference on Broadband Network and Multimedia Technology pp. 207 - 211
• Main Authors: Ali, A., Xiaojun Jing, Saleem, N.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.10.2011
• Subjects: Cities and towns; Classification algorithms; Coherence; Coherence Diffusion; Filtering; Fingerprint recognition; GLCM; Image recognition; Indexes; KNN Classifier
• ISBN: 9781612841588; 1612841589
• DOI: 10.1109/ICBNMT.2011.6155926

An efficient and reliable fingerprint recognition system is the fundamental need of contemporary living. Beside forensic use, it has been deployed in a large number of commercial applications recently. In this paper, a new method for fingerprint recognition is introduced. The Core point is found initially using Poincare Index method. The dominant fingerprint region around the core point is selected and enhanced using the Diffusion Coherence Technique. The Gray level Co-occurrence Matrix (GLCM) is then applied to find out the fingerprint most significant statistical descriptors. Finally the K-Nearest Neighbor (KNN) Classifier is adopted for the recognition of unknown fingerprint images. The proposed algorithm is tested on images from FVC 2002 public domain database DB1. The experimental results demonstrate the improved performance of the algorithm.