Fingerprint Verification using Statistical and Co-Occurrence Matrix Features
Shweta Ujwal Bagadi1, Giridhar P. Jain2
1Mrs. Shweta Ujwal Bagadi, Assistant Professor, Department of Electronics and Telecommunication Engineering, Walchand Institute of Technology, Solapur (Maharashtra), India.
2Mr. Giridhar P. Jain, Assistant Professor, Department of Electronics and Telecommunication Engineering, Walchand Institute of Technology, Solapur (Maharashtra), India.
Manuscript received on 10 December 2014 | Revised Manuscript received on 20 December 2014 | Manuscript Published on 30 December 2014 | PP: 72-75 | Volume-4 Issue-7, December 2014 | Retrieval Number: G1909124714/14©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Fingerprint identification is one of the most well-known and publicized biometrics. Because of their uniqueness and consistency over time, fingerprints have been used for identification for over a century, more recently becoming automated (i.e. a biometric) due to advancement in computing capabilities. Fingerprint identification is popular because of the inherent ease in acquisition, the numerous sources (ten fingers) available for collections, and their established use and collections by law enforcement and immigration. Fingerprint verification is one of the most reliable personal identification method and it plays a very important role in forensic and civilian applications. However, manual fingerprint verification is so tedious, time-consuming, and expensive that it is incapable of meeting today’s increasing performance requirements. Hence, an automatic fingerprint identification system (AFIS) is widely needed. Proposed system describes the design and implementation of an off-line fingerprint verification system using wavelet transforms. In this method, matching is done between the input image and the stored template without resorting to exhaustive search using the extracted feature.
Keywords: Fingerprint Verification, Wavelet Transform, Automatic Fingerprint Identification System (AFIS),
Scope of the Article: System Integration