Garber Filter Based Hybridized Algorithm For Feature Extraction From A Fuzzy Fingerprint Image
S. Suganthi Devi
S. Suganthi Devi, Department of Computer Engineering, Srinivasa Subbaraya Polytechnic College, puthur, Nagappatinam, Tamil nadu, India.
Manuscript received on September 23, 2019. | Revised Manuscript received on October 15, 2019. | Manuscript published on October 30, 2019. | PP: 7251-7257 | Volume-9 Issue-1, October 2019 | Retrieval Number: A1838109119/2019©BEIESP | DOI: 10.35940/ijeat.A1838.109119
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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: Proper extraction of fingerprint functions is important for matching the fingerprint algorithms. Different pieces of fingerprint information, such as rigid orientation and frequency should be taken into consideration for good results. The quality of a fingerprint image is often required to improve the function extraction process. In this article we introduce a Hybridized Garber Filter Algorithm (HGFA) for Fuzzy Fingerprint Image Feature Extraction for effective fingerprint recognition. This paper describes a fingerprint detection system consisting of image preprocessing, filtration, extraction and recognition matching. Preprocessing of images includes normalization based on median value and variation. In order to prepare the fingerprint image further processing, Gabor filters are extracted. The Poincaré index with a partitioning technique is used for the identification of a particular point. The extraction of the ridge line is shown and also the minute extraction with CN algorithm
Keywords: This paper describes a fingerprint detection system consisting of image preprocessing, filtration, extraction and recognition matching.