Implementation of Fingerprint Recognition System using Minutiae Score Matching
K. V. Krishnam Raju1, P. Nishmitha2, P. Mounika3, N. Ajeeth4, V. Krishna Sandeep5, N. Kishore Raju6
1K. V. Krishnam Raju, B.Tech, M.Tech, Department of Computer Science and Engineering, Jawaharlal Nehru Technological University, Hyderabad (Telangana), India.
2P. Nishmitha Pursuing B.Tech, Department of Computer Science and Engineering, Andhra University, Visakhapatnam (Andhra Pradesh), India.
3P. Mounika Pursuing B.Tech, Department of Computer Science and Engineering, Andhra University, Visakhapatnam (Andhra Pradesh), India.
4N. Ajeeth Pursuing B.Tech, Department of Computer Science and Engineering, Andhra University, Visakhapatnam (Andhra Pradesh), India.
5V. Krishna Sandeep Pursuing B.Tech, Department of Computer Science and Engineering, Andhra University, Visakhapatnam (Andhra Pradesh), India.
6N. Kishore Raju Pursuing B.Tech, Department of Computer Science and Engineering, Andhra University, Visakhapatnam (Andhra Pradesh), India.
Manuscript received on 11 May 2019 | Revised Manuscript received on 05 June 2019 | Manuscript Published on 15 June 2019 | PP: 62-67 | Volume-8 Issue-1S3 June 2019 | Retrieval Number: A10120681S319/2019©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: In this computerized world, the prominent biometric technique used to recognise a person is known as fingerprint. A systematic combination of ridges, whorls and furrows in the outer layer of finger is known as fingerprint. Fingerprints vary from person to person but permanent. The aim of this paper is to establish fingerprint identification system that is based on the method called minutiae score matching. The process of the system includes image enhancement, binarization, thinning, minutiae score extraction. Image enhancement and binarization techniques are applied on fingerprint image to get good minutiae points. Thinning is used to convert image to one pixel width . Extract the minutiae points from thinned image. Using these points, find the real minutiae points. No match is perfect in both verification and identification. Therefore, biometric systems are designed to check whether match is found or not, based on a threshold value which is a predefined number. The score that is generated by using real minutiae points is compared to threshold value to found a match or no-match.
Keywords: Image Enhancement, Binarization, Thinning, Minutiae Score Extraction.
Scope of the Article: Pattern Recognition