Improved Fingerprint Image Segmentation Approaches
Y. Suresh1, S.V.N Sreenivasu2, Ch. Anuradha3
1Y. Suresh, Research Scholar, Department of Computer Science & Engineering, Acharya Nagarjuna University, Guntur (A.P), India.
2Dr S.V.N. Sreenivasu, Professor, Department of Computer Science & Engineering, Narasaraopeta Engineering College, Narasaraopeta, Guntur (A.P), India.
3Ch. Anuradha, Assistant Professor, Department of CSE, VR Siddhartha Engineering College, Vijayawada (A.P), India.
Manuscript received on 07 March 2019 | Revised Manuscript received on 20 March 2019 | Manuscript published on 30 March 2019 | PP: 348-351 | Volume-8 Issue-5, March 2019 | Retrieval Number: E3220038519/19©BEIESP
Open Access | Ethics and Policies | Cite | Mendeley | Indexing and Abstracting
© 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: The quality of fingerprint or fingerprint verification depends on the quality of the fingerprint image. Most of the fingerprint management algorithms depend on the features which are extracted based on the minutiae of the fingerprints. The quality of minutiae is depends on how good the fingerprint images. The background and foreground of the images are also effect the results of the fingerprint images. Fingerprint segmentation algorithms are used to extract the finger print image from background. In this paper we are presenting the two fingerprint segmentation algorithms which are the modifications of existing mean and variance based approach and gradient based approach.
Keyword: Bio-Metric. Fingerprint, Image Segmentation.
Scope of the Article: Signal and Image Processing