Fingerprint Classification by using the Delaunay Triangles
Y. Suresh1, S. V. N Srinivasu2
1Y. Suresh, Research Scholar, Department of Computer Science & Engineering, Acharya Nagarjuna University, Andhra Pradesh, India.
2Dr S. V. N Srinivasu, Professor, Department of Computer Science & Engineering, Narasaraopet, Andhra Pradesh, India.
Manuscript received on 10 December 2018 | Revised Manuscript received on 17 December 2018 | Manuscript Published on 30 December 2018 | PP: 268-271 | Volume-8 Issue- 2S December 2018 | Retrieval Number: BS2715128218/19©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: The use of biometrics has increased drastically with the evolution in hardware and software technology. Matching of finger prints are used for two types of system is used for two types of applications; one is finger print verification and another one is finger print identification. The fingerprint identification is computationally expensive one. In this paper we are proposing a approach for fingerprint classification and our main contribution in this paper is we consider the cost of minimums spanning tree constructed using the set of points represents the ridge bifurcation of ridge endings of the fingerprint and also we considered the special points which are participating in more than s triangles in Delaunay triangulation.
Keywords: Biometrics, Finger prin, WFMT, Delaunay Triangle.
Scope of the Article: Classification