Ear Recognition using Feature Fuzzy Matching
Kavitha Jaba Malar R1, Joseph Raj V2

1Kavitha Jaba Malar R, Research Scholar, Mother Teresa Women’s University, Kodaikanal, India.
2Dr. Joseph Raj V, Department of Computer Science , Kamaraj College, Manonmaniam Sundaranar University, Thoothukudi, India.
Manuscript received on November 10, 2014. | Revised Manuscript Received on November 12, 2014. | Manuscript published on November 18, 2014. | PP: 05-08 | Volume-1 Issue-12, November 2014.
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© The Authors. Published By: 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: This paper proposes a novel method, a Fuzzy Feature Match (FFM) based on a triangle feature set to match the ear. The ear is represented by the fuzzy feature set. The fuzzy features set similarity is used to analyze the similarity among ears. Accordingly, a similarity vector pair is defined to illustrate the similarities between two ears. The FFM method shows the similarity vector pair to a normalized value which quantifies the overall image to image similarity. The algorithm has been evaluated with Computer Education and Training Society (CETS) students and staff members’ ear database. Experimental results confirm that the proposed FFM based on the triangle feature set is a reliable and effective algorithm for ear matching.
Keywords: Extraction, Ear recognition, Fuzzy features, Matching, Similarities, Triangularization.