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DFT-DCT Combination Based Novel Feature Extraction Method for Enhanced Iris Recognition Read chapter Read first chapter

2017 | OriginalPaper | Chapter

Structural (Shape) Feature Extraction for Ear Biometric System

Authors : P. Ramesh Kumar, S. S. Dhenakaran

Published in: Proceedings of the International Conference on Signal, Networks, Computing, and Systems

Publisher: Springer India

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Abstract

The Ear Biometrics is an emerging modern human identification system, which is a passive biometrics system where the recognition of an individual is done without the knowledge of the human subject. This kind of passive biometrics system can help the image analyst to extract useful information feature for public surveillance system. The proposed article extracts structure (shape) features such as Area, Perimeter, Eccentricity, Elongation, Compactness, Horizontal Height, Vertical Height, Major Axis, Minor Axis, Circularity and Rectangularity of the human ear to construct an effective ear biometrics system.

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Literature
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Devesh Narayan, Sipi Dubey ‘A Survey Paper on Human Identification using Ear Biometrics’, International Journal of Innovative Science and Modern Engineering (IJISME), ISSN: 2319-6386, Volume-2 Issue-10, September 2014.
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Anika Pflug, Christoph Busch, ‘Ear Biometrics-A Survey of Detection, Feature Extraction and Recognition Methods’, IET Biometrics, Volume 1, Number 2, pages 114–129, June 2012.
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Abaza, A., Ross, A., Herbert, C., Harrison, M. A. F., and Nixon, M. S. 2011. ‘A Survey on Ear Biometrics’. ACM Trans. Embedded. Comput. Syst. 9, 4, 33 pages, Article 39, March 2010.
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Hurley, David J., Mark S. Nixon, and John N. Carter. “Automatic ear recognition by force field transformations.” Visual Biometrics (Ref. No. 2000/018), IEE Colloquium on. IET, 2000.
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Metadata
Title
Structural (Shape) Feature Extraction for Ear Biometric System
Authors
P. Ramesh Kumar
S. S. Dhenakaran
Copyright Year
2017
Publisher
Springer India
Book
Proceedings of the International Conference on Signal, Networks, Computing, and Systems

Print ISBN: 978-81-322-3590-3

Electronic ISBN: 978-81-322-3592-7

Copyright Year: 2017

DOI
https://doi.org/10.1007/978-81-322-3592-7_16