ENGINEERING & TECHNOLOGY IN INDIA

Strength for Today and Bright Hope for Tomorrow

Volume 1:2 March 2016

Chief Editor
Dr. D. Nagarathinam, M.E., Ph.D.

Editors
         Dr. P. N. Rajnarayanan, M.E., Ph.D.
         Dr. K. Sudalaimani, M.E., Ph.D.
         Dr. S. Ramanathan, Ph.D. (Chemistry)

Language and Style Advisors
         G. Baskaran, Ph.D.
         Sam Mohanlal, Ph.D.

Executive Editor
         M. S. Thirumalai, Ph.D.

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Copyright © 2015
M. S. Thirumalai

Person Recognition Using Ear images

R. Revathi and M. Bhavani

Abstract

We present a complete three-dimensional (3-D) ear recognition system combining local and holistic features in a computationally efficient manner. The system is comprised of four primary components, namely: 1) ear image segmentation; 2) local feature extraction and matching; 3) holistic feature extraction and matching; and 4) a fusion framework combining local and holistic features at the match score level. For the segmentation component, we introduce a novel shape-based feature set, termed the Histograms of Indexed Shapes (HIS), to localize a rectangular region containing the ear. For the local feature extraction and representation component, we extend the HIS feature descriptor to an object-centered 3-D shape descriptor, the Surface Patch Histogram of Indexed Shapes (SPHIS), for local ear surface representation and matching. For the holistic matching component, we introduce a voxelization scheme for holistic ear representation from which an efficient, voxel-wise comparison of gallery-probe model pairs can be made. The match scores obtained from both the local and holistic matching components are fused to generate the final match scores.

Keywords: Histograms of Indexed Shapes, Surface Patch Histogram of Indexed Shapes

INTRODUCTION

BIOMETRICS deals with recognition of individuals based on their physiological or behavioral characteristics. Researchers have done extensive studies on biometrics such as fingerprint, face, palm print, iris, and gait. Ear, a viable new class of biometrics, has certain advantages over face and fingerprint, which are the two most common biometrics in both academic research and industrial applications. For example, the ear is rich in features; it is a stable structure that does not change much with age and it does not change its shape with facial expressions. Furthermore, ear is larger in size compared to fingerprints but smaller as compared to face and it can be easily captured from a distance without a fully cooperative subject although it can sometimes be hidden with hair, cap, turban, muffler, scarf, and earrings.

This is only the beginning part of the article. PLEASE CLICK HERE TO READ THE ENTIRE ARTICLE IN PRINTER-FRIENDLY VERSION.

R. Revathi
Assistant Professor in Computer Science & Engineering
Theni Kammavar Sangam College of Technology
Theni 625 534
Tamilnadu
India
revavyas@gmail.com

M. Bhavani
Assistant Professor in Computer Science & Engineering
Theni Kammavar Sangam College of Technology
Theni 625 534
Tamilnadu
India
gmbhavani1990@gmail.com

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