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Proceedings Paper

Challenging ocular image recognition
Author(s): V. Paúl Pauca; Michael Forkin; Xiao Xu; Robert Plemmons; Arun A. Ross
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Paper Abstract

Ocular recognition is a new area of biometric investigation targeted at overcoming the limitations of iris recognition performance in the presence of non-ideal data. There are several advantages for increasing the area beyond the iris, yet there are also key issues that must be addressed such as size of the ocular region, factors affecting performance, and appropriate corpora to study these factors in isolation. In this paper, we explore and identify some of these issues with the goal of better defining parameters for ocular recognition. An empirical study is performed where iris recognition methods are contrasted with texture and point operators on existing iris and face datasets. The experimental results show a dramatic recognition performance gain when additional features are considered in the presence of poor quality iris data, offering strong evidence for extending interest beyond the iris. The experiments also highlight the need for the direct collection of additional ocular imagery.

Paper Details

Date Published: 17 May 2011
PDF: 13 pages
Proc. SPIE 8029, Sensing Technologies for Global Health, Military Medicine, Disaster Response, and Environmental Monitoring; and Biometric Technology for Human Identification VIII, 80291V (17 May 2011); doi: 10.1117/12.885386
Show Author Affiliations
V. Paúl Pauca, Wake Forest Univ. (United States)
Michael Forkin, Wake Forest Univ. (United States)
Xiao Xu, Wake Forest Univ. (United States)
Robert Plemmons, Wake Forest Univ. (United States)
Arun A. Ross, West Virginia Univ. (United States)


Published in SPIE Proceedings Vol. 8029:
Sensing Technologies for Global Health, Military Medicine, Disaster Response, and Environmental Monitoring; and Biometric Technology for Human Identification VIII
B. V. K. Vijaya Kumar; Sárka O. Southern; Kevin N. Montgomery; Salil Prabhakar; Arun A. Ross; Carl W. Taylor; Bernhard H. Weigl, Editor(s)

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