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Proceedings Paper

The problems of using ROC curve as the sole criterion in positive biometrics identification
Author(s): Yingzi Du; Chein-I Chang
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Paper Abstract

Receiver operating characteristic (ROC) curve is widely used in biometric identification. It is a plot of the detection power virus false alarm rate. It is an objective measure of accuracy. Positive biometrics identification is one-to-many match. ROC curve has been served as a "golden" criterion in measuring the accuracy of biometrics system for positive biometric identification. However, in this paper, we will analyze the problems of using ROC curve as the sole criterion in positive biometrics identification. From the view of detection and estimation theory, ROC curve only took concerns of system variance, and would not be able to detect the system bias, which could give wrong conclusion in evaluating system accuracy across multiple databases. ROC curve does not reflect the cost function, the database size, the quality of the image, and many other factors that are important in system performance and accuracy. We will use iris recognition as an example to discuss these issues. At the end, we will discuss some possible solutions to solve these problems.

Paper Details

Date Published: 2 May 2007
PDF: 9 pages
Proc. SPIE 6579, Mobile Multimedia/Image Processing for Military and Security Applications 2007, 65790K (2 May 2007); doi: 10.1117/12.719855
Show Author Affiliations
Yingzi Du, Indiana Univ.-Purdue Univ. Indianapolis (United States)
Chein-I Chang, Univ. of Maryland, Baltimore County (United States)


Published in SPIE Proceedings Vol. 6579:
Mobile Multimedia/Image Processing for Military and Security Applications 2007
Sos S. Agaian; Sabah A. Jassim, Editor(s)

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