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Efficient Eye Location for Biomedical Imaging using Two-level Classifier Scheme  

Nam, Mi-Young (Intelligent technology Laboratory, Dept. of Computer Science & Engineering, Inha University)
Wang, Xi (Intelligent technology Laboratory, Dept. of Computer Science & Engineering, Inha University)
Rhee, Phill-Kyu (Intelligent technology Laboratory, Dept. of Computer Science & Engineering, Inha University)
Publication Information
International Journal of Control, Automation, and Systems / v.6, no.6, 2008 , pp. 828-835 More about this Journal
Abstract
We present a novel method for eye location by means of a two-level classifier scheme. Locating the eye by machine-inspection of an image or video is an important problem for Computer Vision and is of particular value to applications in biomedical imaging. Our method aims to overcome the significant challenge of an eye-location that is able to maintain high accuracy by disregarding highly variable changes in the environment. A first level of computational analysis processes this image context. This is followed by object detection by means of a two-class discrimination classifier(second algorithmic level).We have tested our eye location system using FERET and BioID database. We compare the performance of two-level classifier with that of non-level classifier, and found it's better performance.
Keywords
Biomedical imaging; eye location; two-level classifier; image context;
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