“School of Cognitive%20Sciences”
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| Paper IPM / Cognitive%20Sciences / 11385 |
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| Abstract: | |||||||
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In despite of successful implementation of iris recognition systems, noncooperative recognition is still remained as an unsolved problem. Unexpected behavior of the subjects and uncontrolled lighting conditions as the main aspects of noncooperative iris recognition result in blurred and noisy captured images. This issue can degrade the performance of iris recognition system. In this paper, to address the
aforementioned challenges, an intelligent decision
combiner is proposed in which prior to perform decision
fusion; an automatic image quality inspection is carried
out. The goal is to determine whether captured decisions
based on visible light (VL) and near infrared (NIR)
images have enough reliability to incorporate into final
decision making. Experimental results on the UTIRIS
confirm the superior performance of the proposed
combiner in comparison with other common nontrainable
decision combiners whereas in all cases, the effectiveness of fusion approach makes it a reliable solution to noncooperative subjects? behavior and uncontrolled lighting conditions.
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