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http://dx.doi.org/10.9717/kmms.2016.19.5.881

Person Recognition using Ocular Image based on BRISK  

Kim, Min-Ki (Dept. of Computer Science in Gyeongsang National University, Engineering Research Institute)
Publication Information
Journal of Korea Multimedia Society / v.19, no.5, 2016 , pp. 881-889 More about this Journal
Abstract
Ocular region recently emerged as a new biometric trait for overcoming the limitations of iris recognition performance at the situation that cannot expect high user cooperation, because the acquisition of an ocular image does not require high user cooperation and close capture unlike an iris image. This study proposes a new method for ocular image recognition based on BRISK (binary robust invariant scalable keypoints). It uses the distance ratio of the two nearest neighbors to improve the accuracy of the detection of corresponding keypoint pairs, and it also uses geometric constraint for eliminating incorrect keypoint pairs. Experiments for evaluating the validity the proposed method were performed on MMU public database. The person recognition rate on left and right ocular image datasets showed 91.1% and 90.6% respectively. The performance represents about 5% higher accuracy than the SIFT-based method which has been widely used in a biometric field.
Keywords
Biometrics; BRISK; Ocular Image; Person Recognition;
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Times Cited By KSCI : 1  (Citation Analysis)
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