Title :
Iris recognition using quaternionic sparse orientation code (QSOC)
Author :
Kumar, Ajay ; Chan, Tak-Shing
Author_Institution :
Dept. of Comput., Hong Kong Polytech. Univ., Hong Kong, China
Abstract :
Personal identification from the iris images acquired under less-constrained imaging environment is highly challenging problem but with several important applications in surveillance, image forensics, search for missing children and wandering elderly. In this paper, we develop and formulate a new approach for the iris recognition using hypercomplex (quaternionic or octonionic) and sparse representation of unwrapped iris images. We model iris representation problem as quaternionic sparse coding problem which is solved by convex optimization strategy. This approach essentially exploits the orientation of local iris texture elements which are efficiently extracted using a binarized dictionary of oriented atoms. The feasibility of this approach is evaluated, both for the recognition and the verification problem, on the publicly available visible illumination UBIRIS V2 database. Our experimental results using the proposed formulation illustrate significant improvement in performance (e.g., ~30% improvement in rank-one recognition accuracy) over the previously studied sparse representation approach for the visible illumination iris recognition.
Keywords :
convex programming; feature extraction; image texture; iris recognition; surveillance; QSOC; binarized dictionary; convex optimization strategy; hypercomplex representation; image forensics; iris recognition; iris representation problem; less-constrained imaging environment; local iris texture elements; missing children search; oriented atoms; personal identification; quaternionic sparse orientation coding problem; recognition problem; sparse representation; surveillance; unwrapped iris images; verification problem; visible illumination UBIRIS V2 database; wandering elderly search; Accuracy; Databases; Gabor filters; Image segmentation; Iris; Iris recognition; Lighting;
Conference_Titel :
Computer Vision and Pattern Recognition Workshops (CVPRW), 2012 IEEE Computer Society Conference on
Conference_Location :
Providence, RI
Print_ISBN :
978-1-4673-1611-8
Electronic_ISBN :
2160-7508
DOI :
10.1109/CVPRW.2012.6239216