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Research on Partial Similarity Measure Iris Recognition Alogrithm Based on Local Features

Author: WangLiHua
Tutor: HuZhengPing
School: Yanshan University
Course: Communication and Information System
Keywords: Iris Recognition Iris Location Feature Extraction Steerable pyramid Centre local binarization mode (CLBP) operator
CLC: TP391.41
Type: Master's thesis
Year: 2011
Downloads: 41
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Abstract


With the improvement of the information security requirements , the traditional identification technology has been unable to meet the requirements of the people , more and more biometric technology for authentication . Iris recognition technology as a biometric technology , because of its unique biological characteristics , identify high stability , has become one of the hot research areas of authentication . Research at home and abroad on the basis of the latest research results , the pretreatment portion of the iris recognition algorithm has been improved and the use of local information of the iris to iris feature extraction . First , the iris image pre-processing stage , the use of the inherent structural characteristics of the human iris image iris location , stability , speed and accuracy of the existing iris location algorithm . The inner boundary location , using the method of least squares circle fitting pupil boundary . The outer boundary position , by setting an iris outer boundary of the adaptive template , to obtain a relatively stable iris outer edge contour , and finally a small range Hough transform precise positioning of the outer boundary . Secondly, in the feature extraction stage using steerable pyramid decomposition described the iris from the direction and frequency at the same time . First direction adjustable pyramid filter normalized iris image filtering , different scales , different direction iris subband image ; then center local binary pattern (CLBP) operator to extract the sub-band images the characteristics , and then get a description iris texture features multi-scale orientation histogram distribution and the local binarization of such a center operators to greatly reduce the local binary pattern (LBP) operator produces a histogram dimension . The experimental results confirmed that the method exhibits good performance . Finally, in order to take better recognition rate in the small training samples , the proposed iris recognition algorithm based on the center part of the local binary pattern similarity . Part similarity distance to measure the distance between two iris images used , the recognition rate , but also reduces the complexity of iris recognition method . This identification method either theoretically or experimentally feasible , and in the case of single training sample can achieve better recognition results .

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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Information processing (information processing) > Pattern Recognition and devices > Image recognition device
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