Iris Recognition Using Vector Quantization

被引：4
|
作者：
Kekre, H. B. [1 ]
Sarode, T. K. [2 ]
Bharadi, V. A. [3 ]
Agrawal, A. A. [4 ]
Arora, R. J. [4 ]
Nair, M. C. [4 ]
机构：
[1] NMIMS Univ, Vileparle W, Bombay 56, Maharashtra, India
[2] TSEE, Bombay 56, Maharashtra, India
[3] TCET, Bombay 56, Maharashtra, India
[4] Thadomal Shahani Engg Coll, BE Comp Engn, Bombay 400050, Maharashtra, India
来源：
2010 INTERNATIONAL CONFERENCE ON SIGNAL ACQUISITION AND PROCESSING: ICSAP 2010, PROCEEDINGS | 2010年
关键词：
Biometrics; Iris recognition; Vector Quantization; LBG; KPE; KFCG; ALGORITHM;
D O I：
10.1109/ICSAP.2010.45
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
In today's world, where terrorist attacks are on the rise, employment of infallible security systems is a must. Iris recognition enjoys universality, high degree of uniqueness and moderate user co-operation. This makes Iris recognition systems unavoidable in emerging security & authentication mechanisms. We propose an iris recognition system based on vector quantization. The proposed system does not need any pre-processing and segmentation of the iris. We have tested LBG, Kekre's Proportionate Error Algorithm (KPE) & Kekre's Fast Codebook Generation Algorithm (KFCG) for the clustering purpose. From the results it is observed that KFCG requires 99.79% less computations as that of LBG and KPE. Further the KFCG method gives best performance with the accuracy of 89.10% outperforming LBG that gives accuracy around 81.25%. Performance of individual methods is evaluated and presented in this paper.
引用
收藏
页码：58 / 62
页数：5
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