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

页码：58 / 62

页数：5

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