Hand Geometry Recognition based on optimized K-Means Clustering and Segmentation Algorithm

Authors

  • Saravanan N

DOI:

https://doi.org/10.20894/IJMSR.117.005.001.002

Keywords:

K-Means algorithm, Biometric recognition system, Hand Geometry recognition, Robust recognition system.

Abstract

Biometrics plays an important role in electronic authentication based on biological features of the human beings like hand geometry, palm print, finger print, retina and face geometry. The hardware requirements of the different electronic systems that are subset of biometric systems of categories mentioned above vary significantly. The power consumption increases with the hardware complexity used. Large power consumption leads to less portability which is not desired. Most biometric recognition systems require complex optical systems for properly capturing data without noise. The digital pre-processing of input image is an added advantage. Hand Geometry Recognition is the simplest and robust recognition system among all other recognition methods available. Hand geometry recognition involves extracting the hand which is the foreground from the background using segmentation process. Several segmentation algorithms are available. K-Means algorithm is one of the algorithms. In this work the K-Means algorithm is optimized to be used in the recognition process.

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Author Biography

Saravanan N

P.G Scholar, VLSI Design, PSNA College of Engineering and Technology, Dindigul, Tamilnadu, India.

References

[1] Holland, Corey D., and Oleg V. Komogortsev. "Complex eye movement pattern biometrics: the effects of environment and stimulus." IEEE Transactions on Information Forensics and Security, Vol. 8, No. 12, pp: 2115-2126, 2013.

[2] Proenca, Hugo. "Iris biometrics: indexing and retrieving heavily degraded data." IEEE Transactions on Information Forensics and Security, Vol. 8, No. 12, pp: 1975-1985, 2013.

[3] Kannavara, Raghudeep, and Keith L. Shippy. "Topics in biometric human-machine interaction security." IEEE Potentials, Vol. 32, No. 6, pp: 18-25, 2013.

[4] Yeh, Hsiu-Lien, et al. "Robust elliptic curve cryptography-based three factor user authentication providing privacy of biometric data." IET Information Security Vol. 7, No. 3, pp: 247-252, 2013.

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Published

2013-12-17

Issue

Vol. 5 No. 1 (2013)

Section

Articles

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