Indian Journal of Bioinformatics and Biotechnology

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Manifold Feature Extraction for Foot Print Image


Affiliations
1 Department of CSE, Sathyabama University, Chennai, India
2 Department of IT, Velemmal Engineering College, Chennai, India
 

In this paper, the new biometric of FOOT PRINT RECOGNITION SYSTEM have been introduced. The foot image is proved to be distinct for every human being. On the image of the footprint obtained we performed pre-processing followed by the vital step of feature extraction. The best part of this technique is the use of multiple feature extraction techniques. This feature from the foot image is extracted, classified and then recognized. The use of multiple feature extraction will provide us with better accuracy.

Keywords

Footprint, Gabor Filter, Wavelet, FNN, SVM
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  • Ye, Syoji Kobashi, Yutaka Hata Kazuhiko Taniguchi Kazunari Asari “ Biometric System by Foot Pressure Change Based on Neural Network”, 2009.

  • V.D.Ambeth Kumar and Dr.M.Ramakrishnan,” Lecagyof Footprint Recognition Computer Applications, Vol 35, No-11, Page 9 9-16,Dec 2011.

  • K. Nakajima, Y. Mizukami, K. Tanaka, and T. Tamura, “Foot-Based Personal Recognition”, IEEE: Tr. On Biomedical Engineering, Vol. 47, No. 11, 2000.

  • Sean W. Yip, B.S. and Thomas E. Prieto, “A System for Force Distribution Measurement Beneath The Feet”, IEEE Conference publication ,pp 32-34, 2004.

  • Pier Luigi Dragotti and Martin Vetterli, “Wavelet Footprint: Theory, Algorithms, and Application”, IEEE Trans.Signal Processing, Vol.51, No.5 May 2003.

  • Jin -Woo Jung and Zeungnam Bien ,” Dynamic-Footprint based Person Identification using Mat-type Pressure Sensor ” IEEE 2003.


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  • Manifold Feature Extraction for Foot Print Image

Abstract Views: 545  |  PDF Views: 375

Authors

V. D. Ambeth Kumar
Department of CSE, Sathyabama University, Chennai, India
M. Ramakrishnan
Department of IT, Velemmal Engineering College, Chennai, India

Abstract


In this paper, the new biometric of FOOT PRINT RECOGNITION SYSTEM have been introduced. The foot image is proved to be distinct for every human being. On the image of the footprint obtained we performed pre-processing followed by the vital step of feature extraction. The best part of this technique is the use of multiple feature extraction techniques. This feature from the foot image is extracted, classified and then recognized. The use of multiple feature extraction will provide us with better accuracy.

Keywords


Footprint, Gabor Filter, Wavelet, FNN, SVM

References