Palmprint Recognition using Principle Component Analysis Implemented on TMS320C6713 DSP Processor

Authors

  • Thulfiqar Hussein Mandeel School of Computer and Communication Engineering, Universiti Malaysia Perlis, 02600 Arau, Perlis, Malaysia
  • Muhammad Imran Ahmad School of Computer and Communication Engineering, Universiti Malaysia Perlis, 02600 Arau, Perlis, Malaysia
  • Mohd Nazrin Md Isa School of Microelectronic Engineering, Universiti Malaysia Perlis, 02600 Arau, Perlis, Malaysia
  • Ruzelita Ngadiran School of Computer and Communication Engineering, Universiti Malaysia Perlis, 02600 Arau, Perlis, Malaysia

Keywords:

Biometrics, Palmprint recognition, Principal Component Analysis, Feature Extraction,

Abstract

This paper presents a human identification system using eigen-palm images. The proposed method consists of three main stages. The preprocessing stage computes the palmprint images to capture important information and produce a better representation of palmprint image data. The second stage extracts significant features from palmprint images and reduces the dimension of the palmprint image data by applying the principal component analysis (PCA) technique. Low-dimensional features in the feature space are assumed to be Gaussian. Thus, the Euclidean distance classifier can be used in the matching process to compare test image with the template. The proposed method is tested using a benchmark PolyU dataset. Experimental results show that the best achieved recognition rate is 97.5% when the palmprint image is represented using 34 PCA coefficients. Moreover, the Euclidean distance classifier is implemented on a digital signal processor (DSP) board. Implementing the proposed algorithm using the DSP processor achieves better performance in computation time compared with a personal computer-based system

References

Jain, A. K., Ross, A., Prabhakar, S. (2004). An Introduction To Biometric Recognition. Ieee Transactions On Circuits And Systems For Video Technology , 14(1), Pp. 4-20.

Zhang, D., Kong, W. K., You, J., & Wong, M. (2003). Online Palmprint Identification. Ieee Transactions On Pattern Analysis And Machine Intelligence, 25(9), Pp. 1041-1050.

Duta, N., Jain, A. K., & Mardia, K. V. (2002). Matching Of Palmprints. Pattern Recognition Letters, 23(4), Pp. 477-485.

Liu, L., & Zhang, D. (2005, September). Palm-Line Detection. In Image Processing, 2005. Icip 2005. Ieee International Conference On Vol. 3, Pp. 269-272.

Wang, L., Jin, W., Liu, Z., He, Y., & Li, G. (2012). A Method Of Palmprint Recognition Integrated By 2d-Pca And Sparse Representation. Opto-Electronic Engineering.

Jolliffe, I. (2002). Principal Component Analysis. John Wiley & Sons, Ltd.

Mu, M., Ruan, Q., & Shen, Y. (2010, February). Palmprint Recognition Based On Discriminative Local Binary Patterns Statistic Feature. International Conference On Signal Acquisition And Processing, 2010.

Icsap'10. Pp. 193-197

Iitsuka, S., Miyazawa, K., & Aoki, T. (2009, November). A Palmprint Recognition Algorithm Using Principal Component Analysis Of Phase Information. 16th Ieee International Conference On Image Processing

(Icip), Pp. 1973-1976.

Guo, Z., Wu, G., Chen, Q., & Liu, W. (2011, November). Palmprint Recognition By A Two-Phase Test Sample Sparse Representation. International Conference On Hand-Based Biometrics (Ichb), 2011, Pp.

-4.

Ghandehari, A., Anvaripour, M., & Soltanpour, S. (2012, March). Palmprint Verification And Identification Using Pyramidal Hog Feature And Fast Tree Based Matching. 5th Iapr International Conference On Biometrics (Icb), 2012, Pp. 421-426.

Li, W., Zhang, B., Zhang, L., & Yan, J. (2012). Principal Line-Based Alignment Refinement For Palmprint Recognition. Ieee Transactions On Systems, Man, And Cybernetics, Part C: Applications And Reviews, ,

(6), Pp. 1491-1499.

Badrinath, G. S., & Gupta, P. (2009). Palmprint Based Verification System Robust To Rotation, Scale And Occlusion. 12th International Conference On Computers And Information Technology, 2009. (Iccit'09). Pp. 408-413.

Chassaing, R. (2004). Digital Signal Processing And Applications With The C6713 And C6416 Dsk (Vol. 16). John Wiley & Sons.

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Published

2016-07-01

How to Cite

Hussein Mandeel, T., Ahmad, M. I., Md Isa, M. N., & Ngadiran, R. (2016). Palmprint Recognition using Principle Component Analysis Implemented on TMS320C6713 DSP Processor. Journal of Telecommunication, Electronic and Computer Engineering (JTEC), 8(4), 41–46. Retrieved from https://jtec.utem.edu.my/jtec/article/view/1169

Issue

Vol. 8 No. 4: Pioneering Future Innovation Through Green Technology II

Section

Articles

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