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Illumination Invariant Feature Extraction for Multispectral Palmprint Verification

Venkateswaran N., Saranraj S., Sudharsan S.. Published in Pattern Recognition

International Journal of Applied Information Systems
Year of Publication: 2016
Publisher: Foundation of Computer Science (FCS), NY, USA
Authors: Venkateswaran N., Saranraj S., Sudharsan S.
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  1. Venkateswaran N., Saranraj S. and Sudharsan S.. Illumination Invariant Feature Extraction for Multispectral Palmprint Verification. International Journal of Applied Information Systems 11(3):11-20, August 2016. URL, DOI BibTeX

    	author = "Venkateswaran N. and Saranraj S. and Sudharsan S.",
    	title = "Illumination Invariant Feature Extraction for Multispectral Palmprint Verification",
    	journal = "International Journal of Applied Information Systems",
    	issue_date = "August 2016",
    	volume = 11,
    	number = 3,
    	month = "Aug",
    	year = 2016,
    	issn = "2249-0868",
    	pages = "11-20",
    	numpages = 10,
    	url = "",
    	doi = "10.5120/ijais2016451586",
    	publisher = "Foundation of Computer Science (FCS), NY, USA",
    	address = "New York, USA"


The aim of biometrics is to identify humans from their personal traits more efficiently using devices, algorithms and procedures for applications that require security and authentication. Multispectral image analysis has gained importance due to its potential for accurate and faster recognition performance.  In this paper, Multispectral palmprint biometric system is proposed which uses the fusion of both MS and visible image to acquire more discriminative palm print information. The proposed system collects palm print images in visible and NIR bands. PCA based Fusion algorithm has been used to obtain more informative palmprint. First, Region of Interest (ROI) is extracted from the acquired palm print images. Then, features are extracted using phase congruency, histogram of gradient, Gabor filter and adaptive thresholding based algorithms. Simple distortion based measures are used for recognition. The proposed system is tested on a palmprint data collected using 080GE multispectral camera. Simulation results show high recognition performance using Gabor features obtained by fusion of visible and NIR palm print image.


  1. Patrick Flynn, 2008. Handbook on Biometrics. Springer.
  2. David Maltoni, Anil.K.Jai,,2006. Handbook on Multibiometrics. Inger-Verlag.
  3. Yuan Yan Tang, Yang Lu, 2015. Hyperspectral Image Classification Based on Three-Dimensional Scattering Wavelet Transform. IEEE Transactions on Geoscience and Remote sensing, vol. 53, 2467-2476.
  4. Ruud Bolle, SharathPankanti, 2002. Biometrics personal identification in Network society. Springer, Heidelberg, 2002.
  5. Dong Han, ZhenhuaGuo, 2008 Multispectral Palmprint Recognition Using Wavelet-Based Image Fusion. IEEE Transactions on Biometric computing and Image Processing, 2074-2077.
  6. M. P. Sampat, Z. Wang, S. Gupta, A. C. Bovik, and M. K. Markey 2009. Complex wavelet structural similarity: A new image similarity index. IEEE Trans. Image Process., vol. 18, no. 10, 2385–2401.
  7. D. Zhang,2000. Automated Biometrics—Technologies and Systems. MA: Kluwer.
  8. David Zhang, ZhenhuaGuo, Guangming Lu, 2010. An Online System Of Multispectral palm print Verification IEEE Transactions on Instrumentation and Measurement, vol. 59, no. 2, 480-490.
  9. Online Multispectral Palmprint Recognition 2012. IEEE Transactions On Information Forensics And Security, vol. 7, No. 3, 1094-1099. 2012
  10. R. Raghavendra n, Christoph Busch, 2014. Novel Image Fusion Scheme Based On Dependency Measure For Robust Multispectral Palmprint Recognition. International Journal of Advanced Research in pattern recognition, vol. 47, 2205-2221.
  11. Robert K Rowe, UmutUludag, 2007. A Multispectral Whole-Hand Biometric Authentication System. IEEE Transactions on Biometric Recognition Systems.
  12. Ying Hao, Zhenan Sun, .2010. Comparative Studies On Multispectral Palm Image Fusion For Biometrics. National Laboratory of Pattern Recognition, Institute of Automation, CAS.
  13. Simona Crihalmeanu, Arun Ross,, 2012. Multispectral Scleral Patterns for Ocular Biometric Recognition. IEEE Transactions on pattern Recognition Systems, vol. 33, 1860-1869.
  14. Danfeng Hong, Wanquan Liu, et. al. 2015. A Novel Hierarchical Approach For Multispectral Palmprint Recognition. IEEE Transactions on Neuro computing, 511-521.
  15. Rajashree Bhokare, Deepali Sale . 2013 Multispectral Palm Image Fusion: A Critical Review. International Journal of Advanced Research in Computer Engineering & Technology, 2159-2164.
  16. Ancy.S, G.R.Suresh, Survey On Multispectral Biometric Images. International Journal of Innovative Research in Computer and Communication Engineering. 1025-1036.
  17. Maurício Ramalho, Sanchit Singh 2011. Secure Multi-Spectral Hand Recognition System IEEE Signal Processing Conference, 2269-2273.
  18. D. Zhang, W. Kong, J. You and M. Wong 2003. Online Palm print Identification. IEEE Transactions on Pattern Analysis and Machine Intelligence. 1041– 1050.
  19. T. Connie, A. T. B. Jin, and M. G. K. Ong 2005. Automated palms print recognition system. Image Vis. Comput. 501–505.
  20. D. Hu, G. Feng, and Z. Zhou 2007. Two-dimensional locality preserving projections (2DLPP) with its application to palm print recognition. Pattern Recognit. 339–342,
  21. C. Han, H. Cheng, C. Lin, and K. Fan.2003. Personal authentication using palm-print features. Pattern Recognition. 371–381.
  22. X. Wu, D. Zhang, and K. Wang. 2006. Palm line extraction and matching for personal authentication. IEEE Trans. Syst., Man, Cybern. A, Syst., Humans. 978–987. 2006.
  23. N. Otsu.1979. A threshold selection method from gray-level histograms. IEEE Trans. Syst., Man, Cybern.,Syst. 62–66.
  24. P. Kovesi.1999.Image features from phase congruency. J. Comput. Vis. Res. 1–26, 1999.
  25. Bradley, D. and Roth, G. 2007. Adaptive thresholding using the integral image. J. Graph. Tools. 13-20
  26. Saranraj, S. Venkateswaran,N. 2014. Enhancement of mobile camera captured document image with phase preservation. Proc. ICCNT. 68-73.
  27. Saranraj.S. Venkateswaran, N. 2015. Efficient Illumination Correction for Camera Captured Image Documents, Adv. in Nat. Appl. Sci., 391-396.
  28. A. Kong, D. Zhang, and M. Kamel,2006 Palmprint identification using feature-level fusion Pattern Recognition,. 478–487.
  29. A. Kong and D. Zhang 2004. Competitive coding scheme for palmprint verification. Int. Conf. Pattern Recog. 520–523.
  30. W. Jia, D.-S. Huang, D. Zhang 2008. Palmprint verification based on robust line orientation code. Pattern Recognition. 1504– 1513.


Biometrics, Multispectral image, Region of interest (ROI), Phase Congruency, HoG, Adaptive thresholding, Gabor filter