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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.


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