Directional energy based palmprint identification using non subsampled contourlet transform

Mustafa Mumtaz, Atif Bin Mansoor, Hassan Masood

Research output: Chapter in Book/Conference paperConference paper

6 Citations (Scopus)

Abstract

Palmprint based personal verification has gained preference over other biometric modalities due to its ease of acquisition, high user acceptance and reliability. This paper presents a novel palmprint based identification approach which uses the textural information available on the palmprint by employing the Non Subsampled Contourlet Transform (NSCT). After establishing the region of interest (ROI), the two dimensional (2-D) spectrum is divided into fine slices, using iterated directional filterbanks. Next, directional energy component for each block from the decomposed subband outputs is computed. The proposed algorithm captures both local and global details in a palmprint as a compact fixed length palm code. Palmprint matching is then performed using Normalized Euclidean Distance classifier. The algorithm is tested on a total of 7752 palm images, acquired from the standard database of Polytechnic University of Hong Kong. The experimental results demonstrated the feasibility of the proposed system by exhibiting Decidability Index of 2.8125 and Equal Error Rate of 0.1604%, better than the reported techniques in literature.

Original languageEnglish
Title of host publication2009 IEEE International Conference on Image Processing, ICIP 2009 - Proceedings
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages1965-1968
Number of pages4
ISBN (Print)9781424456543
DOIs
Publication statusPublished - 1 Jan 2009
Externally publishedYes
Event2009 IEEE International Conference on Image Processing, ICIP 2009 - Cairo, Egypt
Duration: 7 Nov 200910 Nov 2009

Conference

Conference2009 IEEE International Conference on Image Processing, ICIP 2009
CountryEgypt
CityCairo
Period7/11/0910/11/09

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