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IJSTR >> Volume 1 - Issue 2, March 2012 Edition



International Journal of Scientific & Technology Research  
International Journal of Scientific & Technology Research

Website: http://www.ijstr.org

ISSN 2277-8616



A DCT-based Local Feature Extraction Algorithm for Palm-print Recognition

[Full Text]

 

AUTHOR(S)

Hafiz Imtiaz,Shaikh Anowarul Fattah

 

KEYWORDS

Feature extraction; classification; discrete cosine transform; dominant spectral feature; palm-print recognition; modularization

 

ABSTRACT

In this paper, a spectral feature extraction algorithm is proposed for palm-print recognition, which can efficiently capture the detail spatial variations in a palm-print image. The entire image is segmented into several spatial modules and the task of feature extraction is carried out using two dimensional discrete cosine transform (2D-DCT) within those spatial modules. A dominant spectral feature selection algorithm is proposed, which offers an advantage of very low feature dimension and results in a very high within-class compactness and between-class separability of the extracted features. A principal component analysis is performed to further reduce the feature dimension. From our extensive experimentations on different palm-print databases, it is found that the performance of the proposed method in terms of recognition accuracy and computational complexity is superior to that of some of the recent methods.

 

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