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Authors: Sirvan Khalighi 1 ; Parisa Tirdad 2 ; Fatemeh Pak 2 and Urbano Nunes 1

Affiliations: 1 University of Coimbra, Portugal ; 2 AZAD University of Qazvin, Iran, Islamic Republic of

Keyword(s): Gray Level Co-occurrence Matrix, Iris Recognition, Non-Subsampled Contourlet Transform, SVM.

Related Ontology Subjects/Areas/Topics: Applications ; Cardiovascular Imaging and Cardiography ; Cardiovascular Technologies ; Classification ; Feature Selection and Extraction ; Health Engineering and Technology Applications ; Kernel Methods ; Object Recognition ; Pattern Recognition ; Signal Processing ; Software Engineering ; Theory and Methods

Abstract: A new feature extraction method for iris recognition in non-subsampled contourlet transform (NSCT) domain is proposed. To extract the features a two-level NSCT, which is a shift-invariant transform, and a rotation-invariant gray level co-occurrence matrix (GLCM) with 3 different orientations are applied on both spatial image and NSCT frequency subbands. The extracted feature set is transformed and normalized to reduce the effect of extreme values in the feature matrix. A set of significant features are selected by using the minimal redundancy and maximal relevance (mRMR) algorithm. Finally the selected feature set is classified using support vector machines (SVMs). The classification results using leave one out cross-validation (LOOCV) on the CASIA iris database, Ver.1 and Ver.4 show that the proposed method performs at the state-of-the art in the field of iris recognition.

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Paper citation in several formats:
Khalighi, S.; Tirdad, P.; Pak, F. and Nunes, U. (2012). SHIFT AND ROTATION INVARIANT IRIS FEATURE EXTRACTION BASED ON NON-SUBSAMPLED CONTOURLET TRANSFORM AND GLCM. In Proceedings of the 1st International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM; ISBN 978-989-8425-99-7; ISSN 2184-4313, SciTePress, pages 470-475. DOI: 10.5220/0003793904700475

@conference{icpram12,
author={Sirvan Khalighi. and Parisa Tirdad. and Fatemeh Pak. and Urbano Nunes.},
title={SHIFT AND ROTATION INVARIANT IRIS FEATURE EXTRACTION BASED ON NON-SUBSAMPLED CONTOURLET TRANSFORM AND GLCM},
booktitle={Proceedings of the 1st International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM},
year={2012},
pages={470-475},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003793904700475},
isbn={978-989-8425-99-7},
issn={2184-4313},
}

TY - CONF

JO - Proceedings of the 1st International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM
TI - SHIFT AND ROTATION INVARIANT IRIS FEATURE EXTRACTION BASED ON NON-SUBSAMPLED CONTOURLET TRANSFORM AND GLCM
SN - 978-989-8425-99-7
IS - 2184-4313
AU - Khalighi, S.
AU - Tirdad, P.
AU - Pak, F.
AU - Nunes, U.
PY - 2012
SP - 470
EP - 475
DO - 10.5220/0003793904700475
PB - SciTePress