SHIFT AND ROTATION INVARIANT IRIS FEATURE EXTRACTION BASED ON NON-SUBSAMPLED CONTOURLET TRANSFORM AND GLCM

Sirvan Khalighi, Parisa Tirdad, Fatemeh Pak, Urbano Nunes

2012

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.

Paper Citation

in Harvard Style

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 2: ICPRAM, ISBN 978-989-8425-99-7, pages 470-475. DOI: 10.5220/0003793904700475

in Bibtex Style

@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 2: ICPRAM,},
year={2012},
pages={470-475},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003793904700475},
isbn={978-989-8425-99-7},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 1st International Conference on Pattern Recognition Applications and Methods - Volume 2: ICPRAM,
TI - SHIFT AND ROTATION INVARIANT IRIS FEATURE EXTRACTION BASED ON NON-SUBSAMPLED CONTOURLET TRANSFORM AND GLCM
SN - 978-989-8425-99-7
AU - Khalighi S.
AU - Tirdad P.
AU - Pak F.
AU - Nunes U.
PY - 2012
SP - 470
EP - 475
DO - 10.5220/0003793904700475