IEICE TRANSACTIONS on Information
Iris Recognition Based on Local Gabor Orientation Feature Extraction
Summary :
In this Letter, a new iris recognition approach based on local Gabor orientation feature is proposed. On one hand, the iris feature extraction method using the traditional Gabor filters can cause time-consuming and high-feature dimension. On the other hand, we can find that the changes of original iris texture in angle and radial directions are more obvious than the other directions by observing the iris images. These changes in the preprocessed iris images are mainly reflected in vertical and horizontal directions. Therefore, the local directional Gabor filters are constructed to extract the horizontal and vertical texture characteristics of iris. First, the iris images are preprocessed by iris and eyelash location, iris segmentation, normalization and zooming. After analyzing the variety of iris texture and 2D-Gabor filters, we construct the local directional Gabor filters to extract the local Gabor features of iris. Then, the Gabor & Fisher features are obtained by Linear Discriminant Analysis (LDA). Finally, the nearest neighbor method is used to recognize the iris. Experimental results show that the proposed method has better iris recognition performance with less feature dimension and calculation time.
- Publication
- IEICE TRANSACTIONS on Information Vol.E98-D No.8 pp.1604-1608
- Publication Date
- 2015/08/01
- Publicized
- 2015/04/22
- Online ISSN
- 1745-1361
- DOI
- 10.1587/transinf.2014EDL8188
- Type of Manuscript
- LETTER
- Category
- Pattern Recognition
Authors
Jie SUN
Qingdao Technological University
Lijian ZHOU
Qingdao Technological University
Zhe-Ming LU
Zhejiang University
Tingyuan NIE
Qingdao Technological University
Keyword
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Jie SUN, Lijian ZHOU, Zhe-Ming LU, Tingyuan NIE, "Iris Recognition Based on Local Gabor Orientation Feature Extraction" in IEICE TRANSACTIONS on Information,
vol. E98-D, no. 8, pp. 1604-1608, August 2015, doi: 10.1587/transinf.2014EDL8188.
Abstract: In this Letter, a new iris recognition approach based on local Gabor orientation feature is proposed. On one hand, the iris feature extraction method using the traditional Gabor filters can cause time-consuming and high-feature dimension. On the other hand, we can find that the changes of original iris texture in angle and radial directions are more obvious than the other directions by observing the iris images. These changes in the preprocessed iris images are mainly reflected in vertical and horizontal directions. Therefore, the local directional Gabor filters are constructed to extract the horizontal and vertical texture characteristics of iris. First, the iris images are preprocessed by iris and eyelash location, iris segmentation, normalization and zooming. After analyzing the variety of iris texture and 2D-Gabor filters, we construct the local directional Gabor filters to extract the local Gabor features of iris. Then, the Gabor & Fisher features are obtained by Linear Discriminant Analysis (LDA). Finally, the nearest neighbor method is used to recognize the iris. Experimental results show that the proposed method has better iris recognition performance with less feature dimension and calculation time.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.2014EDL8188/_p
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@ARTICLE{e98-d_8_1604,
author={Jie SUN, Lijian ZHOU, Zhe-Ming LU, Tingyuan NIE, },
journal={IEICE TRANSACTIONS on Information},
title={Iris Recognition Based on Local Gabor Orientation Feature Extraction},
year={2015},
volume={E98-D},
number={8},
pages={1604-1608},
abstract={In this Letter, a new iris recognition approach based on local Gabor orientation feature is proposed. On one hand, the iris feature extraction method using the traditional Gabor filters can cause time-consuming and high-feature dimension. On the other hand, we can find that the changes of original iris texture in angle and radial directions are more obvious than the other directions by observing the iris images. These changes in the preprocessed iris images are mainly reflected in vertical and horizontal directions. Therefore, the local directional Gabor filters are constructed to extract the horizontal and vertical texture characteristics of iris. First, the iris images are preprocessed by iris and eyelash location, iris segmentation, normalization and zooming. After analyzing the variety of iris texture and 2D-Gabor filters, we construct the local directional Gabor filters to extract the local Gabor features of iris. Then, the Gabor & Fisher features are obtained by Linear Discriminant Analysis (LDA). Finally, the nearest neighbor method is used to recognize the iris. Experimental results show that the proposed method has better iris recognition performance with less feature dimension and calculation time.},
keywords={},
doi={10.1587/transinf.2014EDL8188},
ISSN={1745-1361},
month={August},}
Copy
TY - JOUR
TI - Iris Recognition Based on Local Gabor Orientation Feature Extraction
T2 - IEICE TRANSACTIONS on Information
SP - 1604
EP - 1608
AU - Jie SUN
AU - Lijian ZHOU
AU - Zhe-Ming LU
AU - Tingyuan NIE
PY - 2015
DO - 10.1587/transinf.2014EDL8188
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E98-D
IS - 8
JA - IEICE TRANSACTIONS on Information
Y1 - August 2015
AB - In this Letter, a new iris recognition approach based on local Gabor orientation feature is proposed. On one hand, the iris feature extraction method using the traditional Gabor filters can cause time-consuming and high-feature dimension. On the other hand, we can find that the changes of original iris texture in angle and radial directions are more obvious than the other directions by observing the iris images. These changes in the preprocessed iris images are mainly reflected in vertical and horizontal directions. Therefore, the local directional Gabor filters are constructed to extract the horizontal and vertical texture characteristics of iris. First, the iris images are preprocessed by iris and eyelash location, iris segmentation, normalization and zooming. After analyzing the variety of iris texture and 2D-Gabor filters, we construct the local directional Gabor filters to extract the local Gabor features of iris. Then, the Gabor & Fisher features are obtained by Linear Discriminant Analysis (LDA). Finally, the nearest neighbor method is used to recognize the iris. Experimental results show that the proposed method has better iris recognition performance with less feature dimension and calculation time.
ER -
English
