An Iris Recognition Algorithm of Multiple Features Extraction and Fusion

DOI

10.2991/mmebc-16.2016.181How to use a DOI?

Keywords

iris recognition, feature fusion, Logistic Regression Classifier.

Abstract

In this paper, an iris recognition algorithm of multiple features extraction and fusion was proposed, which was different from the classical iris recognition algorithm that focused on a single texture feature. Firstly, the collected iris images were preprocessed. Secondly, features of preprocessed images were extracted by using Log-Gabor filter and Haar wavelet, and values of similarity were calculated by adopting Hamming Distance and Weighted Euclidean Distance methods. Finally, the Logistic Regression Classifier was used to fuse and classify the values of similarity. The experimental results verified the effectiveness of the algorithm, and a higher correct recognition rate was gained.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Bo Liu
AU  - Zhen Zhang
AU  - Long Li
PY  - 2016/06
DA  - 2016/06
TI  - An Iris Recognition Algorithm of Multiple Features Extraction and Fusion
BT  - Proceedings of the 2016 6th International Conference on Machinery, Materials, Environment, Biotechnology and Computer
PB  - Atlantis Press
SP  - 868
EP  - 871
SN  - 2352-5401
UR  - https://doi.org/10.2991/mmebc-16.2016.181
DO  - 10.2991/mmebc-16.2016.181
ID  - Liu2016/06
ER  -