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Title |
Individuals Authentication from Both-Eye Images using Dempster-Shafer Fusion |
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Author |
Ghalem kamel ghanem and Hendel fatiha |
| Citation |
Vol. 26 No. 7 pp. 43-50 |
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Abstract |
In this paper, an efficient method that allows us to authenticate individuals from both-eye images is presented. The proposed method consists of three main steps: In the first one, the iris images are segmented in order to extract the iris disc. The segmented images are normalized by Daugman rubber sheet model. In the second step, the normalized images are analyzed by a bench of two 1D Log-Gabor filters to extract the texture characteristics. The encoding is realized with a phase of quantization developed by J. Daugman to generate the binary iris templates. In the third step, for the authentication and the similarity measurement between both binary irises templates, the hamming distances combined using Dempster Shafer rule are used with a previously calculated threshold. The proposed method has been tested on a subset of iris database CASIA-IrisV3-Interval which achieves a good performance with accuracy of 99.97%, FPR of 0% and FNR of 3.58%. |
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Keywords |
Both eye, authentication, Dempster Shafer rule, performance. |
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