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Iris detection using intensity and edge information

机译:使用强度和边缘信息进行虹膜检测

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摘要

In this paper e propose a new algorithm to detect the irises of both eyes from a face image, The algorithm first detects the face region in the image and then extracts intensity valleys from the face region. Next, the algorithm extracts iris candidates from the alleys using the feature template of Lin and Wu (IEEE Trans. Image Process. 8 (6) (1999) 834) and the separability filter of Fukui and Yamaguchi (Trans. IEICE Japan J80-D-II (8) ( 1997) 2 170). Finally, using the costs for pairs of iris candidates proposed in this paper, the algorithm selects a pair of iris candidates corresponding to the irises. The costs are computed by using Hough transform, separability filter and template matching. As the results of the experiments, the iris detection rate of the proposed algorithm was 95.3% for 150 face images of 15 persons without spectacles in the database of University of Bern and 96.8% for 63 images of 21 persons without spectacles in the AR database. (C) 2002 Pattern Recognition Society. Published by Elsevier Science Ltd. All rights reserved. [References: 19]
机译:本文提出了一种从面部图像中检测两只眼睛虹膜的新算法,该算法首先检测图像中的面部区域,然后从面部区域中提取强度谷。接下来,该算法使用Lin和Wu的特征模板(IEEE Trans。Image Process。8(6)(1999)834)以及Fukui和Yamaguchi的可分离性过滤器(Trans。IEICE Japan J80-D)从胡同中提取虹膜候选对象。 -II(8)(1997)2170)。最后,使用本文提出的一对虹膜候选成本,该算法选择了与虹膜相对应的一对虹膜候选。通过使用霍夫变换,可分离性过滤器和模板匹配来计算成本。实验结果表明,该算法在伯尔尼大学的数据库中有15个人没有眼镜的150张面部图像的虹膜检测率为95.3%,在AR数据库中有21个人没有眼镜的63张图像的虹膜检测率为96.8%。 (C)2002模式识别学会。由Elsevier Science Ltd.出版。保留所有权利。 [参考:19]

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