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Development of an efficient secure biometric system by using iris, fingerprint, face

机译:通过使用虹膜,指纹,面部来开发有效的安全生物识别系统

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In this research paper three biometric characteristics are used i.e. Fingerprint, Face, Iris at score level of Fusion. For finger print images two methods are used i.e. Minutiae Extraction and Gabor filter approach. For Iris recognition system Gabor wavelet is used for feature selection. For Face biometric system P.C.A. is used for feature selection. The match count of every trait is calculated. Then the generated result of match and non match is utilized for the sum score level fusion. Then decision is find out for persons recognition. The system is tested on std. Dataset and KVK data set. On KVK dataset it generates an the results as 99.7 % with FAR of 0.02% and FRR of 0.1% and for FVC 2004 dataset and MMU dataset it gives the result as 99.8 % with FAR of 0.11% and FRR of 0.09%.
机译:在本研究论文中,使用了三个生物特征,即Fusion得分级别的指纹,面部,虹膜。对于指纹图像,使用两种方法,即细节提取和Gabor滤波方法。对于虹膜识别系统,Gabor小波用于特征选择。对于Face生物识别系统P.C.A.用于功能选择。计算每个特征的匹配计数。然后将匹配和不匹配的生成结果用于总和评分级别融合。然后找出人识别的决定。该系统已在std上进行了测试。数据集和KVK数据集。在KVK数据集上,其结果为99.7%,FAR为0.02%,FRR为0.1%;对于FVC 2004数据集和MMU数据集,其结果为99.8%,FAR为0.11%,FRR为0.09%。

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