发明名称 Identification by iris recognition
摘要 The invention relates to a method for identification on the basis of biometric data of an iris of an eye to be identified, including the steps of: encoding an image of the iris to be identified and a second iris image so as to obtain binary codes that are representative of the images to be compared; determining a binary similarity code from the binary code of the image of the iris to be identified and the second binary code of the second iris image; determining a confidence score on the basis of the local densities of similarities between the two compared iris images, as well as on the basis of the binary similarity code, the local similarity densities being in turn determined on the basis of the binary similarity code; and deciding, depending on the value of the confidence score, whether or not the two iris images are from the same iris. The invention also relates to a system suitable for implementing the identification method.
申请公布号 US9183440(B2) 申请公布日期 2015.11.10
申请号 US201214343048 申请日期 2012.09.06
申请人 MORPHO 发明人 Bohné Julien
分类号 G06K9/00;G06K9/46;G06K9/62;H04N19/91 主分类号 G06K9/00
代理机构 Blakely Sokoloff Taylor & Zafman 代理人 Blakely Sokoloff Taylor & Zafman
主权项 1. An identification method from biometric data of an iris (I) of an eye of a person to be identified, comprising: encoding an image (P1) of the iris (I) to be identified and a second iris image (P2) to be compared to the first image (P1), to obtain binary codes (T1_code, T2_code) representative of the images to be compared, such that adjacent bits of the binary codes (T1_code, T2_code) correspond to adjacent zones of the irises on the corresponding images (P1, P2), determining a binary similarity code (Sim) from the binary code (T1_code) of the image (P1) of the iris (I) to be identified and of the second binary code (T2_code) of the second iris image (P2), determining a confidence score as a function of local densities of similarities (Density(b)) between the two compared irises images (P1, P2), as well as of the binary similarity code (Sim), the local densities of similarity themselves being determined as a function of the binary similarity code (Sim), deciding, as a function of the value of the confidence score, whether the two iris images (P1, P2) come from the same iris.
地址 Issy-les-Moulineaux FR