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Triangular coil pattern of local radius of gyration face for heterogeneous face recognition

机译:异构性面识别局部环绕局部局部半径的三角形线圈图案

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摘要

This paper puts forward a novel methodology for Heterogeneous Face Recognition (HFR), where we present a new-fangled image representation technique called the Local Radius of Gyration Face (LRGF), which has been theoretically proved to be invariant to changes in illumination, rotation and noise. Finally, a novel Local Triangular Coil Binary Pattern (LTCBP) is presented so as to apprehend the local variations of the LRGF attributes, and the method has been entitled as the Triangular Coil Pattern of Local Radius of Gyration Face (TCPLRGF). The proposed algorithm has been tested on a number of challenging databases to study the precision of the TCPLRGF method under varying condition of illumination, rotation, noise and also the recognition accuracy of sketch-photo and NIR-VIS image. The Rank-1 recognition accuracy of 98.27% on CMU-PIE Database, 98.09% on Extended Yale B Database, 96.35% on AR Face Database, 100% on CUHK Face Sketch (CUFS) Database, 89.01% on LFW Database and 98.74% on the CASIA-HFB NIR-VIS Database exhibits the supremacy of the proposed strategy in Heterogeneous Face Recognition (HFR) under various conditions, compared to other recent state-of-the-art methods. For reckoning the similarity measure between images, a hybridized approach amalgamating the Jaccard Similarity method and the standardized L-1 norm approach has been taken into account.
机译:本文提出了一种新颖的异构性面部识别(HFR)的新方法,其中我们提出了一种称为局部环绕面(LRGF)的新型图像表示技术,其理论上被证明是不变的照明,旋转变化和噪音。最后,提出了一种新颖的局部三角形线圈二进制图案(LTCBP)以便理解LRGF属性的局部变化,并且该方法已被标题为局部环绕面(TCPLRGF)的三角形线圈图案。已经在许多具有挑战性的数据库上测试了所提出的算法,以研究TCPLRGF方法的精度,在不同的照明,旋转,噪声以及草图照片和NIR-VIAR图像的识别准确性下。 CMU-PIE数据库的秩1识别准确度为98.27%,延长耶鲁B数据库98.09%,AR面部数据库96.35%,CUHK面部素描(CUFS)数据库100%,LFW数据库89.01%,98.74%与其他最近最先进的方法相比,CASIA-HFB NIR-VIS数据库在各种条件下表现出在各种条件下的异构性面部识别(HFR)的策略的至上。为了监测图像之间的相似性测量,已经考虑了杂交的方法合并jaccard相似性方法和标准化的L-1规范方法。

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