Abstract
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 L1 norm approach has been taken into account.














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Kar, A., Neogi, P.P.G. Triangular coil pattern of local radius of gyration face for heterogeneous face recognition. Appl Intell 50, 698–716 (2020). https://doi.org/10.1007/s10489-019-01545-x
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DOI: https://doi.org/10.1007/s10489-019-01545-x