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14 May 2018 Face description using anisotropic gradient: thermal infrared to visible face recognition
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Face recognition technologies have been in high demand in the past few decades due to the increase in human-computer interactions. It is also one of the essential components in interpreting human emotions, intentions, facial expressions for smart environments. This non-intrusive biometric authentication system relies on identifying unique facial features and pairing alike structures for identification and recognition. Application areas of facial recognition systems include homeland and border security, identification for law enforcement, access control to secure networks, authentication for online banking and video surveillance. While it is easy for humans to recognize faces under varying illumination conditions, it is still a challenging task in computer vision. Non-uniform illumination and uncontrolled operating environments can impair the performance of visual-spectrum based recognition systems. To address these difficulties, a novel Anisotropic Gradient Facial Recognition (AGFR) system that is capable of autonomous thermal infrared to visible face recognition is proposed. The main contribution of this paper includes a framework for thermal/fused-thermal-visible to visible face recognition system and a novel human-visual-system inspired thermal-visible image fusion technique. Extensive computer simulations using CARL, IRIS, AT and T, Yale and Yale-B databases demonstrate the efficiency, accuracy, and robustness of the AGFR system.
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Qianwen Wan, Shishir Paramathma Rao, Aleksandra Kaszowska, V. Voronin, Karen Panetta, Holly A. Taylor, and Sos Agaian "Face description using anisotropic gradient: thermal infrared to visible face recognition", Proc. SPIE 10668, Mobile Multimedia/Image Processing, Security, and Applications 2018, 106680V (14 May 2018);


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