Thermal Face Recognition Using Moments Invariants

Face recognition using different imaging modalities, particularly infrared imaging sensors, has become an area of growing interest. The use of thermal IR images can improve the performance of face recognition in uncontrolled illumination conditions. In this paper, we present a new technique for face recognition based on statistical calculations of thermal images. We propose the use of moments invariants which become one of the most important shape descriptors. The proposed feature vector consists of 11 different moments, where three of them are geometric moments and the rest eight are central geometric moments that offer robustness against variability due to changes in localized regions of the faces. The new method has been tested on a new database comprising of images of different expressions, different lightings, and were taken within different time-lapse. The work is reinforced by a discussion of body and face physiology behind thermal face recognition.