Thermal Face Recognition Using Moments Invariants
Naser Zaeri 1,
Faris Baker 1, and
Rabie Dib 2
1. Faculty of Computer Studies, Arab Open University, P.O. Box 3322 Safat 13033, Kuwait
2. College of Technological Studies, PAAET, P.O. Box 23167 Safat 13092, Kuwait
2. College of Technological Studies, PAAET, P.O. Box 23167 Safat 13092, Kuwait
Abstract—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.
Index Terms—face recognition, thermal image, feature extraction, moments invariants
Cite: Naser Zaeri, Faris Baker, and Rabie Dib, "Thermal Face Recognition Using Moments Invariants," International Journal of Signal Processing Systems, Vol. 3, No. 2, pp. 94-99, December 2015. doi: 10.12720/ijsps.3.2.94-99
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