Thermal Physiological Moment Invariants for Face Identification

This paper presents the extension of our previous work on moment invariants with respect to centroid point (obtained from frontal mugs hot images) for thermal-based face identification system. In previous work, seeded region growing method was applied for background filtering. Sequentially, the system decomposes a background filtered thermal image into 4 thermal regions via 3-valued threshold method. In the extension of the pre-processes, we employed anistropic diffusion between these two steps. This step aids in decreasing the effect of noise. Furthermore, previously we only considered frontal mugs hot images as registered images, therefore, in this paper we include mid-profiles and left and right profile in the registered dataset. This is to overcome for images with angular pose that exceeds 45 degrees to the left and right. Due to multiple angular pose available in the registered dataset, customized and simple pose estimation is introduced in this paper. The pose estimation utilizes information previously obtained during the pre-processes, thus avoiding additional steps that is required if current available pose estimation methods were to be employed. This system employs minimum distance measurement method for classification purposes. The encouraging performance of this system is represented by a cumulative match characteristic curve (also known as the CMC curve) at the end of this paper.