Implementation of Frontal-Centroid Moment Invariants in Thermal-Based Face Identification System

This paper presents the implementation of moment invariants; with respect to centroid point obtained from frontal mugshot images, for thermal-based face identification system. Initially, seeded region growing method is applied for background filtering. Sequentially, the system decomposes a background filtered thermal image into 4 thermal regions via 3-valued threshold method. Region with the lowest thermal value is omitted from further processes. This is to ensure that the background scenery is not taken into consideration. Differing from conventional features; such as length of eyes, nose, and mouth, the first moment invariant, I₁, from Hu´s classical moment invariants were computed and extracted as a feature from each generated thermal regions with respect to centroid point obtained from frontal, background filtered source images. This system employs minimum distance measurement method for classification purposes. The performance of this system is encouraging with 92.5% of correct identification rate for test to registered image ratio of 2:1 and 90% of correct identification rate for test to registered image ratio of 4:1.