Simple Face Thermal Features for Gender Discrimination


Georgia Koukiou and Vassilis Anastassopoulos, University of Patras, Greece


A very simple approach is proposed for gender discrimination using thermal infrared images of the persons' face. The selected features are actually based on the mean value of the pixels of specific locations on the face. It is proved that the discrimination is feasible either by simple visualization in the feature space or by using a relatively simple neural network for this purpose. All cases of persons from the used database, males and females, are correctly distinguished based on the mean value of the employed locations of the face. Classification results are verified using two conventional approaches, namely: a. the simplest possible neural network so that generalization is achieved along with successful discrimination between all persons and b. the leave-one-out approach to demonstrate the classification performance on unknown persons using the simplest classifiers possible.


Thermal Infrared, Face Recognition, Gender Discrimination, Neural Networks.

Full Text  Volume 10, Number 8