Thermal imaging-based identification of facial features in noisy environment

Abstract

Face identification is amongst the most efficacious and extensive applications in biometrics involving extraction and locating facial features. With identification being monotonous task attributable to reliance on parameters like varied cameras, fluctuating backgrounds, and exposure to the environment in which an individual is present. Thermal imaging is endeavoring to resolve the accuracy issue of apparent imaging, such as lighting and brightness intensity, among all biometric variables. This paper presents a study of thermal imaging and effective methods involved in the feature extraction process for facial features with thermal imaging under the influence of varied noise. A novel face dataset is created TID comprising 27 thermal images and its corresponding visual band image using Fluke 480 Ti Pro camera. The study analyses detection efficiency of six feature extraction techniques in visible and thermal bands in facial features identification. Also, the influence of noise in the thermal band within the region of interest using feature points FIN, FOUT has been estimated. Throughout TID dataset, ORB extraction technique has been able to identify strongest inlier features FIN to a maximum extent with detection around the nose, eyes, and mouth. Further, results indicate feature detection in thermal images being invariant to effect of noise for detecting facial features.