Thermal Image Segmentation of Facial Thermograms Using K-Means Algorithm in Evaluation of Orofacial Pain

The study aims at analyzing skin surface temperature, aided by the thermal camera, a supporting software, and application of k-means algorithm, and feature extraction in MATLAB to diagnose dental diseases, specifically, orofacial pain. The thermal camera is employed for capturing thermal images of the Left, Right, and Front profiles of all the subjects taken into account. MATLAB-based image segmentation using k-means algorithm, and feature extraction was carried out for control and test group data. The results obtained from the study depict that the mean temperature difference of maximum, minimum and average values of temperature recorded were found to be 1.09% in the front, 3.78% in the right, and 3.97% in the left facial regions between the normal subjects and abnormal diseased subjects. Of the regions examined using thermography, and subsequent feature extraction, the right and left sides show almost similar percentage differences, that is, of 3.78 and 3.97%. These findings point toward a clear, and significant rise of temperature, due to presence of infections, or ailments in the From this data it is safe to infer that, presence of infections, significantly increases the temperature of the region they are present in, and hence give an indication of possible application of thermography in dental disease detection.