Computationally light forehead segmentation from thermal images

Thermal images are often paired with visible spectrum images captured simultaneously-as surface features are easier to identify with proper illumination-to determine the thermal feature locations. Not all thermal images are necessarily recorded this way, yet determining salient feature regions is beneficial to other tasks. The forehead region is useful to the field of vital signs analysis and the goal of this work is automatically identifying the forehead region solely from thermal images. The anatomy of the forehead and its thermo-dynamic properties lend itself to minimizing the variance of a facial thermogram. Experiments conducted indoors on 32 subjects under normal, exercise and pain conditions. The proposed solution identifies the forehead region with 90-95% accuracy in 80ms or less, without initialization or training data, and can be easily implemented in parallel.