Infrared Image Normalization Using Block and Least-Squares Method

To reduce the impact of ambient temperature on infrared facial image, a normalization method of infrared image is proposed based on block-least-squares method. Firstly, the images collected under different ambient temperatures were divided into some block images, the values of the change of ambient temperature and the change of corresponding temperature in face were obtained, which were used to be fitted into a function through the least-squares method. Then, each block image was normalized by the relevant function and the whole image could be normalized into the standard condition. Finally, the thermal images were converted into simplified blood perfusion domain to get stable biological features. The experiments demonstrate that the images after temperature normalization have good performance.