Target Area Extraction Algorithm of Infrared Thermal Image Combining Target Detection with Matching Correction

Abstract

Infrared thermal image makes the target have certain degree of recognition by reflecting the thermal radiation information emitted by the target, which effectively compensates the information loss of visible light image in harsh imaging environment. Contour extraction effect of target area using traditional Canny algorithm is not good, because the contour gradient change of infrared thermal image target area is not obvious. At the same time, the threshold of most of algorithms needs to be set manually, which is greatly affected by subjective factors, and the image processing efficiency is low. Therefore, this paper studied the target area extraction algorithm of infrared thermal image by combining target detection with matching correction. First, the paper introduced the feature matching algorithm based on grid motion statistics, and converted smoothness constraint of motion into statistics, thus replacing the number of extended feature points with the acquisition of features with better performance and filtering false image matching based on the number of other matching points in the neighborhood of statistical matching points. Second, based on the feature matching results obtained in the previous section, this paper proposed a extraction method of infrared thermal image target area based on thermal feature descriptors, which combined the extracted thermal features with the semantic attributes of each area in the infrared thermal image, thus distinguishing the subtle differences between the infrared thermal image sub-categories. Finally, experimental results verified the effectiveness of the proposed method.