Smoke detection in infrared images based on superpixel segmentation

Abstract

Infrared smoke interference technology seriously infected the combat effectiveness of photoelectric guided weapons in modern warfare. As a result of the occlusion caused by smoke screen, the robustness of image matching guidance algorithm will decrease. Thus, to judge whether there is smoke interference in images and smoke screen area extraction are of great importance for the accuracy of image matching guidance algorithm. However, most of the smoke detection methods aimed at fire early warning, so that they focused on whether smoke exists or not. While both of the discrimination of smoke interference and smoke screen area extraction are what we concern. In this paper, a smoke detection method based on superpixel segmentation and region merging is proposed. Firstly, over-segmentation regions of input infrared image with superpixel segmentation are obtained. Then, fusion texture feature of the image is computed. Finally, superpixel regions are merged based on the fusion features of each superpixel block obtained in the previous step and smoke screen area extraction is completed.