Smoke detection in infrared images based on superpixel segmentation

Min Dai; Peng Gao; Mozhou Sha; Jinwen Tian

doi:10.1117/12.2538195

14 February 2020 Smoke detection in infrared images based on superpixel segmentation

Min Dai, Peng Gao, Mozhou Sha, Jinwen Tian

Proceedings Volume 11432, MIPPR 2019: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications; 1143213 (2020) https://doi.org/10.1117/12.2538195
Event: Eleventh International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2019), 2019, Wuhan, China

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.

Citation Download Citation

Min Dai, Peng Gao, Mozhou Sha, and Jinwen Tian "Smoke detection in infrared images based on superpixel segmentation", Proc. SPIE 11432, MIPPR 2019: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications, 1143213 (14 February 2020); https://doi.org/10.1117/12.2538195

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