关键词: 烟雾图像分割, 粗糙集, 区域生长, 粗糙度直方图

Abstract: In view of the problem that existing image fire smoke segmentation algorithms cannot extract white, gray and black smoke at the same time, this paper proposes a new smoke image segmentation algorithm based on rough set and region growing method. It constructs the roughness histogram according to the statistical histogram of R component extracted from RGB color space of image. And it selects appropriate wave valleys as the segmentation threshold to segment the image in a coarse way. As smoke belongs to motion information compared with background image, the frame difference method is used to extract moving region, excluding static interference. A smoke color model in the RGB color space is established with the unique color characteristics of smoke, to remove the movement interference and obtain the candidate smoke region. The seed points are selected in the region, and region growing method is used to segment image on the results of rough set and extract the smoke region. The results show that the proposed algorithm can segment white, gray and black smoke at the same time, and the edge information of smoke is completed. Compared with the existing algorithms, the mean precision, recall and F-beta of the segmentation are respectively increased by 19%, 21.5%, 20%.

Key words: smoke image segmentation, rough set, region growing, roughness histogram