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所属单位：电子信息工程学院

发表刊物：Zhongguo Kuangye Daxue Xuebao

摘要：It is difficult to utilize traditional active contour models to extract the fire region of the early fire image of mine accurately. Aiming at this problem, an improved CV model was proposed. On the basis of calculating the global region fitting centers of the object and background regions, the local gray histograms of the region inside and outside the curve were utilized to obtain the local region fitting centers of the object and background regions. Then the normalized adjustable ratios were incorporated into the global and local region fitting centers, which can synthetically utilize both global and local information of the image. To accelerate the motion of the curve towards the object boundaries, the minimum absolute differences of the pixel grayscale values inside and outside the curve were used to replace the original internal and external energy weights, which can improve the segmentation efficiency of the model. The experimental results show that, compared with CV model, LBF model, LGIF model, and the CV model incorporating adaptive energy weight, the proposed model can extract the fire region of the early fire image of mine more rapidly and accurately, and has obvious advantages in terms of segmentation performance and segmentation efficiency. © 2018, Editorial Board of Journal of CUMT. All right reserved.

ISSN号：1000-1964

是否译文：否

发表时间：2018-03-01

合写作者：韩斌,倪康

通讯作者：吴一全