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中文摘要：
因受窑内高温、高粉尘等因素的影响，氧化铝回转窑火焰图像中往往存在噪声。针对现有火焰图像分割算法存在抗噪性差和计算时间长等问题，对斜分最大类间方差法（Otsu 法）进行改进，提出一种基于改进斜分Otsu 法的回转窑火焰图像分割算法。该算法采用简化的距离测度函数作为阈值选取标准，以减少计算量和便于多阈值扩展；采用基于后处理原理的图像分割方式，以进一步增强算法的抗噪性；运用分子动理论优化算法实现加快计算速度。某厂氧化铝回转窑火焰图像的分割实验表明，该算法抗噪性强，运算速度快，能较为精确地分割出火焰图像的背景区、黑把子、火焰区、辐射带、物料区等区域。
英文摘要：
Influenced by high temperature, high dust and other factors, an alumina rotary kiln flame image often contains noise. The existing algorithms for flame image segmentation have deficiencies such as poor anti-noise capability, long computing time and so on. This paper proposes an improved Otsu method based on histogram oblique segmentation for the segmentation of alumina rotary kiln flame images. To reduce the amount of calculation and be convenient for multi-threshold extension, a simplified distance measure function is used as the threshold selection criterion. To further enhance the anti-noise capability, a post-processing based segmentation method is adopted. And a kinetic-molecular theory based optimization algorithm （KMTOA） is used to accelerate the calculation speed. The segmentation experiments of rotary kiln flame image show that the proposed method has stronger anti-noise capability, faster calculation speed, and can more precisely get the background area, black handle, flame area, illuminated area and the material area.
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