In order to realize an automatic recognition and rapid separation of the coal and refuse,the texture features of the coal and refuse,grayscale grade of the profile surface and other large difference features were applied and the single colure grayscale image of the coal and refuse were treated with the smooth filtering,noise reduction and other method.A differential box dimensional method was applied to calculate the grayscale image fractal dimension of the coal and refuse in order to distinguish the surface texture roughness of the coal and refuse.The experiment results showed that there were obvious differences in the fractal dimensions of the coal and refuse,the fractal dimension of coal was larger than that of gangue,take the value 2.450 0 as the dividing point,and the fractal dimension of coal was above the dividing point,the fractal dimension of gangue was below the dividing point.According to the differences,an automatic recognition of the coal and refuse could be realized and could set up a theoretical basis to realize a new coal and refuse separation system.%为实现煤矸自动识别及快速分选,利用煤与矸石的纹理特征与轮廓表面灰度级别等差异较大的特点,对于二者的单一颜色灰度图像,采取平滑滤波、降噪等方法处理,应用差分盒维法求得二者灰度图像分形维数,以区分煤与矸石图像表面纹理粗糙度.试验结果表明,煤和矸石的分形维数有明显的不同,煤的分形维数要大于矸石,以数值2.4500为分界点,煤的分形维数在分界点之上,矸石的分形维数在分界点之下.根据这一差异可有望实现煤矸的自动识别,为实现一种全新的煤矸分选系统奠定理论基础.
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