图像灰度信息在煤矸石自动分选中的应用研究

摘要

针对传统的基于图像灰度信息的块煤和矸石分选系统只是随意地选择块煤和矸石样本而缺乏代表性和实用性的问题,研究了一种侧重于实用性和系统性的基于图像灰度信息的块煤和矸石自动分选系统.首先从材质、纹理特征、清洁度三个方面选择6块比较有代表性的块煤或矸石,分别在强光、自然光和节能灯光三种强度光照条件下,按照一定的分组方式分析它们的图像灰度分布规律并将其作为计算机目标识别的依据,从而实现块煤或矸石的自动分选.测试结果表明,在特定条件下,利用块煤与矸石图像灰度信息较明显的差异对两者进行视觉区别可实现两者的自动分选.%In view of problems of no representation and practicality because that traditional separation system of lump coal and gangue based on image gray information only randomly selects samples of coal and gangue, the paper researched an automatic separation system of lump coal and gangue based on image gray information which emphasized in practicality and system. At first, it selected six representative lump coals and gangues in term of material, texture feature and cleanness, and analyzed distribution law of image gray of the six lump coals and gangues according to certain group mode under conditions of strong light, natural light and energy-saving lamp light and made the distribution law as basis of object recognition of computer, so as to realize automatic separation for lump coal and gangue. The test result showed that using obvious differences of image gray information between lump coal and gangue to make visual distinction can realize automatic separation under special conditions.