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有色金属(矿山部分):2019,71(6):110-115
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混配矿石图像的分割优化及级配检测算法
((中国矿业大学(北京)机电与信息工程学院, 北京 100083))
Segmentation optimization and grading detection algorithm of mixed ore images
((China University of Mining & Technology, Beijing 100083, China))
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中文摘要: 混配矿石的粒级分布自动检测直接指导生产及施工过程,基于图像分析的混配矿石粒级统计,可用于现场实时检测。从图像中准确分割出大量混配矿石的边界,受到噪声、矿石目标粘连等问题的干扰。提出了一种基于密度变换的分割优化方法,在阈值图像中,通过矿石图像邻域的密度统计,去除噪声像素及矿石目标粘连问题。根据几何形态特征检测粒径,统计粒级分布,绘制级配曲线。实验结果表明,所提优化方法的分割结果及粒度分布,与筛分测量的级配曲线吻合度高,可用于施工现场级配检测。
Abstract:The automatic detection of the particle size distribution of the mixed ore directly guides the production and construction process, and the particle size analysis of the mixed ore based on image analysis can be used for on-site real-time detection. The boundary of massive mixed ore is accurately segmented from the image, and is disturbed by problems such as noise and adhesion of ore targets. This paper proposes a segmentation optimization method based on density transform. In the threshold image, the noise pixel and ore target adhesion problem are removed by the density statistics of the ore image neighborhood. The particle size is detected according to geometric morphological features, the particle size distribution is calculated, and the gradation curve is drawn. The experimental results show that the segmentation result and particle size distribution of the proposed optimization method are consistent with the gradation curve of the screening measurement, and can be used for grading detection at the construction site.
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基金项目:国家自然科学基金资助项目(U1704242)
引用文本:
谢雅君,张国英.混配矿石图像的分割优化及级配检测算法[J].有色金属(矿山部分),2019,71(6):110-115.
XIE Yajun, ZHANG Guoying,XIE Yajun, ZHANG Guoying.Segmentation optimization and grading detection algorithm of mixed ore images[J].NONFERROUS METALS(Mining Section),2019,71(6):110-115.

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