采矿业聚类分析方法与算法:矿物岩石识别任务的解决方案

O. Baklanova, O. Shvets
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引用次数: 5

摘要

介绍了利用聚类分析方法对矿石彩色图像进行自动分割的算法。实例说明了该算法在解决矿物岩石识别问题中的应用。研究结果通过k-means聚类展示了不同的色彩空间。它被认为是预先计算质心值的技术。有公式转换度量颜色空间HSV。本文方法的有效性在于自动识别图像上的感兴趣对象,算法的调优参数是一个表示分配给片段数量的数字。本文简要介绍了用于矿业矿物岩石识别的聚类分析算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Methods and algorithms of cluster analysis in the mining industry: Solution of tasks for mineral rocks recognition
It is described the algorithm for automatic segmentation of colour images of ores, using the methods of cluster analysis. There are some examples illustrated using of the algorithm in the solving of mineral rock recognition problems. Results of studies are demonstrated different colour spaces by k-means clustering. It was supposed the technique of pre-computing the values of the centroids. There is formulas translation metrics colour space HSV. The effectiveness of the proposed method lies in the automatic identification of interest objects on the total image, tuning parameters of the algorithm is a number that indicates the amount allocated to the segments. This paper contains short description of cluster analysis algorithm for the mineral rock recognition in the mining industry.
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