Title :
Methods and algorithms of cluster analysis in the mining industry: Solution of tasks for mineral rocks recognition
Author :
Olga E. Baklanova;Olga Ya Shvets
Author_Institution :
Department of Mathematical and Computer Modelling, D. Serikbayev East-Kazakhstan State Technical University, 19, Serikbaeva Street, Ust-Kamenogorsk, The Republic Kazakhstan
Abstract :
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.
Keywords :
"Image color analysis","Image segmentation","Minerals","Rocks","Clustering algorithms","Algorithm design and analysis","Microscopy"
Conference_Titel :
Signal Processing and Multimedia Applications (SIGMAP), 2014 International Conference on