In this research, first of all, the existing problems in fragmentation measurement are reviewed for the sake of its fast and reliable evaluation. Then, the available methods used for evaluation of blast results are mentioned. The produced errors especially in recognizing the rock fragments in computer-aided methods, and also, the importance of determination of their sizes in the image analysis methods are described. After reviewing the previous work done, an algorithm is proposed for the automated determination of rock particles’ boundary in the Matlab software. This method can determinate automatically the particles boundary in the minimum time. The results of proposed method are compared with those of Split Desktop and GoldSize software in two automated and manual states. Comparing the curves extracted from different methods reveals that the proposed approach is accurately applicable in measuring the size distribution of laboratory samples, while the manual determination of boundaries in the conventional software is very time-consuming, and the results of automated netting of fragments are very different with the real value due to the error in separation of the objects.
Sereshki, F., Hoseini, M., & Ataei, M. (2016). Fragmentation measurement using image processing. International Journal of Mining and Geo-Engineering, 50(2), 211-218. doi: 10.22059/ijmge.2016.59831
MLA
Farhang Sereshki; Morteza Hoseini; Mohammad Ataei. "Fragmentation measurement using image processing", International Journal of Mining and Geo-Engineering, 50, 2, 2016, 211-218. doi: 10.22059/ijmge.2016.59831
HARVARD
Sereshki, F., Hoseini, M., Ataei, M. (2016). 'Fragmentation measurement using image processing', International Journal of Mining and Geo-Engineering, 50(2), pp. 211-218. doi: 10.22059/ijmge.2016.59831
VANCOUVER
Sereshki, F., Hoseini, M., Ataei, M. Fragmentation measurement using image processing. International Journal of Mining and Geo-Engineering, 2016; 50(2): 211-218. doi: 10.22059/ijmge.2016.59831
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