Multiscalar rock recognition using active vision

This paper describes an active vision approach to rock recognition for the purpose of measuring rock size distributions or fragmentation. Such a measure is useful in the mining industry to facilitate the control and monitoring of autogenous mills. A new approach for recognising and segmenting rock images is described. It is based on rapid identification of targets at which attention is focused for analysis. In addition, a multiscalar image pyramid is used in a novel way to allow target detection and analysis to be optimised for a particular size, thereby improving their performances. The results that have been obtained with this approach are both robust and accurate.

[1]  Xing-Qiang Wu,et al.  A segmentation method for multi-connected particle delineation , 1992, [1992] Proceedings IEEE Workshop on Applications of Computer Vision.

[2]  D Marr,et al.  Theory of edge detection , 1979, Proceedings of the Royal Society of London. Series B. Biological Sciences.

[3]  John M Kemeny,et al.  Practical technique for determining the size distribution of blasted benches, waste dumps and heap leach sites , 1994 .

[4]  K JainAnil,et al.  Small Sample Size Effects in Statistical Pattern Recognition , 1991 .

[5]  Thomas S. Huang,et al.  Image processing , 1971 .

[6]  G. de Jager,et al.  Rock recognition using feature classification , 1994, Proceedings of COMSIG '94 - 1994 South African Symposium on Communications and Signal Processing.

[7]  G. Hunter,et al.  A review of image analysis techniques for measuring blast fragmentation , 1990 .