MOTION ESTIMATION IN FLOTATION FROTH USING THE KALMAN FILTER

被引：0

作者：

Amankwah, Anthony ^{[1
]}

Aldrich, Chris ^{[2
,3
]}

机构：

[1] Univ Ghana, Sch Comp Sci, LG 25, Accra, Ghana

[2] Dept Proc Engn, Private Bag X1, ZA-7602 Stellenbosch, South Africa

[3] Western Australia Sch Mines, GPO Box 1987, Perth, WA 6845, Australia

来源：

2015 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS) | 2015年

关键词：

Kalman filter; motion estimation; froth flotation; SEARCH ALGORITHM;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Machine vision systems have been used to monitor mineral froth flotation systems since the 1990s and their ability to track key performance indicators of the systems online is critical to improved plant operation. One of the challenges faces by these computer vision systems, is estimation of the motion of the froth, which is hindered by the simultaneous deformation, bursting and merging of bubbles. In this paper, we propose a block based motion estimation method using Kalman filtering to improve the motion vector estimates resulting from the new-three-step-search technique. Experimental results derived from flotation froth video sequences are presented.

引用

页码：1897 / 1900

页数：4

共 13 条

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