Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
9668099 | Computers in Industry | 2005 | 13 Pages |
Abstract
Traditionally, crushed aggregate to be used in construction is graded using sieves. We describe an innovative machine vision approach to such grading. Our operational scenario is one where a camera takes images from directly overhead of a layer of aggregate on a conveyor belt. In this article, we describe effective solutions for (i) image segmentation, allowing larger pieces of aggregate to be measured and (ii) supervised classification from wavelet entropy features, for class assignment of both finer and coarse aggregate.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science Applications
Authors
Fionn Murtagh, Xiaoyu Qiao, Paul Walsh, P.A.M. Basheer, Danny Crookes, Adrian Long,