Grading of construction aggregate through machine vision: Results and prospects

被引：4
|
作者：
Murtagh, F [1 ]
Qiao, XY
Walsh, P
Basheer, PAM
Crookes, D
Long, A
机构：
[1] Univ London Royal Holloway & Bedford New Coll, Dept Comp Sci, Egham TW20 0EX, Surrey, England
[2] Queens Univ Belfast, Sch Comp Sci, Belfast BT7 1NN, Antrim, North Ireland
[3] Queens Univ Belfast, Sch Civil Engn, Belfast BT7 1NN, Antrim, North Ireland
来源：
COMPUTERS IN INDUSTRY | 2005年 / 56卷 / 8-9期
基金：
英国工程与自然科学研究理事会;
关键词：
machine vision; construction industry; wavelet transform; supervised and unsupervised classification; image database;
D O I：
10.1016/j.compind.2005.05.016
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
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. (c) 2005 Elsevier B.V. All rights reserved.
引用
收藏
页码：905 / 917
页数：13
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