Automated sewer inspection using image processing and a neural classifier

被引：8

作者：

Duran, O ^{[1
]}

Althoefer, K ^{[1
]}

Seneviratne, LD ^{[1
]}

机构：

[1] Kings Coll London, Dept Mech Engn, London WC2R 2LS, England

来源：

PROCEEDING OF THE 2002 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS, VOLS 1-3 | 2002年

关键词：

D O I：

10.1109/IJCNN.2002.1007652

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The focus of the research presented here is on the automated assessment of sewer pipe conditions using a laser-based sensor. The proposed method involves image and data processing algorithms categorising signals acquired from the internal pipe surface. Fault identification is carried out using a neural network. Experimental results are presented.

引用

页码：1126 / 1131

页数：2

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