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DALIAN UNIVERSITY OF TECHNOLOGY Login 中文
Wang Zhelong

Professor
Supervisor of Doctorate Candidates
Supervisor of Master's Candidates


Main positions:Professor, Head of Lab of Intelligent System
Other Post:自动化技术研究所所长
Gender:Male
Alma Mater:University of Durham
Degree:Doctoral Degree
School/Department:School of Control Science and Engineering
Discipline:Control Theory and Control Engineering. Pattern Recognition and Intelligence System. Detection Technology and Automation Device
Business Address:Lab of Intelligent System
http://lis.dlut.edu.cn/

Contact Information:0411-84709010 wangzl@dlut.edu.cn
E-Mail:wangzl@dlut.edu.cn
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A cavity detection method based on machine vision

Hits : Praise

Indexed by:会议论文

Date of Publication:2010-01-01

Included Journals:EI、Scopus

Volume:3

Page Number:V3111-V3115

Abstract:In order to search and rescue the victims in rubble effectively, a 3D model of the cavity is required. This paper presents a cavity detection method based on machine vision for disaster rescue robot. Laser ring projection technique is developed to lighten the profile of cross-section of the cavity and draw a line around the internal surface. A CMOS camera is used to capture the images which consist of essential profile information as well as various noises. The method of image acquiring and image preprocessing is also described. However, due to the inevitable influence of the harsh environment and lighting conditions, the profile in the acquired image might be partitioned into several segments. Thus, a method of detecting the curve segments based on vector argument is proposed. The 3D model of the cavity is reconstructed by using a series of complete and accurate cross-section profiles which are fitted by the improved cubic B-spline interpolation. Experimental results show that the proposed profile tracking algorithm is effective and adaptable. ? 2010 IEEE.