OU Jianliang, BAO Feng, WANG Weian, LU Jiao. Building and Road Characteristic Line-segment Automatic Classification Research of Ground Mobile Mapping Close-range Imagery[J]. Geomatics and Information Science of Wuhan University, 2011, 36(1): 60-65.
Citation:
OU Jianliang, BAO Feng, WANG Weian, LU Jiao. Building and Road Characteristic Line-segment Automatic Classification Research of Ground Mobile Mapping Close-range Imagery[J]. Geomatics and Information Science of Wuhan University, 2011, 36(1): 60-65.
OU Jianliang, BAO Feng, WANG Weian, LU Jiao. Building and Road Characteristic Line-segment Automatic Classification Research of Ground Mobile Mapping Close-range Imagery[J]. Geomatics and Information Science of Wuhan University, 2011, 36(1): 60-65.
Citation:
OU Jianliang, BAO Feng, WANG Weian, LU Jiao. Building and Road Characteristic Line-segment Automatic Classification Research of Ground Mobile Mapping Close-range Imagery[J]. Geomatics and Information Science of Wuhan University, 2011, 36(1): 60-65.
1 Department of Survey and Geo-Informatics,Tongji University,1239 Siping Road,Shanghai 200092,China;2 College of Aerospace and Material Engineering,National University of Defense Technology,Yanwachi Street,Changsha 410073,China
Ground mobile mapping system(MMS) is a brand-new integration system in survey and mapping field.It collects digital measurable real imagery for geo-objects(e.g.building and road) with multi-and ground-views easily.MMS works in a lower cost and higher speed way compared to other survey methods,and its imagery data contains rich information for observed objects.It becomes a fundamental issue for the observed object characteristic line-segments to be classified from MMS imagery accurately and rapidly.The paper presented a new method that including mathematic model between building and road 3D characteristic lines and MMS imagery with vanishing point theory,and imagery line-segment classification and filtering by vanishing points.Experiment result shows that object characteristic line-segments were obtained completely while other noise line-segments excluded accurately and the total number of relevant imagery line-segments is reduced markedly.Thus,an important basic work of automatic object measuring and imagery understanding is finished in the paper.
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