Extraction of road lanes from high-resolution stereo aerial imagery based on maximum likelihood segmentation and texture enhancement
Data(s) |
01/12/2009
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Resumo |
Accurate road lane information is crucial for advanced vehicle navigation and safety applications. With the increasing of very high resolution (VHR) imagery of astonishing quality provided by digital airborne sources, it will greatly facilitate the data acquisition and also significantly reduce the cost of data collection and updates if the road details can be automatically extracted from the aerial images. In this paper, we proposed an effective approach to detect road lanes from aerial images with employment of the image analysis procedures. This algorithm starts with constructing the (Digital Surface Model) DSM and true orthophotos from the stereo images. Next, a maximum likelihood clustering algorithm is used to separate road from other ground objects. After the detection of road surface, the road traffic and lane lines are further detected using texture enhancement and morphological operations. Finally, the generated road network is evaluated to test the performance of the proposed approach, in which the datasets provided by Queensland department of Main Roads are used. The experiment result proves the effectiveness of our approach. |
Formato |
application/pdf |
Identificador | |
Publicador |
IEEE Computer Society |
Relação |
http://eprints.qut.edu.au/31343/1/c31343a.pdf DOI:10.1109/DICTA.2009.52 Jin, Hang, Feng, Yanming, & Li, Zhengrong (2009) Extraction of road lanes from high-resolution stereo aerial imagery based on maximum likelihood segmentation and texture enhancement. In Proceedings of DICTA 2009 : Digital Image Computing :Techniques and Applications, IEEE Computer Society, Medina Grand Melbourne, Melbourne, Victoria. |
Direitos |
Copyright 2009 IEEE Computer Society Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. |
Fonte |
Faculty of Science and Technology |
Palavras-Chave | #090905 Photogrammetry and Remote Sensing #090903 Geospatial Information Systems #road lane extraction #stereo aerial imagery #image analysis |
Tipo |
Conference Paper |