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Extraction of road lanes from high-resolution stereo aerial imagery based on maximum likelihood segmentation and texture enhancement

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.

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Abstract

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.

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ID Code: 31343
Item Type: Conference Paper
Keywords: road lane extraction, stereo aerial imagery, image analysis
DOI: 10.1109/DICTA.2009.52
ISBN: 9781424452972
Subjects: Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > GEOMATIC ENGINEERING (090900) > Photogrammetry and Remote Sensing (090905)
Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > GEOMATIC ENGINEERING (090900) > Geospatial Information Systems (090903)
Divisions: Past > QUT Faculties & Divisions > Faculty of Science and Technology
Copyright Owner: Copyright 2009 IEEE Computer Society
Copyright Statement: 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.
Deposited On: 17 Mar 2010 07:59
Last Modified: 01 Mar 2012 00:12

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