- Title
- Extracting road centrelines from binary road images by optimizing geodesic lines
- Creator
- Zhou, Shaoguang; Lu, Guojun; Teng, Shyh; Zhang, Dengsheng
- Date
- 2016
- Type
- Text; Conference proceedings; Conference paper
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/154295
- Identifier
- vital:11104
- Identifier
-
https://doi.org/10.1109/IVCNZ.2015.7761524
- Identifier
- ISBN:21512191 (ISSN); 9781509003570 (ISBN)
- Abstract
- Binary road images can be obtained from remotely sensed images with the aid of classification and segmentation techniques. Extracting road centrelines from these binary images are crucial to update a Geographic Information System (GIS) database. A current state of art method of centreline extraction needs to remove road junctions and depends on the accuracy of the endpoints, leading to three main limitations: (1) causing small gaps in the roads, (2) wrongly treating short non-road segments as roads, and (3) producing centrelines of low accuracy around the road end regions. To overcome these limitations, we propose to use an iteratively searching scheme to obtain the longest geodesic line in the preprocessed road skeleton images. Several image pixels at each end of the geodesic lines were removed to avoid noise, and the remaining parts were optimized using a dynamic programming snake model. The proposed method is applied to three types of binary road images and compared with the state of art method. It shows that the proposed method is less affected by the end regions of the roads, and is effective in filling the gaps in the roads. It also has an advantage on processing short non-road segments. © 2015 IEEE.; International Conference Image and Vision Computing New Zealand
- Publisher
- IEEE Computer Society
- Relation
- 2015 International Conference on Image and Vision Computing New Zealand, IVCNZ 2015; Auckland, New Zealand; 23rd-24th November 2015 Vol. 2016-November, p. 1-6
- Rights
- Copyright ©2015 IEEE
- Rights
- This metadata is freely available under a CCO license
- Subject
- Geodesic line; Remotely sensed imagery; Road centreline extraction; Road extraction; Snake model; Binary images; Bins; Dynamic programming; Extraction; Feature extraction; Geodesy; Geographic information systems; Image segmentation; Iterative methods; Remote sensing; Roads and streets; Transportation; Centreline extraction; Geodesic lines; Image processing
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