Road detection in spaceborne SAR images using a genetic algorithm
SCIE
SCOPUS
- Title
- Road detection in spaceborne SAR images using a genetic algorithm
- Authors
- Jeon, BK; Jang, JH; Hong, KS
- Date Issued
- 2002-01
- Publisher
- IEEE-INST ELECTRICAL ELECTRONICS ENGI
- Abstract
- This paper presents a technique for the detection of roads in a spaceborne synthetic aperture radar (SAR) image using a genetic algorithm (GA). Roads in a spaceborne SAR image can be modeled as curvilinear structures that possess width. Curve segments, which represent the candidate positions for roads, are extracted from the image using a curvilinear structure detector, and the roads are accurately detected by grouping those curve segments. For this purpose, we designed a grouping method based on a GA, which is a global optimization method. We combined perceptual grouping factors with it and tried to reduce its overall computational cost by introducing a concept of region growing. In this process, a selected initial seed is grown into a finally grouped segment by the iterated GA process, which considers segments only in a search region. To detect roads more accurately, postprocessing, including noisy curve segment removal, is performed after grouping. We applied our method to ERS-1 SAR and SIR-C/X-SAR images that have a resolution of about 30 m. The experimental results show that our method can accurately detect road networks as well as single-track roads and is much faster than a globally applied GA approach.
- Keywords
- genetic algorithm (GA); perceptual grouping; road detection; synthetic aperture radar (SAR); EXTRACTION
- URI
- https://oasis.postech.ac.kr/handle/2014.oak/19212
- DOI
- 10.1109/36.981346
- ISSN
- 0196-2892
- Article Type
- Article
- Citation
- IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, vol. 40, no. 1, page. 22 - 29, 2002-01
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