Road detection in SAR images using genetic algorithm with region growing concept
Byoung-Ki Jeon
Jeong-Hun Jang
Ki-Sang Hong
POSTECH, Pohang, South Korea;
This paper appears in: Image Processing, 2000. Proceedings. 2000 International Conference on
Publication Date: 10-13 Sept. 2000
Volume: 2,
On page(s): 688-691 vol.2
Meeting Date: 09/10/2000 - 09/13/2000
Location: Vancouver, BC, Canada, Canada
ISSN: 1522-4880
ISBN: 0-7803-6297-7
References Cited: 11
INSPEC Accession Number: 6998703
Digital Object Identifier: 10.1109/ICIP.2000.899802
Current Version Published: 2002-08-06
Abstract
This paper presents a technique for the detection of roads in a spaceborne SAR image using a genetic algorithm. Roads in a spaceborne SAR image can be modelled as curvilinear structures with some thickness. Curve segments, which represent the candidate positions of roads, are extracted from the image using a curvilinear structure detector, and roads are detected accurately by grouping those curve segments. For this purpose, we designed a grouping method based on a genetic algorithm (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 images that have a resolution of about 30 meters. The experimental results show that our method can detect roads accurately and is much faster than a globally applied GA approach.
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