Automatic extraction of roads from aerial images based on scale space and snakes
Machine Vision and Applications
Image Retrieval Via Isotropic and Anisotropic Mappings
PRIS '01 Proceedings of the 1st International Workshop on Pattern Recognition in Information Systems: In conjunction with ICEIS 2001
A system to detect houses and residential street networks in multispectral satellite images
Computer Vision and Image Understanding
Compound geospatial object detection in an aerial image
VISUAL'07 Proceedings of the 9th international conference on Advances in visual information systems
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A novel region-based perceptual grouping algorithm is proposed for road segment identifying in urban areas from aerial images. Unlike the conventional edge-based approaches, our grouping is regional basis. An imagery scene is modelled by the spectrally homogeneous regions restrained in shape and size. Given a set of low level image features, perceptual grouping is performed on the regions to generate a higher level of structure, from which road segments are extracted. In our unique approach, perceptual grouping is based on the similarity of spectral, orientation and proximity of the candidate regions. The road candidates are further merged into larger regions in terms of their orientation and adjacency. The road segments are extracted from these merged regions on geometric measurement. Experiments were carried out on imagery of real scenes for evaluation. The results showed the approach has the advantage of distinguishing roads from artefacts caused by parking lots and buildings.