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2 December 2005 Application of knowledge based watershed transform approach to road detection
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Proceedings Volume 6045, MIPPR 2005: Geospatial Information, Data Mining, and Applications; 60452D (2005) https://doi.org/10.1117/12.651577
Event: MIPPR 2005 SAR and Multispectral Image Processing, 2005, Wuhan, China
Abstract
An approach for automatic road extraction from remote sensing image is presented. The extraction is based on the knowledge about the road in high-resolution image. The information about the road is utilized to implement the watershed algorithm and guide the region merging. First, the Kalman filter algorithm is used to detect the straight line in the image, the center point of parallel line pairs is utilized as marker point to modify the morphological gradient of the input image by geodesic reconstruction, the modified gradient image is then segmented by the watershed transform. The segmentation result is input to region merging process. This process applies the region adjacency graph (RAG) representation of the segmented regions and knowledge about the road to execute the region merging, which significantly reduce the merging time. The proposed scheme was tested on remote sensing images of 2m resolution, and the results show that the extraction of road is quite promising.
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Tiancan Mei, Deren Li, and Qianqing Qin "Application of knowledge based watershed transform approach to road detection", Proc. SPIE 6045, MIPPR 2005: Geospatial Information, Data Mining, and Applications, 60452D (2 December 2005); https://doi.org/10.1117/12.651577
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