Abstract
Topological maps are graph-like spatial representations. To mitigate the above drawbacks of existing image segmentation algorithms, we propose a general theory of topological maps based on the abstract data structure whereby sensory input, topological and local metrical information are combined to define the topological maps explaining such information. In order to put the theory here proposed into computational practice, we provide two improvement algorithms on conventional region-based and edge-based image segmentation methods, which aim to extract directly regional boundaries and topological maps from the pixel sets in the processing of remote sensing image segmentation. The experimental results show that the two algorithms support different exploration strategies and facilitates map disambiguation when perceptual aliasing arises, and remain well the geometric topology information.
The research is supported by the Director Fund (IS201116002) from Institute of Seismology, China Earthquake Administration, and the National Science and Technology Support Project (2012BAH01F02) from Ministry of Science and Technology of the People’s Republic of China.
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Liu, X., Zhu, G., Li, X. (2013). Topological Relationship Extraction by Two Improved Image Segmentation Methods. In: Bian, F., Xie, Y., Cui, X., Zeng, Y. (eds) Geo-Informatics in Resource Management and Sustainable Ecosystem. Communications in Computer and Information Science, vol 398. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-45025-9_53
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DOI: https://doi.org/10.1007/978-3-642-45025-9_53
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