Abstract
Representing the regions of a segmented image is an important aspect of image segmentation. Several different models have been proposed to represent the regions of a segmented image but most of them are dedicated to a specific method. Among the non hierarchical models, the model of planar maps with discrete embedding is certainly the most versatile one. Maps have the great advantage to provide a continuity of representation from the abstract mathematical model to the concrete implementation. They encode and provide most of topological and geometrical features required by segmentation algorithms and can be efficiently updated. In this paper we give an overview of the use of planar maps with discrete embedding in the context of image segmentation and we show how to design, implement and use a general environment for 2D image segmentation, from the mathematical model up to a real application. The model, data structure, algorithms and API described in this paper are currently implemented in a software which will be available under LGPL in the course of year 2005.
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Braquelaire, A. (2005). Representing and Segmenting 2D Images by Means of Planar Maps with Discrete Embeddings: From Model to Applications. In: Brun, L., Vento, M. (eds) Graph-Based Representations in Pattern Recognition. GbRPR 2005. Lecture Notes in Computer Science, vol 3434. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-31988-7_10
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DOI: https://doi.org/10.1007/978-3-540-31988-7_10
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