Abstract
In this paper we present an image segmentation technique based on the concepts of circulation and topological control. Circulation is a mathematical tool widely used for engineering problems, but still little explored in the field of image processing. On the other hand, by controlling the topology it is possible to dictate the number of regions in the segmentation process. If we take very small regions as noise, the mechanism can be seen as an efficient means for noise reduction. This has motivated us to combine both mathematical tool in our algorithm. As a result, we obtained an automatic segmentation algorithm that generates segmented regions bounded by simple closed curves; a desireable characteristic in many applications.
Keywords
- Image Segmentation
- Adjacent Region
- Boundary Curve
- Euler Characteristic
- Markov Random Fields
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Nonato, L.G., da Silva, A.M., Batista, J., Bruno, O.M. (2005). Circulation and Topological Control in Image Segmentation. In: Sanfeliu, A., Cortés, M.L. (eds) Progress in Pattern Recognition, Image Analysis and Applications. CIARP 2005. Lecture Notes in Computer Science, vol 3773. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11578079_40
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DOI: https://doi.org/10.1007/11578079_40
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-29850-2
Online ISBN: 978-3-540-32242-9
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