Abstract
Contour segmentation problem is investigated in the context of an object recognition system dealing with overlapping parts. A knowledge based approach is adopted, in order to get stable results. Contours are described by curvature function. Angles are detected in a preliminary phase. Dynamic programming allows a fast approximation with straight lines and circle arcs. A simple rule based system is developed in order to choose the best approximation. Some results are discussed.
Keywords
- Curvature Function
- Optimal Partition
- Straight Segment
- Morphological Filter
- Constant Piecewise Approximation
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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© 1988 Plenum Press, New York
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Mangili, F., Viano, G. (1988). A Dynamic Programming Approach to Knowledge Based Contour Segmentation. In: Cantoni, V., Di Gesù, V., Levialdi, S. (eds) Image Analysis and Processing II. Springer, Boston, MA. https://doi.org/10.1007/978-1-4613-1007-5_14
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DOI: https://doi.org/10.1007/978-1-4613-1007-5_14
Publisher Name: Springer, Boston, MA
Print ISBN: 978-1-4612-8289-1
Online ISBN: 978-1-4613-1007-5
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