Complex curve tracing based on a minimum spanning tree model and regularized fuzzy clustering
The fuzzy curve-tracing (FCT) algorithm can be used to extract a smooth curve from unordered noisy data. However, the model produces good results only if the curve shape is either opened or closed. In this paper, we propose several techniques to generalize the FCT algorithm for tracing complicated c...
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| Published in: | 2004 International Conference on Image Processing, 2004. ICIP '04 Vol. 3; pp. 2091 - 2094 Vol. 3 |
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| Main Authors: | , |
| Format: | Conference Proceeding |
| Language: | English |
| Published: |
Piscataway NJ
IEEE
2004
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| Subjects: | |
| ISBN: | 0780385543, 9780780385542 |
| ISSN: | 1522-4880 |
| Online Access: | Get full text |
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| Summary: | The fuzzy curve-tracing (FCT) algorithm can be used to extract a smooth curve from unordered noisy data. However, the model produces good results only if the curve shape is either opened or closed. In this paper, we propose several techniques to generalize the FCT algorithm for tracing complicated curves. We develop a modified clustering algorithm that can produce cluster centers less dependent on the pre-specified number of clusters, which makes the reordering of cluster centers easier. We make use of the Eikonal equation and the Prim's algorithm to form the initial curve, which may contain sharp corners and intersections. We also introduce a more powerful curve smoothing method. Our generalized FCT algorithm is able to trace a wide range of complicated curves, such as handwritten Chinese characters. |
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| ISBN: | 0780385543 9780780385542 |
| ISSN: | 1522-4880 |
| DOI: | 10.1109/ICIP.2004.1421497 |

