Abstract
Automated tongue image segmentation in Chinese medicine is difficult due to two special factors: (1) There are a lot of pathological details on the surface of tongue, which have a large influence on edge extraction; (2) The shapes of tongue bodies captured from various diseases or persons are quite different, so they are impossible to be properly described by a predefined deformable template. To address these problems, in this paper, we propose an original technique based on the combination of a bielliptical deformable template and an active contour model, namely Bi-Elliptical Deformable Contour (BEDC). Applying our approach to clinical tongue images, the experimental results indicate that it is superior over both traditional DT (Deformable Templates) and ACM (Active Contour Model or Snakes) with respect to stability and veracity.
| Original language | English |
|---|---|
| Pages (from-to) | 616-619 |
| Number of pages | 4 |
| Journal | Proceedings - International Conference on Pattern Recognition |
| Volume | 16 |
| Issue number | 1 |
| State | Published - 2002 |
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