An Improvement on C-V Model
Minggang Jing, Jitao Wu, Xiaotao Wang
Available Online December 2013.
- https://doi.org/10.2991/wiet-13.2013.36How to use a DOI?
- C-V model; Level Set Method; Image Segmen-tation
- C-V model has the advantage of being able to detect boundaries of objects that are not defined by gradient. However, when detecting these types of edges, the C-V model only considers the average value of each region without local information. As a result, its segmentation result may exist errors, when detecting non-gradient defined boundaries. In order to overcome this problem, we modify the fitting term of classical C-V model with an extra weight. This weight can control the relative height of zero-level contour, so the new method can decrease the segmentation errors. Experiments show that the new model can obtain more accurate results and segment multi-phase images by setting proper weights.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Minggang Jing AU - Jitao Wu AU - Xiaotao Wang PY - 2013/12 DA - 2013/12 TI - An Improvement on C-V Model BT - AASRI Winter International Conference on Engineering and Technology (AASRI-WIET 2013) PB - Atlantis Press SP - 154 EP - 157 SN - 1951-6851 UR - https://doi.org/10.2991/wiet-13.2013.36 DO - https://doi.org/10.2991/wiet-13.2013.36 ID - Jing2013/12 ER -