Name
Abstract | ||
|---|---|---|
Variational models have been studied for image segmentation application since the Mumford-Shah functional was introduced in the late 1980s. In this paper, we focus on multiphase segmentation with a new regularization term that yields an unsupervised segmentation model. We propose a functional that automatically chooses a favorable number of phases as it segments the image. The primary driving force of the segmentation is the intensity fitting term while a phase scale measure complements the regularization term. We propose a fast, yet simple, brute-force numerical algorithm and present experimental results showing the robustness and stability of the proposed model. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/TIP.2009.2032310 | IEEE Transactions on Image Processing |
Keywords | Field | DocType |
unsupervised segmentation model,multiphase segmentation,brute-force numerical algorithm,intensity fitting term,image segmentation application,unsupervised multiphase segmentation,variational model,new regularization term,favorable number,regularization term,logic,scale,image segmentation,numerical analysis,computer science,level set,mathematics | Mumford–Shah functional,Computer vision,Scale-space segmentation,Pattern recognition,Segmentation,Segmentation-based object categorization,Image processing,Image segmentation,Robustness (computer science),Regularization (mathematics),Artificial intelligence,Mathematics | Journal |
Volume | Issue | ISSN |
19 | 1 | 1941-0042 |
Citations | PageRank | References |
13 | 0.68 | 17 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Berta Sandberg | 1 | 27 | 1.36 |
| Sung Ha Kang | 2 | 430 | 29.39 |
| Tony F. Chan | 3 | 8733 | 659.77 |