Name
Title | ||
|---|---|---|
Morphological gradient applied to new active contour model for color image segmentation |
Abstract | ||
|---|---|---|
In this paper, we propose a novel segmentation algorithm for color images. This method is a combination of edge information with region information and a geometric active contour without re-initialization, called distance regularized level set evolution. The information given by a new edge detector using morphological gradient is more accurate than normal gradient computing methods for color images. And the information of the region containing objects is relied on Chan-Vese minimal variance criterion. With both of these information, the model can have its initial contour that is more flexible to construct anywhere, fast to evolve and quite exact to stop at the boundary of objects. The suggested algorithm has been applied on natural color images with good performance. Some experimental results have shown to compare our model with others with respect to accuracy and computational efficiency. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1145/2184751.2184778 | ICUIMC |
Keywords | Field | DocType |
edge information,new active contour model,region information,morphological gradient,natural color image,novel segmentation algorithm,new edge detector,initial contour,color image,geometric active contour,color image segmentation,normal gradient computing method,active contour model,level set,active contour | Active contour model,Computer vision,Image gradient,Color histogram,Pattern recognition,Segmentation,Computer science,Level set,Image segmentation,Artificial intelligence,Morphological gradient,Color gradient | Conference |
Citations | PageRank | References |
5 | 0.42 | 12 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Nguyen Tran Lan Anh | 1 | 6 | 1.47 |
| Youngchul Kim | 2 | 92 | 21.26 |
| Gueesang Lee | 3 | 208 | 52.71 |