Name
Abstract | ||
|---|---|---|
Segmentation based on active contour has been received widespread concerns recently for its good flexible performance. However, most available active contour models lack adaptive initial contour and priori information of target region. In this paper, we presented a new method that is based on active contours combined with saliency map for plant leaf segmentation. Firstly, priori shape information of target objects in input leaf image which is used to describe the initial curve adaptively is extracted with the visual saliency detection method in order to reduce the influence of initial contour position. Furthermore, the proposed active model can segment images adaptively and automatically. Experiments on two applications demonstrate that the proposed model can achieve a better segmentation result. |
Year | Venue | Field |
|---|---|---|
2015 | ICIG | Active contour model,Computer vision,Saliency map,Scale-space segmentation,Pattern recognition,Segmentation,Computer science,Image segmentation,Artificial intelligence,Visual saliency |
DocType | Citations | PageRank |
Conference | 2 | 0.36 |
References | Authors | |
7 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Qiangqiang Zhou | 1 | 37 | 3.43 |
| Zhicheng Wang | 2 | 176 | 17.00 |
| weidong zhao | 3 | 77 | 14.73 |
| Yufei Chen | 4 | 2 | 0.36 |