Name
Abstract | ||
|---|---|---|
This paper presents a new image segmentation method via fusing Normalized Cut (NCut) eigenvector maps. In this method, we fuse the eigenvector maps by maximizing the salient contour signals and suppress the non-maximum ones. Then, we use OWT-UCM method to produce the image segmentation from the soft contour map generated from the fused eigenvector maps and local contour cues. We evaluate our segmentation method based on BSDS500 database. Experimental results show that the proposed segmentation method is more accurate and preserve large meaningful region. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1117/12.956472 | Proceedings of SPIE |
Keywords | Field | DocType |
Image segmentation,NCut,Eigenvector,Fusion | Computer vision,Scale-space segmentation,Normalization (statistics),Pattern recognition,Segmentation,Computer science,Contour line,Segmentation-based object categorization,Image segmentation,Artificial intelligence,Fuse (electrical),Eigenvalues and eigenvectors | Conference |
Volume | Issue | ISSN |
8334 | null | 0277-786X |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tiejun Zhang | 1 | 10 | 3.21 |
| Ahmed A. Abd El-Latif | 2 | 371 | 36.32 |
| Ning Wang | 3 | 83 | 7.85 |
| Qiong Li | 4 | 68 | 10.69 |
| Xiamu Niu | 5 | 754 | 91.72 |