Name
Abstract | ||
|---|---|---|
With saliency map generated from visual attention model, this paper proposes two regions of interest ROI extraction algorithms respectively based on salient points and saliency regions. The former one adopts statistical and clustering techniques, selects cluster centre as seed points to fill outline map of image and finally makes mask operation between filled outline map and input image to implement ROI extraction. The latter one is based on salient regions, uses improved Grabcut image segmentation algorithm and saliency map generated from visual attention model to implement ROI extraction. To evaluate the performance of two proposed algorithms, this paper uses extracted ROI based on eye-movement data as evaluation criterion. The results show the algorithm based on salient points is applicable to extract simple images and has less runtime. The algorithm based on saliency regions is applicable to extract colourful and complex image. These two algorithms can be combined to get better performance. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1504/IJAACS.2016.075392 | IJAACS |
Field | DocType | Volume |
Computer vision,Saliency map,Pattern recognition,Salience (neuroscience),Computer science,GrabCut,Image segmentation,Artificial intelligence,Region of interest,Salience (language),Cluster analysis,Salient | Journal | 9 |
Issue | Citations | PageRank |
1/2 | 0 | 0.34 |
References | Authors | |
11 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zailiang Chen | 1 | 43 | 9.10 |
| Huajie Huang | 2 | 0 | 0.34 |
| Hailan Shen | 3 | 1 | 2.72 |
| Beiji Zou | 4 | 231 | 41.61 |
| Jiang Wang | 5 | 13 | 4.58 |