Name
Abstract | ||
|---|---|---|
In this paper, we propose a technique for extracting salient objects in images using feature maps, regardless of the complexity of images and the position of objects. In order to extract salient objects, the proposed method uses feature maps with edge and color information. We also propose a reference map created by integrating feature maps, and a combination map representing the boundaries of meaningful objects that is created by integrating the reference map and feature maps. Candidate object regions including boundaries of objects from the combination map are extracted by convex hull algorithm. Finally, by applying a segmentation algorithm on the area of candidate regions, object regions and background regions are separated, and real object regions are extracted from the candidate object regions. Experimental results show that the proposed method extracts the salient objects efficiently, with 84.3% precision rate and 81.3% recall rate. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1109/ICASSP.2007.365983 | 2007 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, VOL I, PTS 1-3, PROCEEDINGS |
Keywords | Field | DocType |
salient object extraction, feature map, reference map, combination map, segmentation | Computer vision,Recall rate,Pattern recognition,Computer science,Segmentation,Salient objects,Image retrieval,Convex hull,Feature extraction,Image segmentation,Artificial intelligence,Flowchart | Conference |
ISSN | Citations | PageRank |
1520-6149 | 7 | 0.50 |
References | Authors | |
6 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ki Tae Park | 1 | 24 | 6.23 |
| Young Shik Moon | 2 | 110 | 16.82 |