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Automatic Extraction of Salient Objects Using Feature Maps

Title
Automatic Extraction of Salient Objects Using Feature Maps
Author
박기태
Keywords
Salient object extraction; Feature map; Reference map; Combination map; Segmentation
Issue Date
2007-04
Publisher
IEEE
Citation
2007 IEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP '07, Page. I-617-I-620
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.
URI
https://ieeexplore.ieee.org/abstract/document/4217155http://repository.hanyang.ac.kr/handle/20.500.11754/106374
ISSN
1520-6149; 2379-190X
DOI
10.1109/ICASSP.2007.365983
Appears in Collections:
ETC > 연구정보
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