Proceedings of the 2016 4th International Conference on Advanced Materials and Information Technology Processing (AMITP 2016)

Salient Region Detection Based on SLIC and Graph-based Segmentation

Authors
Xiaofei Sun, Wenwen Pan, Xia Wang, Xuhong Li, Guan Wang
Corresponding Author
Xiaofei Sun
Available Online September 2016.
DOI
https://doi.org/10.2991/amitp-16.2016.96How to use a DOI?
Keywords
saliency map; graph-based image segmentation; SLIC, color sparse histogram.
Abstract
At present, the most recent saliency detection algorithms are still not satisfactory. A saliency detection algorithm based on SLIC and graph-based segmentation is proposed. Firstly, graph-based segmentation is used to obtain larger image partitions, and the partitions with good contours are acquired. Then the relatively detailed partitions are obtained using SLIC image segmentation. Sparse color histogram is applied to these two methods. By using the color and spatial distance information, the saliency of each partition is calculated. Contours of salient objects from saliency maps generated using Graph-Based Segmentation are acquired and the gray scale values of the two kinds of saliency maps in the area surrounded by contours are merged. Experimental results show that compared with other detection methods, the proposed algorithm can effectively detect the salient object in the image.
Open Access
This is an open access article distributed under the CC BY-NC license.

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Proceedings
Part of series
Advances in Computer Science Research
Publication Date
September 2016
ISBN
978-94-6252-245-9
ISSN
2352-538X
DOI
https://doi.org/10.2991/amitp-16.2016.96How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Xiaofei Sun
AU  - Wenwen Pan
AU  - Xia Wang
AU  - Xuhong Li
AU  - Guan Wang
PY  - 2016/09
DA  - 2016/09
TI  - Salient Region Detection Based on SLIC and Graph-based Segmentation
PB  - Atlantis Press
SP  - 482
EP  - 486
SN  - 2352-538X
UR  - https://doi.org/10.2991/amitp-16.2016.96
DO  - https://doi.org/10.2991/amitp-16.2016.96
ID  - Sun2016/09
ER  -