Salient Region Detection Based on SLIC and Graph-based Segmentation
Xiaofei Sun, Wenwen Pan, Xia Wang, Xuhong Li, Guan Wang
Available Online September 2016.
- https://doi.org/10.2991/amitp-16.2016.96How to use a DOI?
- saliency map; graph-based image segmentation; SLIC, color sparse histogram.
- 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.
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 BT - Proceedings of the 2016 4th International Conference on Advanced Materials and Information Technology Processing (AMITP 2016) 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 -