Graph Based Image Saliency Detection

DOI

10.2991/cmes-15.2015.180How to use a DOI?

Keywords

Image Saliency; Absorbing Markov chain; Manifold Ranking; Saliency map

Abstract

In this paper, we propose a new saliency detection method based on graph. The method firstly uses SLIC to segment the image into a set of superpixels which are not overlapped, and regards these superpixels as nodes of the graph, then constructs a partly connected graph with these nodes. Secondly, the saliency values of these nodes are computed via absorbing Markov chain and manifold ranking, and a saliency map are obtained corresponding to each image. Finally, it uses a contrast stretching function to correct the above saliency map for improving the quality of image. Experimental results demonstrate that the proposed method can more easily distinguish salient objects from background, and performs better than some methods in terms of robustness and performance.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Ye Huang
AU  - Jianlin Zhang
AU  - Yuxing Wei
PY  - 2015/04
DA  - 2015/04
TI  - Graph Based Image Saliency Detection
BT  - Proceedings of the 2nd International Conference on Civil, Materials and Environmental Sciences
PB  - Atlantis Press
SP  - 662
EP  - 666
SN  - 2352-5401
UR  - https://doi.org/10.2991/cmes-15.2015.180
DO  - 10.2991/cmes-15.2015.180
ID  - Huang2015/04
ER  -