Shahrood University of Technology Journal of AI and Data Mining 2322-5211 6 1 2018 03 01 Graph-based Visual Saliency Model using Background Color 145 156 911 10.22044/jadm.2017.911 EN Sh. Foolad Department of Electrical & Computer Engineering, Semnan University, Semnan, Iran. A. Maleki Faculty of Biomedical Engineering, Semnan University, Semnan, Iran. Journal Article 2015 07 03 Visual saliency is a cognitive psychology concept that makes some stimuli of a scene stand out relative to their neighbors and attract our attention. Computing visual saliency is a topic of recent interest. Here, we propose a graph-based method for saliency detection, which contains three stages: pre-processing, initial saliency detection and final saliency detection. The initial saliency map is obtained by putting adaptive threshold on color differences relative to the background. In final saliency detection, a graph is constructed, and the ranking technique is exploited. In the proposed method, the background is suppressed effectively, and often salient regions are selected correctly. Experimental results on the MSRA-1000 database demonstrate excellent performance and low computational complexity in comparison with the state-of-the-art methods. https://jad.shahroodut.ac.ir/article_911_77e682b5cb54b5006b09f33ec359aa36.pdf