Document Type: Research/Original/Regular Article

Authors

• Sh. Foolad ¹
• A. Maleki ²

¹ Department of Electrical & Computer Engineering, Semnan University, Semnan, Iran.

² Faculty of Biomedical Engineering, Semnan University, Semnan, Iran.

Abstract

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.

Keywords

• Visual attention
• bottom-up model
• saliency detection
• graph based
• background color

Main Subjects

• H.3.11. Vision and Scene Understanding