Graph-based Visual Saliency Model using Background Color | ||
| Journal of AI and Data Mining | ||
| مقاله 12، دوره 6، شماره 1، خرداد 2018، صفحه 145-156 اصل مقاله (2.98 M) | ||
| نوع مقاله: Original/Review Paper | ||
| شناسه دیجیتال (DOI): 10.22044/jadm.2017.911 | ||
| نویسندگان | ||
| Sh. Foolad1؛ A. Maleki* 2 | ||
| 1Department of Electrical & Computer Engineering, Semnan University, Semnan, Iran. | ||
| 2Faculty of Biomedical Engineering, Semnan University, Semnan, Iran. | ||
| چکیده | ||
| 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. | ||
| کلیدواژهها | ||
| Visual attention؛ bottom-up model؛ saliency detection؛ graph based؛ background color | ||
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آمار تعداد مشاهده مقاله: 1,456 تعداد دریافت فایل اصل مقاله: 1,553 |
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