Saliency Detection Based on Color and Gradient Boolean Features
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Graphical Abstract
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Abstract
There exist non-uniform areas and low saliency score problems in image saliency detection.By analyzing the model of Boolean map based saliency,this paper proposes the Boolean maps of color and gradient based saliency model (BMCG).According to Gestalt principle of figure-ground segregation,the Boolean maps with the topological structure are generated via the random threshold color channels and gradient channel.Furthermore,these Boolean maps are refined into the attention maps of visual and are linearly combined to generate the saliency map via post-process.The simulation results show that BMCG algorithm is better than BMS algorithm,improving the recall rate of 2.12% and precision rate of 4.56%.
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