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A Salient Object Detection Algorithm Based on Hierarchical Cognitive Mechanism

Received: 17 July 2019 Accepted: 20 November 2019 The key of salient object detection is to extract the most attractive area in the scene. This paper fully explores the hierarchical cognitive mechanism of visual information, combines color contrast and depth contrast, and puts forward a salient object detection algorithm for the RGB-D image. Three saliency maps were prepared, namely, initial saliency map, middle saliency map and advanced saliency map. The three maps were then fused into a final saliency map. The proposed method was compared with six popular salient object detection methods on three RGB-D image datasets. The comparison shows that our algorithm achieved the best results in accuracy, recall rate and F-value. The research findings shed important new light on salient object detection in RGB-D images.