JOURNAL ARTICLE

Salient region detection using background contrast

Abstract

In this paper, the salient region detection problem is investigated by using background contrast. Since background colors usually appear near image border, and all background colors can be mainly represented by the colors in the image boundary, the boundary-based model is established via computing the different between the intern colors and the boundary colors. As we know, the nearer the patches are close to center, the more they affect other patches. Based on this, a new distribution-based model is proposed. Because of the fact that pixels in the small neighborhood usually have the very similar color components, and computing region-based contrast can reduce the computational complexity, the superpixel algorithm is used in the pretreatment process. Finally, experimental results demonstrate that the proposed method outperforms the state-of-the-art approaches.

Keywords:
Contrast (vision) Salient Artificial intelligence Computer science Pixel Computer vision Boundary (topology) Computational complexity theory Color contrast Image (mathematics) Process (computing) Pattern recognition (psychology) Mathematics Algorithm

Metrics

3
Cited By
0.24
FWCI (Field Weighted Citation Impact)
29
Refs
0.57
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Visual Attention and Saliency Detection
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Image and Video Quality Assessment
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Image Enhancement Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
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