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Saliency detection with color contrast based on boundary information and neighbors

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Abstract

Object-level saliency detection is significant in many computer vision tasks. In this paper, we propose a novel saliency detection model based on color contrast and image boundaries. The saliency of an image is defined as the contrast between the image elements (regions) and image boundaries elements (regions). We consider the saliency in two-stage procedure rather than in one stage. First of all, according to the definition of saliency, we take four boundaries of image into consideration respectively to obtain a combination coarse saliency map. Furthermore, a new energy function based on the coarse saliency map is proposed, which takes the coarse saliency map as input to yield the final full resolution saliency map. Experimental results on two public datasets demonstrate that the proposed model performs better than the state-of-the-art methods.

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Acknowledgments

This work was supported by the Key Project of Hunan Province Science and Technology Planning Project, China (2014G2012).

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Authors and Affiliations

  1. College of Information Science and Engineering, Hunan University, Changsha,  410000, China

    Min Xu & Hanling Zhang

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  1. Min Xu
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  2. Hanling Zhang
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Correspondence to Min Xu.

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Xu, M., Zhang, H. Saliency detection with color contrast based on boundary information and neighbors. Vis Comput 31, 355–364 (2015). https://doi.org/10.1007/s00371-014-0930-9

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  • DOI: https://doi.org/10.1007/s00371-014-0930-9

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