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Image saliency detection using Gabor texture cues

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Abstract

Image saliency analysis plays an important role in various applications such as object detection, image compression, and image retrieval. Traditional methods for saliency detection ignore texture cues. In this paper, we propose a novel method that combines color and texture cues to robustly detect image saliency. Superpixel segmentation and the mean-shift algorithm are adopted to segment an original image into small regions. Then, based on the responses of a Gabor filter, color and texture features are extracted to produce color and texture sub-saliency maps. Finally, the color and texture sub-saliency maps are combined in a nonlinear manner to obtain the final saliency map for detecting salient objects in the image. Experimental results show that the proposed method outperforms other state-of-the-art algorithms for images with complex textures.

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Acknowledgment

The authors thank Fangli Ying, Xiao-Long Xiao and Xing-jian Lu for their reading the paper carefully and the useful suggestions in the saliency detection. This work is supported by the Nature Science Foundation of China (Grant No.61370174, Grant No.61572316, Grant No.61300133, and Grant No. 61202154), National High-tech R & D Program of China (863 Program) (Grant No. 2015AA011604), Shanghai Pujiang Program (No.13PJ1404500), the Science and Technology Commission of ShanghaiMunicipality Program (No. 13511505000), and the Open Project Program of the State Key Lab of CAD and CG (Grant No. A1401), Zhejiang University.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, East China University of Science and Technology, Shanghai, 200237, China

    Zhi-hua Chen, Yi Liu, Jian-ning Liang, Jing Zhang & Yu-bo Yuan

  2. Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China

    Bin Sheng

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  1. Zhi-hua Chen
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  2. Yi Liu
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  3. Bin Sheng
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  4. Jian-ning Liang
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  5. Jing Zhang
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  6. Yu-bo Yuan
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Correspondence to Bin Sheng.

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Chen, Zh., Liu, Y., Sheng, B. et al. Image saliency detection using Gabor texture cues. Multimed Tools Appl 75, 16943–16958 (2016). https://doi.org/10.1007/s11042-015-2965-y

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  • DOI: https://doi.org/10.1007/s11042-015-2965-y

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