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A two step salient objects extraction framework based on image segmentation and saliency detection

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Abstract

Salient objects extraction from a still image is a very hot topic, as it owns a lot of useful applications (e.g., image compression, content-based image retrieval, digital watermarking). In this paper, targeted to improve the performance of the extraction approach, we propose a two step salient objects extraction framework based on image segmentation and saliency detection (TIS). Specially, during the first step, the image is segmented into several regions using image segmentation algorithm and the saliency map for the whole image is detected with saliency detection algorithm. In the second step, for each region, some features are extracted for the SVM algorithm to classify the region as a background region or a salient region twice. Experimental results show that our proposed framework can extract the salient objects more precisely and can achieve a good extraction results, compared with previous salient objects extraction methods.

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Acknowledgements

This work was supported by “the Fundamental Research Funds for the Central Universities” (2012JBM032). Tao Han’s research was supported by Hubei Provincial Science and Technology Department (Grant No.: 2011BFA004).

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Authors and Affiliations

  1. School of Computer and Information Technology, Beijing Jiaotong University, Beijing, China

    Qiang Liu, Yantao Sun, Zhong Chu & Bingwen Shen

  2. Department of Electronics and Information Engineering, Huazhong University of Science and Technology, Huazhong, China

    Tao Han

Authors
  1. Qiang Liu
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  2. Tao Han
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  3. Yantao Sun
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  4. Zhong Chu
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  5. Bingwen Shen
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Correspondence to Tao Han.

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Liu, Q., Han, T., Sun, Y. et al. A two step salient objects extraction framework based on image segmentation and saliency detection. Multimed Tools Appl 67, 231–247 (2013). https://doi.org/10.1007/s11042-012-1077-1

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