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Region saliency detection via multi-feature on absorbing Markov chain

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Abstract

Saliency region detection plays an important role in image pre-processing, and uniformly emphasizing saliency region is still an intractable problem in computer vision. In this paper, we present a data-driven salient region detection method via multi-feature (included contrast, spatial relationship and background prior, etc.) on absorbing Markov chain, which uses super pixel to extract salient regions, and each super-pixel represents a node. In detail, we first construct function to calculate absorption probability of each node on absorbing Markov chain. Second we utilize image contrast and space relation to model the prior salient map which is provided to foreground salient nodes and then calculate the saliency of nodes based on absorption probability. Third, we also exploit background prior to supply the absorbing nodes and compute the saliency of nodes. Finally, we fuse both the saliency of nodes by cosine similarity measurement method and acquire the ultimate saliency map. Our approach is simple and efficient and highlights not only a single object but also multiple objects consistently. We test the proposed method on MSRA-B, iCoSeg and SED databases. Experimental results illustrate that the proposed approach presents better robustness and efficiency against the eleven state-of-the art algorithms.

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Acknowledgments

The authors thank the anonymous reviewers for helping to review this paper. This work was supported by Major State Basic Research Development Program (973 Program Grant no. 2013CB328903), special fund of 2011 Internet of Things development of Ministry of Industry and Information Technology (2011BAJ03B13-2) and Chongqing Key Project of Science and Technology of China (cstc2012gg-yyjs40008).

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Authors and Affiliations

  1. College of Automation, Chongqing University, Chongqing, 400044, China

    Wenjie Zhang & Weiren Shi

  2. Key Laboratory of Dependable Service Computing in Cyber Physical Society, MOE, Chongqing, 400044, China

    Qingyu Xiong

  3. School of Software Engineering, Chongqing University, Chongqing, 400044, China

    Qingyu Xiong

  4. College of Information Engineering, Yangzhou University, Yangzhou, China

    Shuhan Chen

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  1. Wenjie Zhang
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  2. Qingyu Xiong
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  3. Weiren Shi
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  4. Shuhan Chen
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Correspondence to Qingyu Xiong.

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Zhang, W., Xiong, Q., Shi, W. et al. Region saliency detection via multi-feature on absorbing Markov chain. Vis Comput 32, 275–287 (2016). https://doi.org/10.1007/s00371-015-1065-3

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