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Exploiting contrast cues for salient region detection

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Abstract

Visual saliency detection is an important cue used in human visual system, which can offer efficient solutions for both biological and artificial vision systems. Although there are many saliency detection models that can achieve good results on public datasets, the accuracy and reliability of salient object detection models still remains a challenge. For this reason, a novel effective salient region detection model is presented in this paper. Based on the principle that a combination of global statistics and surrounding contrast saliency operators can yield even better results than just using either alone, we use a histogram-based contrast method to calculate the global saliency values in an opponent color space. At the same time, we partition the input image into a set of regions, and the regional saliency is detected by considering the color isolation with spatial information and textural distinctness simultaneously. The final saliency is obtained based on a weighted fusion of the two saliency results. The experimental results from three widely used databases validate the efficacy of the proposed method in comparison with fourteen state-of-the-art existing methods.

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Authors and Affiliations

  1. School of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing, China

    Jie Niu & Xiongzhu Bu

  2. School of Electrical and Electronic Engineering, Changzhou College of Information Technology, Changzhou, China

    Jie Niu

  3. School of Automation, Southeast University, Nanjing, China

    Kun Qian

Authors
  1. Jie Niu
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  2. Xiongzhu Bu
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  3. Kun Qian
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Correspondence to Xiongzhu Bu.

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Niu, J., Bu, X. & Qian, K. Exploiting contrast cues for salient region detection. Multimed Tools Appl 76, 10427–10441 (2017). https://doi.org/10.1007/s11042-016-3430-2

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  • DOI: https://doi.org/10.1007/s11042-016-3430-2

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