JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE) ›› 2015, Vol. 45 ›› Issue (6): 1-6.doi: 10.6040/j.issn.1672-3961.0.2015.176

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An image saliency object detection algorithm based on information diffusion

REN Yongfeng1,2, ZHOU Jingbo1   

  1. 1. Faculty of Computer and Software Engineering, Huaiyin Institute of Technology, Huai'an 223003, Jiangsu, China;
    2. College of Computer and Information, Hohai University, Nanjing 211100, Jiangsu, China
  • Received:2015-06-08 Revised:2015-11-02 Online:2015-12-20 Published:2015-06-08

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Abstract: In order to better extract salient regions in images, we proposed an image salient region detection algorithm based on information diffusion mechanism. The proposed algorithm was divided into three steps. First, we segmented an input image into superpixels which were represented as the nodes in a graph. The node with high frequency was generated by the characteristics of the salient regions. Then, according to high-frequency nodes, convex hull computation was used to generate the saliency seeds of the salient object area. Finally, based on the seeds obtained by convex hull computation, the second-order Gaussian-Markov random fields were used to diffuse the information from saliency seeds to others, thereby forming the saliency region for a given image. The experimental results showed that the quadratic programming solution exploited to compute the weights between the nodes can effectively avoid threshold selection and enhance robustness accordingly. In addition, the proposed method performed better than the other state-of-the-art methods.

Key words: convex hull computation, information diffusion, saliency detection, Gaussian-Markov random fields, high frequency node

CLC Number: 

  • TP301.6
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