JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE) ›› 2017, Vol. 47 ›› Issue (3): 56-62.doi: 10.6040/j.issn.1672-3961.0.2016.305

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An image saliency object detection algorithm based on adaptive manifold similarity

REN Yongfeng, DONG Xueyu   

  1. Electrical Power Simulation and Control Engineering Center, Nanjing Institute of Technology, Nanjing 210013, Jiangsu, China
  • Received:2016-07-22 Online:2017-06-20 Published:2016-07-22

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Abstract: In order to improve the adaptability and precision in extracting salient regions in images, an image salient region detection algorithm was proposed based on adaptive manifold similarity. An input image was segmented into super-pixels which were represented as the nodes in a graph. The node with high frequency was generated by the characteristics of the salient regions. Convex hull computation was used to generate the saliency seeds of the salient object area according to high-frequency nodes. The proposed algorithm was used to complete information reconstruction of the current image by adaptively assessing the salient weights on the edges between the nodes. In addition, based on local characteristics information reconstruction, the proposed algorithm utilized similarity extraction function to self-adaptively obtain the similarity characteristics and manifold structures in order to spread salient characteristics information. The experimental results showed that the quadratic programming solution exploited to compute the weights between the nodes could effectively avoid threshold selection and enhance robustness accordingly, and the proposed method performed better than the other state-of-the-art methods.

Key words: saliency detection, manifold similarity, convex hull computation, spread salient characteristics, adaptive

CLC Number: 

  • TP301.6
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