An Improved Graph-based Manifold Ranking for Salient Object Detection

Lü Jian-yong; Tang Zhen-min

doi:10.11999/JEIT150619

Volume 37 Issue 11

Nov. 2015

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Article Navigation > Journal of Electronics & Information Technology > 2015 > 37(11): 2555-2563

Liu Changshu, Ma Xin, Li Wenyuan, Zhang Yuzhong . A FAST ALGORITHM FOR REAL-TIME MPEG-2AUDIO CODING AND DECODING[J]. Journal of Electronics & Information Technology, 2001, 23(2): 147-153.

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Lü Jian-yong, Tang Zhen-min. An Improved Graph-based Manifold Ranking for Salient Object Detection[J]. Journal of Electronics & Information Technology, 2015, 37(11): 2555-2563. doi: 10.11999/JEIT150619

Liu Changshu, Ma Xin, Li Wenyuan, Zhang Yuzhong . A FAST ALGORITHM FOR REAL-TIME MPEG-2AUDIO CODING AND DECODING[J]. Journal of Electronics & Information Technology, 2001, 23(2): 147-153.

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An Improved Graph-based Manifold Ranking for Salient Object Detection

doi: 10.11999/JEIT150619

Lü Jian-yong¹,
Tang Zhen-min¹

Funds:

The National Natural Science Foundation of China (61473154)

Received Date: 2015-05-25
Rev Recd Date: 2015-08-13
Publish Date: 2015-11-19

Abstract

Abstract

To overcome the shortage that the spatial connectivity of every node is modeled only via the k-regular graph and the idealistic prior background assumption is used in existing salient object detection method based on graph-based manifold ranking, an improved method is proposed to increase the precision while preserving the high recall. When constructing the graph model, the affinity propagation clustering is utilized to aggregate the superpixels (nodes) to different color clusters adaptively. Then, based on the traditional k-regular graph, the nodes belonging to the same cluster and located in the same spatial connected region are connected with edges. According to the boundary connectivity, the superpixels along the image boundaries are assigned with different background weights. Then, the real background seeds are selected by graph cuts method. Finally, the classical manifold ranking method is employed to compute saliency. The experimental comparison results of 4 quantitative evaluation indicators between the proposed and 7 state-of-the-art methods on MSRA-1000 and complex SOD datasets demonstrate the effectiveness and superiority of the proposed improved method.
- Salient object detection,
- Improved graph model,
- Manifold ranking,
- Boundary connectivity,
- Connected region

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References(29)

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