LIU Shuo, DING Wenrui, LI Hongguang, LI Yingting. A Novel Salient Region Detection Method Based on Hierarchical Spatial Information[J]. Chinese Journal of Electronics, 2017, 26(2): 319-324. doi: 10.1049/cje.2017.01.027
Citation: LIU Shuo, DING Wenrui, LI Hongguang, LI Yingting. A Novel Salient Region Detection Method Based on Hierarchical Spatial Information[J]. Chinese Journal of Electronics, 2017, 26(2): 319-324. doi: 10.1049/cje.2017.01.027

A Novel Salient Region Detection Method Based on Hierarchical Spatial Information

doi: 10.1049/cje.2017.01.027
Funds:  This work is supported by the National Natural Science Foundation of China (No.61450008).
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  • Corresponding author: DING Wenrui (corresponding author) received the B.S. degree in computer science from Beihang University in 1994. From 1994 to now, she was a lecturer of Beihang University where she is a now a professor, deputy general designer of UAV system. Her research interests include data link, computer vision, and artificial intelligence. (Email:ding@buaa.edu.cn)
  • Received Date: 2014-11-26
  • Rev Recd Date: 2015-05-05
  • Publish Date: 2017-03-10
  • Different patterns in one object will cause unequal saliency degree which makes it hard to highlight the object region uniformly. We propose a salient region detection method which mainly includes image abstraction, saliency calculation and integration. Under the detection framework, the hierarchical spatial information is introduced to improve the performance. The image abstraction with "pixel level" spatial information is applied to capture some meaningful elements. The local contrast is calculated with the "element level" spatial information. The "object level" spatial information is represented as compactness and background possibility, which further help to better pop out the object region and suppress the background. The results show that our method has a good performance even though the object consists of complex patterns.
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