基于结构标签学习的显著性目标检测

程藜; 吴谨; 朱磊

doi:10.3788/YJYXS20163107.0726

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基于结构标签学习的显著性目标检测

显示与图像 | 更新时间：2020-07-07

- 基于结构标签学习的显著性目标检测
- Salient object detection based on structured labels learning
- 液晶与显示 2016年31卷第7期页码：726-732
- 作者机构：
  
  武汉科技大学信息科学与工程学院, 湖北武汉 430081
- 作者简介：
  
  程藜(1990-),女,湖北武汉人,硕士,主要从事图像处理与显著目标检测方面的研究。E-mail:342362994@qq.com
  [ "朱磊(1982-),男,湖北武汉人,博士,讲师,主要从事图像处理与机器学习方面的研究。E-mail:179901529@qq.com" ]
- 基金信息：
  
  国家自然科学基金青年项目(No.61502358);Supported by National Natural Science Foundation of China(No.61502358)
- DOI：10.3788/YJYXS20163107.0726
  中图分类号： TP391.4;TN911.73
- 收稿日期：2016-01-25，
  
  录用日期：2016-2-29，
  
  纸质出版日期：2016-07
- 稿件说明：
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程藜, 吴谨, 朱磊. 基于结构标签学习的显著性目标检测[J]. 液晶与显示, 2016,31(7):726-732.

Li CHENG, Jin WU, Lei ZHU. Salient object detection based on structured labels learning[J]. Chinese journal of liquid crystals and displays, 2016, 31(7): 726-732.
程藜, 吴谨, 朱磊. 基于结构标签学习的显著性目标检测[J]. 液晶与显示, 2016,31(7):726-732. DOI： 10.3788/YJYXS20163107.0726.

Li CHENG, Jin WU, Lei ZHU. Salient object detection based on structured labels learning[J]. Chinese journal of liquid crystals and displays, 2016, 31(7): 726-732. DOI： 10.3788/YJYXS20163107.0726.

摘要

提出了一种基于结构标签学习的显著性目标检测算法，将结构化学习方法应用到显著性目标检测中。首先从含有标记的图像中随机采集固定大小的矩形区域，并记录其结构标签；然后使用含结构标签的区域特征构建决策树集合；最后采用监督学习的方法对图像进行优化预测，得到最终的显著图。实验结果表明，本文方法能较准确地检测出图像库中图像的显著性区域，在数据库MSRA5000和BSD300的AUC值分别为0.891 8、0.705 2，说明本文方法具有较好的显著性检测效果。

Abstract

This paper proposes a salient object detection method based on structured labels learning

applying a structured learning method to salient object detection. Firstly

we get a fixed rectangular region randomly from the local image which includes the labeling

and record the corresponding structured labels. Then

a collection of decision trees is built by using the regional features which includes the structured labels.Finally

the final saliency map is captured by using the supervised learning approach. Experiments show that our method can detect the salient objects accurately

and the AUC scores are 0.891 8 and 0.705 2 on the MSRA5000 and BSD300 datasets

the result shows that our method can achieve good effect in salient object detection.

关键词

Keywords

references

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