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山东大学学报(工学版) ›› 2017, Vol. 47 ›› Issue (3): 27-33.doi: 10.6040/j.issn.1672-3961.0.2016.340

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基于视觉中心转移的视觉显著性检测方法

胡金戈,唐雁   

  1. 西南大学计算机与信息科学学院, 重庆 400715
  • 收稿日期:2016-08-27 出版日期:2017-06-20 发布日期:2016-08-27
  • 通讯作者: 唐雁(1965— ),女,重庆人,教授,硕士生导师,主要研究方向为人工智能,web应用与数据挖掘等.E-mail:ytang@swu.edu.cn E-mail:445441787@qq.com
  • 作者简介:胡金戈(1991— ),女,重庆人,硕士研究生,主要研究方向为视觉显著性检测.E-mail:445441787@qq.com
  • 基金资助:
    中央高校基本科研业务费专项资金资助项目(XDJK2015C110)

Visual saliency detection based on visual center shift

HU Jinge, TANG Yan   

  1. College of Computer and Information Science, Southwest University, Chongqing 400715, China
  • Received:2016-08-27 Online:2017-06-20 Published:2016-08-27

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摘要： 针对现有许多检测方法提取出的显著性区域不够清晰的问题,提出一种基于视觉中心偏移的视觉显著性检测方法,在对图像进行预分割的基础上,结合图像的颜色对比特征、颜色分布特征和位置特征,提取出图像显著性区域,利用视觉中心转移模拟人类视野系统的视野转移过程,对图像进行多尺度分析,融合不同尺度显著图得到最终显著图。试验结果表明,本方法较现有显著性检测方法在视觉效果和查准率召回率有明显提高,ROC曲线下的面积可达0.952。

关键词: 多尺度分析, 图像分割, 显著图, 中心转移, 视觉显著性

Abstract: Many existing detection methods could not extract saliency regions clearly. A novel saliency detection method based on visual center offsetting was proposed. On the basis of images' pre-segmentation, combining with color contrast features, color distribution features and location features, saliency region of an image was extracted. The center offsetting was used to simulate the vision transfer process of human, after multi-scale analysis, by fusing saliency maps at different scales. The final saliency map was computed. The results showed that the performance of the proposed method was better on visual effect and the precision recall rate than existing methods, the area under ROC curve was 0.952.

Key words: saliency map, multi-scale, image segmentation, visual saliency, center shift

中图分类号: 

  • TP391
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