基于图像单元对比度与统计特性的显著性检测

唐勇; 杨林; 段亮亮

doi:10.3724/SP.J.1004.2013.01632

基于图像单元对比度与统计特性的显著性检测

doi: 10.3724/SP.J.1004.2013.01632

唐勇^1,2,
杨林^1,2,
段亮亮¹

1.
燕山大学信息科学与工程学院秦皇岛 066004;
2.
河北省计算机虚拟技术与系统集成重点实验室秦皇岛 066004

基金项目:

国家自然科学基金 (60970073),河北省自然科学基金 (F2012203084)资助

详细信息

作者简介:
唐勇燕山大学信息科学与工程学院教授.2005年获得燕山大学工学博士学位.主要研究方向为虚拟现实技术及其应用.E-mail:tangyong@ysu.edu.cn

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- 被引次数: 0
出版历程
- 收稿日期: 2012-11-12
- 修回日期: 2013-03-27
- 刊出日期: 2013-10-20

Image Cell Based Saliency Detection via Color Contrast and Distribution

1.
College of Information Science and Engineering, Yanshan University, Qinhuangdao 066004;
2.
Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province, Qinhuangdao 066004

Funds:

Supported by National Natural Science Foundation of China (60970073) and Natural Science Foundation of Hebei Province (F2012203084)

摘要

摘要: 根据视觉注意机制, 提出一种基于图像单元对比度与空间统计特性的可靠显著性区域检测方法. 通过自适应的图像分割构造图像单元结构, 以图像单元为基础, 分别利用颜色对比度和空间统计特性两种模型进行显著性区域检测, 最后, 将两种模型的检测结果通过高斯模型进行结合, 得到最终的显著性区域检测的结果. 实验表明, 该检测方法与现有的方法比较, 具有更好的精度和召回率, 能明显抑制复杂纹理和噪声, 去除复杂背景的影响.
- 显著性区域检测 /
- 自适应图像分割 /
- 颜色对比度 /
- 空间统计特性
Abstract: According to biological visual attention mechanism, a salient region detection method is proposed in this paper, which is based on image cell contrast and space statistical characteristics. By constructing image cell structure with an adaptive image segmentation, based on image cell, it makes a salient region detection using both the color contrast model and space statistical characteristics model. In the end, two models' detection results combine by Gaussian model to get the final salient region detection results. Experiments show that this detection method has a higher precision and recall rate, which can not only resist the complex texture and the noise but also remove the influence of the complex background.
- Salient region detection /
- adaptive image segmentation /
- color contrast /
- space statistical characteristics

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参考文献(20)

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