基于Local特征和Regional特征的图像显著性检测

郭迎春; 袁浩杰; 吴鹏

doi:10.3724/SP.J.1004.2013.01214

基于Local特征和Regional特征的图像显著性检测

doi: 10.3724/SP.J.1004.2013.01214

1.
河北工业大学计算机科学与软件学院天津 300401

基金项目:

国家自然科学基金(60302018);河北省科技支撑计划项目(11213518D)资助

详细信息

作者简介:
袁浩杰河北工业大学计算机科学与软件学院硕士研究生. 主要研究方向为数字图像处理, 图像检测.E-mail: yuanhaojie9@163.com

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出版历程
- 收稿日期: 2011-07-25
- 修回日期: 2012-07-25
- 刊出日期: 2013-08-20

Image Saliency Detection Based on Local and Regional Features

1.
School of Computer Science and Engineering, Hebei University of Technology, Tianjin 300401

Funds:

Supported by National Natural Science Foundation of China (60302018) and Hebei Science and Technology Support Program (11213518D)

摘要

摘要: 提出了一种基于颜色空间的Local特征和Regional特征的自然图像显著性检测方法. 该方法将图像分成8×8的子块, 计算多个尺度下每一个子块的Local特征和Regional特征, 并将其加权组合来确定子块的显著程度, 从而得到整个图像的显著特征. 此外, 通过计算4个颜色通道上的色度对比度, 获得显著物体的边缘. 将图像的显著特征与显著物体的边缘综合后得到图像中的显著目标. 实验结果显示, 本文提出的方法能够快速、清晰而准确地提取出图像中的显著性目标.
- 显著性检测 /
- Local特征 /
- Regional特征 /
- 多尺度
Abstract: This paper proposes a model of salient region detection based on local and regional features in color space. Firstly, the image is divided into 8×8 sub-blocks, in each sub-block, then the multi-scale local and regional features are calculated and combined by weighted summation as the sub-block's salient value; secondly, the salient edge is calculated by the color contrast of the four color channels; finally, the salient map can be extracted by combining the salient features and salient edge together. The experiment results show that our model can extract salient objects in images fast and exactly.
- Saliency detection /
- local feature /
- regional feature /
- multi-scale

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参考文献(25)

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