A novel CBIR system with WLLTSA and ULRGA
Feng, Lin; Liu, Shenglan; Xiao, Yao; Hong, Qiao; Wu, Bin; Feng, L
2015
发表期刊NEUROCOMPUTING
卷号147期号:0页码:509-522
摘要At present, relevance feedback (RF) has been widely applied in content-based image retrieval (CBIR) system. Local Regression and Global Alignment (LRGA) is a novel ranking algorithm used in CBIR system which utilizes RE technique. However, there are some problems in LRGA: (1) for handling the problem of out-of-sample, dimension reduction is used after RF, but it is time-consuming; (2) feature space of images is often assumed to be linear. While, classical manifold learning methods are sensitive to the Gaussian bandwidth parameter of Laplacian matrix and cannot be combined with RF either. To address problems above, this paper proposes a novel CBIR system. Firstly, we calculate the local curvature parameter of manifold utilizing the angle information in subspace to avoid local high curvature problem and then we propose a Warp Linear Local Tangent Space Alignment (WLLTSA) algorithm; furthermore, we propose a U-Local Regression and Global Alignment (ULRGA) ranking algorithm to rank low-dimensional image features. Curvature parameter is used in both WLLTSA and ULRGA to enhance robustness. A large amount of experimental results demonstrate the efficiency of our CBIR system. (C) 2014 Elsevier B.V. All rights reserved.
关键词Dimensionality Reduction Local Curvature Tangent Space Cbir Rf
学科领域Computer Science
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/12587
专题复杂系统管理与控制国家重点实验室_机器人理论与应用
通讯作者Feng, L
推荐引用方式
GB/T 7714
Feng, Lin,Liu, Shenglan,Xiao, Yao,et al. A novel CBIR system with WLLTSA and ULRGA[J]. NEUROCOMPUTING,2015,147(0):509-522.
APA Feng, Lin,Liu, Shenglan,Xiao, Yao,Hong, Qiao,Wu, Bin,&Feng, L.(2015).A novel CBIR system with WLLTSA and ULRGA.NEUROCOMPUTING,147(0),509-522.
MLA Feng, Lin,et al."A novel CBIR system with WLLTSA and ULRGA".NEUROCOMPUTING 147.0(2015):509-522.
条目包含的文件
条目无相关文件。
个性服务
推荐该条目
保存到收藏夹
查看访问统计
导出为Endnote文件
谷歌学术
谷歌学术中相似的文章
[Feng, Lin]的文章
[Liu, Shenglan]的文章
[Xiao, Yao]的文章
百度学术
百度学术中相似的文章
[Feng, Lin]的文章
[Liu, Shenglan]的文章
[Xiao, Yao]的文章
必应学术
必应学术中相似的文章
[Feng, Lin]的文章
[Liu, Shenglan]的文章
[Xiao, Yao]的文章
相关权益政策
暂无数据
收藏/分享
所有评论 (0)
暂无评论
 

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。