SIA OpenIR  > 光电信息技术研究室
多模态鲁棒的局部特征描述符
Alternative TitleMultimodality robust local feature descriptors
赵春阳; 赵怀慈
Department光电信息技术研究室
Source Publication光学精密工程
ISSN1004-924X
2015
Volume23Issue:5Pages:1474-1483
Indexed ByEI ; CSCD
EI Accession number20152600979068
CSCD IDCSCD:5431773
Contribution Rank1
Funding Organization国家973重点基础研究发展计划资助项目 ; 中国科学院光电信息处理重点实验室开放基金资助项目(No.OEIP-O-201203)
Keyword图像配准 多模态配准 多模态鲁棒特征 相位一致性 局部方向 归一化相关
Abstract针对基于灰度的局部特征匹配方法对图像对比度变化敏感,导致在多模态图像配准应用中性能大幅下降的问题,提出了一种多模态鲁棒的局部特征描述符和匹配方法。首先,基于对比度变化不敏感的相位一致性和局部方向信息,提出一种多模态鲁棒的角点和线段特征提取方法,在对比度差异显著的多模态图像之间提取较多的共性角点和线段特征;然后,以角点为中心选择48个均匀分布的圆形特征子区域,利用角点与特征子区域内线段的距离和线段长度信息,构建96维的特征向量;最后,将归一化相关函数作为匹配测度函数进行特征匹配,并采用基于位置约束的随机抽样一致(RANSAC)方法进行匹配提纯。实验表明,本文提出的多模态匹配方法匹配正确率和重复率...
Other AbstractThe intensity-based local feature matching methods are sensitive to image contrast variations, so the performance declines significantly when they are applied in multimodal image registration. To solve the above problem, a multimodality robust local feature descriptor was proposed and the corresponding feature matching method was developed. Firstly, an extraction method for the multimodality robust corner and line segment was proposed based on the phase congruency and local direction information insensitive to contrast variants. Compared with intensity based method, more equivalent corners and line segments were extracted between multimodal images with more contrast differences. Then, the feature region containing of 48circular sub-regions was selected by using the corner for a center and the 96dimensional feature vectors were generated by using the distance values of corners and the length values of line segments located in feature subregions. Finally, the feature matching method based on normalized correlation function was proposed and the location constraint-based RANdom SAmple Consensus(RANSAC)algorithm was used to remove false matching point pairs. The experimental results indicate that the precision and repeatability on multimodal image matching of the proposed method reach 80%and 13%respectively. As compared with the other intensity-based image matching methods, the precision and repeatability of proposed method are 2-4times and 4-7times respectively those of Symmetric-Scale Invariable Feature Transformation(S-SIFT)and Multimodal-Speeded-up Robust Features(MM-SURF).It concludes that the proposed method outperforms many state-of-the-art methods significantly.
Language中文
Citation statistics
Document Type期刊论文
Identifierhttp://ir.sia.cn/handle/173321/16179
Collection光电信息技术研究室
Affiliation1.中国科学院沈阳自动化研究所
2.中国科学院光电信息处理重点实验室
3.中国科学院大学
Recommended Citation
GB/T 7714
赵春阳,赵怀慈. 多模态鲁棒的局部特征描述符[J]. 光学精密工程,2015,23(5):1474-1483.
APA 赵春阳,&赵怀慈.(2015).多模态鲁棒的局部特征描述符.光学精密工程,23(5),1474-1483.
MLA 赵春阳,et al."多模态鲁棒的局部特征描述符".光学精密工程 23.5(2015):1474-1483.
Files in This Item: Download All
File Name/Size DocType Version Access License
多模态鲁棒的局部特征描述符.pdf(905KB)期刊论文出版稿开放获取ODC PDDLView Download
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[赵春阳]'s Articles
[赵怀慈]'s Articles
Baidu academic
Similar articles in Baidu academic
[赵春阳]'s Articles
[赵怀慈]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[赵春阳]'s Articles
[赵怀慈]'s Articles
Terms of Use
No data!
Social Bookmark/Share
File name: 多模态鲁棒的局部特征描述符.pdf
Format: Adobe PDF
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.