计算机应用与软件2017，Vol.34Issue(8)：185-190,196,7.DOI:10.3969/j.issn.1000-386x.2017.08.033
基于局部近邻图的特征描述与特征匹配算法研究
RESEARCH OF FEATURE DESCRIPTION AND FEATURE MATCHING ALGORITHM BASED ON LOCAL NEIGHBORHOOD GRAPH
摘要
Abstract
Feature description and feature matching are important parts in the field of computer vision.In recent years, many feature description algorithms have been proposed to achieve reliable and robust performance in image matching, such as SIFT, SURF, DAISY and BRIEF.However, their descriptors usually fail when the images have undergone large viewpoint changes such as translation, rotation and scaling.To solve this problem, on the basis of local neighborhood graph model, a novel feature description and similarity measure method (referred to as LNFM algorithm) is proposed.The proposed descriptor and similarity can be well applied to a variety of popular image matching algorithms.The experimental results show that: in the process of feature matching, the proposed algorithm can detect reliable matching relationship, and the performance is relatively superior.关键词
特征描述/局部近邻图/特征匹配/相似性度量Key words
Feature description/Local neighborhood graph/Feature matching/Similarity measure分类
信息技术与安全科学引用本文复制引用
谢宜婷,王爱平,邹海..基于局部近邻图的特征描述与特征匹配算法研究[J].计算机应用与软件,2017,34(8):185-190,196,7.基金项目
国家自然科学基金项目(61573022). （61573022）
