An improvement to the SIFT descriptor for image representation and matching

被引：57

作者：

Liao, Kaiyang ^{[1
]}

Liu, Guizhong ^{[1
]}

Hui, Youshi ^{[1
]}

机构：

[1] Xi An Jiao Tong Univ, Sch Elect & Informat Engn, Xian 710049, Peoples R China

来源：

PATTERN RECOGNITION LETTERS | 2013年 / 34卷 / 11期

基金：

国家高技术研究发展计划(863计划);

关键词：

Local descriptor; SIFT; Point matching; INVARIANT; COLOR; SCALE; CLASSIFICATION; FEATURES;

D O I：

10.1016/j.patrec.2013.03.021

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Constructing proper descriptors for interest points in images is a critical aspect for local features related tasks in computer vision and pattern recognition. Although the SIFT descriptor has been proven to perform better than the other existing local descriptors, it does not gain sufficient distinctiveness and robustness in image match especially in the case of affine and mirror transformations, in which many mismatches could occur. This paper presents an improvement to the SIFT descriptor for image matching and retrieval. The framework of the proposed descriptor consists of the following steps: normalizing elliptical neighboring region, transforming to affine scale-space, improving the SIFT descriptor with polar histogram orientation bin, as well as integrating the mirror reflection invariant. A comparative evaluation of different descriptors is carried out showing that the present approach provides better results than the existing methods. (C) 2013 Elsevier B.V. All rights reserved.

引用

页码：1211 / 1220

页数：10

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