[1]李 俊.基于中心对称特征耦合仿射度量模型的图像匹配方法[J].机械与电子,2024,42(09):18-24.
　LI Jun.Image Matching Method Based on Variance Constraint Coupled Geometric Invariance[J].Machinery & Electronics,2024,42(09):18-24.
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基于中心对称特征耦合仿射度量模型的图像匹配方法()
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《机械与电子》[ISSN:1001-2257/CN:52-1052/TH]

卷:
42
期数:
2024年09期
页码:
18-24
栏目:
研究与设计
出版日期:
2024-09-27

文章信息/Info

Title:
Image Matching Method Based on Variance Constraint Coupled Geometric Invariance
文章编号:
1001-2257 ( 2024 ) 09-0018-07
作者:
李 俊
陕西工业职业技术学院,陕西 咸阳 712000
Author(s):
LI Jun
( Shaanxi Polytechnic Institute , Xianyang 712000 , China )
关键词:
图像匹配; 中心对称特征; 仿射度量模型; 结构相似度函数; Forstner 算子
Keywords:
image matching ;  centrally symmetric features ;  affine metric model ;  structural similarity index measurement function ;  Forstner operator
分类号:
TP391
文献标志码:
A
摘要:
针对当下较多图像匹配算法利用距离度量法来实现特征匹配,没考虑图像仿射变换的影响,使得匹配结果准确率不高的问题,提出了中心对称特征耦合仿射度量模型的图像匹配算法。首先,引入 Forstner 算子,利用像素点的 GS 梯度特征提取特征点;然后,利用图像的 Haar 小波信息与中心对称像素点的灰度值,求取特征向量;接着,利用特征点之间的旋转、平移以及缩放的仿射特征,构造仿射度量模型,利用其计算出匹配的特征点对;最后,采用结构相似度( SSIM )函数,计算匹配点对的结构相似性,对匹配点对去伪求真,以求取最优匹配效果。实验结果表明,与当下匹配方法相比,所提算法不仅能更准确地实现图像匹配,而且还能够更好地适应具有仿射变换关系图像之间的匹配。
Abstract:
In response to the current problem of many image matching algorithms using distance measurement to achieve feature matching without considering the impact of image affine transformation , resulting in low accuracy of matching results , this paper proposes an image matching algorithm based on the centrosymmetric feature coupled affine measurement model.Firstly , the Forstner operator is introduced to extract feature point using the Robert gradient features of pixels ; then , using the Haar wavelet information of the image and the grayscale values of the centrosymmetric pixels , the feature vector is obtained ; next , using the affine features of rotation , translation , and scaling between feature points , an affine metric model is constructed to calculate the matched feature point pairs ; finally , the structural similarity index measurement ( SSIM ) function is used to calculate the structural similarity of matching point pairs , and to remove artifacts and truth from the matching point pairs in order to obtain the optimal matching effect.The experimental results show that compared with current matching methods , the proposed algorithm can not only achieve more accurate image matching , but also better adapt to the matching between images with affine transformation relationships.

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备注/Memo

备注/Memo:
收稿日期: 2023-10-05
基金项目:陕西省自然科学基础研究计划(青年人才项目)( 2022JQ-710 )
作者简介:李 俊 ( 1975- ),女,安徽涡阳人,硕士,副教授,研究方向为计算机应用。
更新日期/Last Update: 2024-09-24