Feature Matching Algorithm Based on SURF and Lowes Algorithm

被引：0

作者：

Wang, Xiaoqi ^{[1
,2
]}

Cao, Weihua ^{[1
,2
]}

Yao, Chaolong ^{[1
,2
]}

Yin, Hang ^{[1
,2
]}

机构：

[1] China Univ Geosci, Sch Automat, Wuhan 430074, Peoples R China

[2] Hubei Key Lab Adv Control & Intelligent Automat C, Wuhan 430074, Peoples R China

来源：

PROCEEDINGS OF THE 39TH CHINESE CONTROL CONFERENCE | 2020年

基金：

中国国家自然科学基金;

关键词：

Median filtering; SURF; Feature matching; Lowes algorithm;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Feature extraction and matching of images is a key step in 3D reconstruction, and its accuracy directly affects the accuracy of 3D reconstruction. In this paper, aiming at the mismatch caused by the high similarity between screws, proposes a feature matching algorithm based on median filtering, Lowes algorithm and scale-invariant feature transform (SURF), called M-L-SURF algorithm. First, the median filtering is performed on the screw image to remove noise, then the SURF algorithm is used for feature extraction and matching, and finally, the Lowe's algorithm is used to filter the matching results. The results of experiments show that the M-L-SURF algorithm can achieve a 97.4% correct rate of screw image matching. The matching results obtained in this paper can be better applied to the subsequent work of 3D reconstruction.

引用

页码：5996 / 6000

页数：5

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