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2018 | OriginalPaper | Chapter

Mismatching Elimination Algorithm in SIFT Based on Function Fitting

Authors : Xiaoni Zhong, Yunhong Li, Jie Ren

Published in: Advances in Brain Inspired Cognitive Systems

Publisher: Springer International Publishing

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Abstract

In order to solve the problems such as time consuming and mismatching in the experiment of eliminating SIFT mismatch points in RANSAC algorithm, proposed Mismatching Elimination Algorithm in SIFT Based on Function Fitting; Firstly, we use SIFT algorithm to direct the matching of the image and the matching image, using iterative least squares fitting method to construct function model for the key points of matched Image; secondly, fit the function model with the key points of matching image features; Finally, the errors of the two algorithms are calculated, when the error is greater than the set threshold, verify that the point is a mismatch point, and it is eliminated. The experimental results show that using Mismatching Elimination Algorithm in SIFT Based on Function Fitting than RANSAC algorithm in time to save the 2 s on average, the correct matching rate is increased by 11.75%, and more correct matching points can be reserved.

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Metadata
Title
Mismatching Elimination Algorithm in SIFT Based on Function Fitting
Authors
Xiaoni Zhong
Yunhong Li
Jie Ren
Copyright Year
2018
Book
Advances in Brain Inspired Cognitive Systems

Print ISBN: 978-3-030-00562-7

Electronic ISBN: 978-3-030-00563-4

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-3-030-00563-4_23

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