An improved RANSAC image stitching algorithm based similarity degree

Yule Ge*, Chunxiao Gao, Guodong Liu

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Citations (Scopus)

Abstract

In terms of the deficiency in the aspects that the higher computational complexity caused by excessive iterations and the easy happened stitching dislocation caused by the difficult-to-determine parameters. In this paper, an improved RANSANC algorithm based similarity degree is proposed and is applied in image mosaic. This improved algorithm includes that sorting rough matched points by similarity degree, calculating transformation matrix, rejecting obviously wrong matched points and executing classical RANSAC algorithm. It is demonstrated by the experiments that this algorithm can effectively remove wrong matched pairs, reduce iteration times and shorten the calculation time, meanwhile ensure the accuracy of requested matrix transformation. By this method can get high quality stitching images.

Original languageEnglish
Title of host publicationMultiMedia Modeling - 22nd International Conference, MMM 2016, Proceedings
EditorsRichang Hong, Nicu Sebe, Qi Tian, Guo-Jun Qi, Benoit Huet, Xueliang Liu
PublisherSpringer Verlag
Pages185-196
Number of pages12
ISBN (Print)9783319276731
DOIs
Publication statusPublished - 2016
Event22nd International Conference on MultiMedia Modeling, MMM 2016 - Miami, United States
Duration: 4 Jan 20166 Jan 2016

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9517
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference22nd International Conference on MultiMedia Modeling, MMM 2016
Country/TerritoryUnited States
CityMiami
Period4/01/166/01/16

Keywords

  • Image stitching
  • RANSAC
  • Similarity degree

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