An improved RANSAC image stitching algorithm based similarity degree

Yule Ge*, Chunxiao Gao, Guodong Liu

*此作品的通讯作者

科研成果: 书/报告/会议事项章节会议稿件同行评审

2 引用 (Scopus)

摘要

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.

源语言英语
主期刊名MultiMedia Modeling - 22nd International Conference, MMM 2016, Proceedings
编辑Richang Hong, Nicu Sebe, Qi Tian, Guo-Jun Qi, Benoit Huet, Xueliang Liu
出版商Springer Verlag
185-196
页数12
ISBN(印刷版)9783319276731
DOI
出版状态已出版 - 2016
活动22nd International Conference on MultiMedia Modeling, MMM 2016 - Miami, 美国
期限: 4 1月 20166 1月 2016

出版系列

姓名Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
9517
ISSN(印刷版)0302-9743
ISSN(电子版)1611-3349

会议

会议22nd International Conference on MultiMedia Modeling, MMM 2016
国家/地区美国
Miami
时期4/01/166/01/16

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