CONFERENCE PROCEEDINGS
Advanced Search
Home > Proceedings > Volume 11430 > Article
Paper
14 February 2020 Turnover and shape filter based feature matching for image stitching
Shuang Song, Xinguo He, Lin He
Author Affiliations +
Proceedings Volume 11430, MIPPR 2019: Pattern Recognition and Computer Vision; 114301E (2020) https://doi.org/10.1117/12.2539406
Event: Eleventh International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2019), 2019, Wuhan, China
Abstract
This work intends to deal with the problem of misalignment in image stitching caused by small overlap area. To reduce mismatches between matched features pairs in two connected images, random sample consensus (RANSAC) [1] is usually adopted, which works under the assumption that the sampling of matched feature points with the largest number of inliers should be utilized to compute geometric matrix. However, this assumption does not hold in the case of small overlap area between the connected images, as compressing or turning over the image may result in better spatial consistency of matched feature points. Therefore, we propose a turnover and shape filter based feature matching method for image stitching. In the method, a turnover and shape filter is firstly used to filter out the samplings resulted from turnover and compression, which is then connected to RANSAC to yield final inliers. Experimental results from real-world datasets validate the effectiveness of our method.
© (2020) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Citation Download Citation
Shuang Song, Xinguo He, and Lin He "Turnover and shape filter based feature matching for image stitching", Proc. SPIE 11430, MIPPR 2019: Pattern Recognition and Computer Vision, 114301E (14 February 2020); https://doi.org/10.1117/12.2539406
ACCESS THE FULL ARTICLE
ORGANIZATIONAL
Sign in with credentials provided by your organization.
INSTITUTIONAL
Select your institution to access the SPIE Digital Library.
SELECT YOUR INSTITUTION
PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.
PERSONAL SIGN IN
No SPIE Account? Create one
PURCHASE THIS CONTENT
SUBSCRIBE TO DIGITAL LIBRARY
50 downloads per 1-year subscription
Members: $195
Non-members: $335 ADD TO CART
25 downloads per 1 - year subscription
Members: $145
Non-members: $250 ADD TO CART
PURCHASE SINGLE ARTICLE
Includes PDF, HTML & Video, when available
Members: $17.00
Non-members: $21.00 ADD TO CART
PROCEEDINGS
 6 PAGES
DOWNLOAD PAPER SAVE TO MY LIBRARY
GET CITATION
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Image filtering
Computer vision technology
Affine motion model
Feature extraction
Image fusion
RELATED CONTENT
Subscribe to Digital Library
Receive Erratum Email Alert
Back to Top