Advertisement
Published in:
2014 | OriginalPaper | Chapter
Hough-RANSAC: A Fast and Robust Method for Rejecting Mismatches
Authors : Hongxia Gao, Jianhe Xie, Yueming Hu, Ze Yang
Published in: Pattern Recognition
Publisher: Springer Berlin Heidelberg
Activate our intelligent search to find suitable subject content or patents.
Select sections of text to find matching patents with Artificial Intelligence. powered by
Select sections of text to find additional relevant content using AI-assisted search. powered by
This paper proposed a novel method - Hough-RANSAC for rejecting mismatches in image registration. Many well-known algorithms for rejecting mismatches, such as the Least Median of Square regression algorithm (LMedS) and the Random Sample Consensus algorithm (RANSAC), perform poorly when the percent of mismatches is more than 50%. Compared with the two well-known algorithms, the Hough-RANSAC algorithm can guarantee both time performance and accuracy, even if the percent of correct matches fell much below 20%.