Abstract
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%.
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Gao, H., Xie, J., Hu, Y., Yang, Z. (2014). Hough-RANSAC: A Fast and Robust Method for Rejecting Mismatches. In: Li, S., Liu, C., Wang, Y. (eds) Pattern Recognition. CCPR 2014. Communications in Computer and Information Science, vol 483. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-45646-0_37
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DOI: https://doi.org/10.1007/978-3-662-45646-0_37
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