Abstract
In order to solve the problems such as time consuming and mismatching in the experiment of eliminating SIFT mismatch points in RANSAC algorithm, proposed Mismatching Elimination Algorithm in SIFT Based on Function Fitting; Firstly, we use SIFT algorithm to direct the matching of the image and the matching image, using iterative least squares fitting method to construct function model for the key points of matched Image; secondly, fit the function model with the key points of matching image features; Finally, the errors of the two algorithms are calculated, when the error is greater than the set threshold, verify that the point is a mismatch point, and it is eliminated. The experimental results show that using Mismatching Elimination Algorithm in SIFT Based on Function Fitting than RANSAC algorithm in time to save the 2 s on average, the correct matching rate is increased by 11.75%, and more correct matching points can be reserved.
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Zhong, X., Li, Y., Ren, J. (2018). Mismatching Elimination Algorithm in SIFT Based on Function Fitting. In: Ren, J., et al. Advances in Brain Inspired Cognitive Systems. BICS 2018. Lecture Notes in Computer Science(), vol 10989. Springer, Cham. https://doi.org/10.1007/978-3-030-00563-4_23
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DOI: https://doi.org/10.1007/978-3-030-00563-4_23
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