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Improved RANSAC features image-matching method based on SURF

机译:改进的RANSAC具有基于冲浪的图像匹配方法

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摘要

For the speed of traditional SIFT algorithm in the feature extraction and matching is slow, the article proposes an improved RANSAC features image matching method based on speeded up robust features (SURF). First of all, detect images features and extract with SURF method, use the fast library for approximate nearest neighbours-based matcher method to perform initial matching on image feature points. Improve the RANSAC algorithm to increase the probability of correct matching points being sampled. Experimental results show that the improved RANSAC algorithm has high matching accuracy, good robustness, and short running time. It lays the foundation for the subsequent fast image stitching.
机译:对于特征提取和匹配中的传统SIFT算法的速度很慢,文章提出了一种改进的RANSAC具有基于加速鲁棒特征(冲浪)的图像匹配方法。首先,检测图像功能和用SURF方法提取,使用快速库进行近似最近邻居的匹配方法,以在图像特征点上执行初始匹配。提高RANSAC算法以增加正在采样的正确匹配点的概率。实验结果表明,改进的Ransac算法具有高匹配的精度,良好的鲁棒性和短时间内。它为随后的快速图像拼接奠定了基础。

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