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Research on adaptive SIFT algorithm in image matching of pipeline inner surface visual measurement

机译:自适应SIFT算法在管道内表面视觉测量图像匹配中的研究

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SIFT algorithm has many advantages such as high matching rate and good robustness. However, it still has same imperfect. Due to the large number of key points and large amount of computation, the processing speed is very slow. This article propose an improved SIFT matching algorithm with threshold and adaptive. In this algorithm, the threshold size is changeable. The number of feature points and the spatial domain are also controllable. The matching accuracy and speed can be improved by optimizing parameters. Then stereo image matching of inner surface of pipeline can be realized. Experimental results show that the matching rate and the matching speed are improved obviously. The algorithm can be applied to the matching of the inner surface corrosion images.
机译:SIFT算法具有匹配率高,鲁棒性好等优点。但是,它仍然具有同样的缺陷。由于关键点数量众多且计算量大,因此处理速度非常慢。本文提出了一种改进的具有阈值和自适应的SIFT匹配算法。在此算法中,阈值大小是可变的。特征点的数量和空间域也是可控制的。通过优化参数可以提高匹配精度和速度。然后可以实现管道内表面的立体图像匹配。实验结果表明,匹配率和匹配速度都有明显提高。该算法可以应用于内表面腐蚀图像的匹配。

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