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Binocular vision physical coordinate positioning algorithm based on PSO-Harris operator

机译:基于PSO-Harris算子的双目视觉物理坐标定位算法

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Aiming at the problems of low accuracy, low positioning accuracy and low efficiency of feature points extraction inexisting binocular vision positioning methods, and classical Harris corner detection algorithms depending on theselection of experiential threshold and the setting of corner points extraction, a corner detection algorithm based on PSOHarrisoperator to detect the double threshold is proposed in this paper, which calculates the optimal threshold bydynamic iterative optimization of the threshold. On this basis, the feature point parallax is calculated to match the imagefeatures, and the coordinates of the world coordinate system are calculated according to the coordinates of the targetpoint. The comparison experiments show that the algorithm effectively improves the positioning accuracy and efficiencyof feature point extraction.
机译:针对现有技术中特征点提取精度低,定位精度低,效率低的问题。 现有的双目视觉定位方法,以及传统的哈里斯角点检测算法,具体取决于 经验阈值的选择和角点提取的设置,基于PSOHarris的角点检测算法 本文提出了一种检测双阈值的算子,该算子通过 阈值的动态迭代优化。在此基础上,计算特征点视差以匹配图像 要素,并根据目标的坐标计算世界坐标系的坐标 观点。对比实验表明,该算法有效提高了定位精度和效率。 特征点提取。

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