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Sensitivity analysis of the error factors in the binocular vision measurement system

机译：双目视觉测量系统中误差因素的敏感性分析

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摘要

A method based on uniform experimental design and the backpropagation (BP) neural network to analyze the sensitivity of measurement errors in the binocular vision system is proposed. Six main error factors that affect the measurement accuracy of the system are summarized according to the binocular vision principle. The measurement experiment was carried out based on uniform design. The mapping relationship between the total measurement error and each error factor was established by BP neural network. Then the sensitivity coefficient of each error factor can be calculated by this mapping. These sensitivity coefficients provide a measure of the degree of influence each factor had on the total measurement error. The results show that the sensitivity coefficients of lens distortion and the image noise are 0.287 and 0.243, respectively, which are significantly higher than the other error factors. This means that these two error factors need to be emphatically suppressed during the measurement process.
机译：提出了一种基于均匀实验设计和BP神经网络的双目视觉系统中测量误差敏感性分析的方法。根据双目视觉原理，总结了影响系统测量精度的六个主要误差因素。测量实验是基于统一设计进行的。利用BP神经网络建立了总测量误差与各误差因子之间的映射关系。然后，可以通过该映射来计算每个误差因子的灵敏度系数。这些灵敏度系数提供了每个因素对总测量误差的影响程度的度量。结果表明，镜头畸变和图像噪声的敏感度系数分别为0.287和0.243，明显高于其他误差因子。这意味着在测量过程中需要着重抑制这两个误差因素。

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