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Character recognition for automotive electrical box components based on Machine vision

机译:基于机器视觉的汽车电器箱部件字符识别

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According to the features of the electric box components, the characters on the components are identified from the general optical character recognition process. The problem of multi classification in the recognition process is studied. First, the paper introduces the machine vision components of automotive electrical box system based on automatic detection; then, according to the multi classification support vector machine learning, we propose a support vector machine and active learning and give the idea of combining active learning model, the inquiry mechanism is established according to the fuzzy sample in the learning process; Finally, a multi-classifier construction algorithm is given based on the interrogation strategy. The algorithm is applied to character recognition of new energy electrical box components by software programming, and the effectiveness of the algorithm is verified, the robustness of the algorithm is enhanced, and the recognition rate is improved.
机译:根据电箱组件的特征,通过一般的光学字符识别过程来识别组件上的字符。研究了识别过程中的多分类问题。首先,本文介绍了基于自动检测的汽车电器箱系统的机器视觉组件。然后,根据多分类支持向量机学习,提出一种支持向量机和主动学习,并提出结合主动学习模型的思想,根据学习过程中的模糊样本建立查询机制。最后,提出了一种基于查询策略的多分类器构造算法。通过软件编程将该算法应用于新能源电器箱部件的字符识别,验证了算法的有效性,增强了算法的鲁棒性,提高了识别率。

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