A novel algorithm using computer vision and machine learning techniques has been developed in this research and applied to automate the reading of analog meters. This approach does not rely on any prior information about the meter being read or any human intervention during the process. High-level features of the meter, including the graduation values and angles, are extracted using a cascade of image contour filters with a series of digit classifiers. The features are refined and used to train regression models that return the reading of the analog meter automatically.

中文翻译：

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智能仪表阅读器：使用计算机视觉和机器学习自动抄表

本研究开发了一种使用计算机视觉和机器学习技术的新算法，并将其应用于自动读取模拟仪表。这种方法不依赖于有关正在读取的仪表的任何先验信息或在此过程中的任何人为干预。使用带有一系列数字分类器的级联图像轮廓滤波器提取仪表的高级特征，包括刻度值和角度。这些特征被改进并用于训练自动返回模拟仪表读数的回归模型。