基于BOW的电能表分类

W. Mo, Liqiang Pei, Qingdan Huang, Weijie Liao
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引用次数: 0

摘要

电能表的自动检定具有重要意义,其中的关键是电能表类型的分类。本文提出了一种基于机器视觉的电能表类型识别方法。构建词袋模型(Bag-of-Words model, BOW),提取仪器的图像特征,构建视觉词典,在此基础上训练支持向量机分类器,实现仪器类型的自动识别。实验结果表明,该方法对几种特定功率计的分类率达到100%,具有重要的应用意义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Electric Power Meter Classification Based on BOW
The automatic verification of power meters is of great significance, and the key point is the classification of the power meter types. In this paper, we propose a power meter type recognition method based on machine vision. We construct a Bag-of-Words model(BOW), and extract the image features of the instrument, and construct a visual dictionary, based on which to train a support vector machine classifier to realize the automatic identification of the instrument type. The experimental results show that the proposed method achieves a classifiaction rate of 100% for several specific power meters, and is of great significance for applications.
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