The Use of Tesseract OCR Number Recognition for Food Tracking and Tracing

Stevan Cakic, Tomo Popović, Stevan Sandi, S. Krco, A. Gazivoda
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引用次数: 12

Abstract

One of the most interesting enabling technologies for digital transformation is computer vision. Object and character recognition has already become very popular and it is used in everyday life. This research focuses on the use of computer vision to read serial numbers from wine labels in order to enable applications based on tracking and tracing of each individual wine bottle. After experimenting with several OCR tools, an open source software called Tesseract OCR engine was selected for the pilot solution. The paper discusses the implementation and image processioning that improved detection accuracy. The coding was done in the Python programming language. The solution code was tested using real-life like images of wine serial numbers. In addition, a custom built web-based evaluation tool was created and used for the interactive evaluation of the system.
Tesseract OCR数字识别在食品跟踪与追溯中的应用
计算机视觉是数字化转型中最有趣的技术之一。对象和字符识别已经变得非常流行,并在日常生活中使用。本研究的重点是使用计算机视觉从葡萄酒标签上读取序列号,以实现基于每个单独酒瓶的跟踪和追踪的应用。在对几种OCR工具进行实验后,一个名为Tesseract OCR引擎的开源软件被选中作为试点解决方案。本文讨论了提高检测精度的实现方法和图像处理方法。代码是用Python编程语言编写的。解决方案代码使用现实生活中的葡萄酒序列号图像进行了测试。此外,还创建了一个自定义的基于web的评估工具,并将其用于系统的交互式评估。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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