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Detection and identification method of medical label barcode based on deep learning

机译:基于深度学习的医用标签条形码检测与识别方法

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The widespread use of barcode technology has led to the complexity of the application scenario. In the traditional barcode recognition method, there is no universal solution to the problems of uneven illumination, distortion, and sheltered. In this paper, the deep learning theory is used to solve the problem of barcode detection under the above situation. And on this basis, the problem of correcting linear distortion Data Matrix code is solved, and the key technology of barcode recognition under complex situation is broken through. After testing, the recognition speed reached 125ms, and the recognition accuracy reached about 93%. The system uses CCD camera to collect pictures, adopts the HALCON to build the processing algorithm, and uses Visual Studio platform to build the software, which realizes the Date Matrix code, Drug Electronic Supervision Code and Product bar code fast and accurate identification on pharmaceutical packaging. The developed system can also detect the rotation angle of Barcode and Data Matrix code, which is favorable for reading the barcode information. The whole process is real-time.
机译:条形码技术的广泛使用导致了应用方案的复杂性。在传统的条形码识别方法中,没有通用的方法,对照明,扭曲和庇护的不均匀问题。在本文中,深入学习理论用于解决上述情况下的条形码检测问题。在此基础上,解决了校正线性失真数据矩阵代码的问题,并且在复杂情况下的条形码识别的关键技术被打破了。在测试之后,识别速度达到125ms,识别精度达到约93%。系统使用CCD相机收集图片,采用HALCON构建处理算法,并使用Visual Studio平台构建软件,该软件实现日期矩阵代码,药物电子监控码和产品条形码快速准确地识别药品包装。开发系统还可以检测条形码和数据矩阵码的旋转角度,这有利于读取条形码信息。整个过程是实时的。

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