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Adaptive Binarization of QR Code Images for Fast Automatic Sorting in Warehouse Systems

机译:仓库系统中快速自动排序的QR码图像的自适应二值图

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摘要

As the fundamental element of the Internet of Things, the QR code has become increasingly crucial for connecting online and offline services. Concerning e-commerce and logistics, we mainly focus on how to identify QR codes quickly and accurately. An adaptive binarization approach is proposed to solve the problem of uneven illumination in warehouse automatic sorting systems. Guided by cognitive modeling, we adaptively select the block window of the QR code for robust binarization under uneven illumination. The proposed method can eliminate the impact of uneven illumination of QR codes effectively whilst meeting the real-time needs in the automatic warehouse sorting. Experimental results have demonstrated the superiority of the proposed approach when benchmarked with several state-of-the-art methods.
机译:作为事物互联网的基本要素,QR码对连接在线和离线服务越来越重要。关于电子商务和物流,主要关注如何快速准确地识别QR码。建议采用自适应二值化方法来解决仓库自动分拣系统中不均匀照明的问题。通过认知建模引导,我们自适应地选择QR码的块窗口,以在不均匀照明下的鲁棒二值化。所提出的方法可以消除QR码不均匀照明的影响,同时满足自动仓库分类的实时需求。实验结果表明,当用几种最先进的方法进行基准测试时,所提出的方法的优越性。

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