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

Abstract

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.

Fast Restoration for Out-of-Focus Blurred Images of QR Code With Edge Prior Information via Image Sensing

“…Large screen counter and infrared sensor probe the key to such systems. How to accurately and rapidly identify the QR code depends on the efficacy and efficiency of the system, as well as the capacity and scale of the warehouse [14]. However, as captured moments are ephemeral and difficult to reproduce, the out-of-focus blur caused by lens loose or lens vibration in the optical imaging process has introduced a lot of unnecessary time cost to the warehouse management system.…”

Research on Logistic Warehouse Scheduling Management With IoT and Human-Machine Interface

“…It recommends the features of the WMS, such as the process of order selection (Minashkina et al, 2020). An IoT computer can supply information on the products to the pickers' job position of the performance and the order picking development to increase (Lorenc et al, 2020;Chen et al, 2019). The heavy workload of staff is the central concern (Kutlu Gündoğdu et al, 2019).…”

Robust Combined Binarization Method of Non-Uniformly Illuminated Document Images for Alphanumerical Character Recognition

“…One of the dynamically growing areas of the applications of video technologies based on the use of camera sensors is related to the utilization of Optical Character Recognition (OCR) systems. Some of them include: document image analysis, recognition of the QR codes from natural images [1,2], as well as automatic scanning and digitization of books [3], where additional infrared cameras may also be applied, e.g., supporting the straightening process for the scanned pages. Considering the wide application possibilities of binary image analysis for shape recognition, also in embedded systems with limited computational power and a relatively small amount of memory, a natural direction seems to be their utilization in mobile devices.…”