Development of a Price Tag Detection System on Mobile Devices using Deep Learning

Melek Turan, M. Peker, Hüseyin Özkan, Cevat Balaban, Nadir Kocakır, Önder Karademir
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引用次数: 1

Abstract

Ensuring customer satisfaction is an important issue in the retail industry. The way to achieve this satisfaction is to provide a quality service. The data on the price tags on the product shelves are frequently updated. These data should be included on the price tags in their current form. Customers may encounter inaccurate information on price tags in shopping places, which causes negative results in terms of customer loyalty and satisfaction. The data on the price tags is mostly checked manually, which can cause human errors. In this study, a deep learning-based solution is proposed for fast and high accuracy detection of price tag area. One of the first and important stages of a deep learning-based price recognition system is the correct detection of the price tag area. The successful execution of this stage is important for the successful execution of the next processes (barcode reading, price reading). The proposed method has been tested on mobile phones. It is envisaged that the proposed method is applicable in its current form and can be a technical reference for similar problems in the retail industry.
基于深度学习的移动设备价格标签检测系统的开发
确保顾客满意是零售业的一个重要问题。实现这种满意的方法是提供优质的服务。产品货架上的价格标签上的数据经常更新。这些数据应以当前形式包含在价格标签上。顾客在购物场所可能会遇到价格标签信息不准确的情况,这会对顾客的忠诚度和满意度产生负面影响。价格标签上的数据大多是人工检查的,这可能会导致人为错误。本文提出了一种基于深度学习的价格标签区域快速、高精度检测方法。基于深度学习的价格识别系统的第一个重要阶段是正确检测价格标签区域。此阶段的成功执行对于下一个过程(条形码读取、价格读取)的成功执行非常重要。该方法已经在手机上进行了测试。设想所提出的方法在目前的形式下是适用的,可以作为零售行业类似问题的技术参考。
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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