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Fast and accurate recognition for codes on complex backgrounds for real-life industrial applications
المؤلفون المشاركون
Sun, Wei
Zhang, Dan
Wang, Yaonan
Liang, Qiaokang
Ge, Qiao
Zou, Kunlin
المصدر
Journal of Engineering Research
العدد
المجلد 11، العدد 1 A (31 مارس/آذار 2023)، ص ص. 340-354، 15ص.
الناشر
جامعة الكويت مجلس النشر العلمي
تاريخ النشر
2023-03-31
دولة النشر
الكويت
عدد الصفحات
15
التخصصات الرئيسية
الملخص EN
In the food and beverage industry, the existing recognition of code characters on the surface of complex packaging usually suffers from low accuracy and low speed.
This work presents an efficient and accurate inkjet code recognition system based on the combination of the deep learning and traditional image processing methods.
The proposed system mainly consists of three sequential modules, i.e., the character’s region extraction by modified YOLOv3-tiny network, the character processing by the traditional image processing methods such as binarization and the modified character projection segmentation, and the character recognition by a Convolutional recurrent neural network (CRNN) model based on a modified version of MobileNetV3.
In this system, only a small amount of tag data has been made and an effective character data generator is designed to randomly generate different experimental data for the CRNN model training.
To the best of our knowledge, this report for the first time describes that deep learning has been applied to the recognition of codes on complex background for the real-life industrial application.
Experimental results have been provided to verify the accuracy and effectiveness of the proposed model, demonstrating a recognition accuracy of 0.986 and a processing speed of 100 ms per bottle in the end-to-end character recognition system.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Liang, Qiaokang& Ge, Qiao& Sun, Wei& Zhang, Dan& Wang, Yaonan& Zou, Kunlin. 2023. Fast and accurate recognition for codes on complex backgrounds for real-life industrial applications. Journal of Engineering Research،Vol. 11, no. 1 A, pp.340-354.
https://search.emarefa.net/detail/BIM-1494694
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Liang, Qiaokang…[et al.]. Fast and accurate recognition for codes on complex backgrounds for real-life industrial applications. Journal of Engineering Research Vol. 11, no. 1 A (Mar. 2023), pp.340-354.
https://search.emarefa.net/detail/BIM-1494694
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Liang, Qiaokang& Ge, Qiao& Sun, Wei& Zhang, Dan& Wang, Yaonan& Zou, Kunlin. Fast and accurate recognition for codes on complex backgrounds for real-life industrial applications. Journal of Engineering Research. 2023. Vol. 11, no. 1 A, pp.340-354.
https://search.emarefa.net/detail/BIM-1494694
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references : p. 353-354
رقم السجل
BIM-1494694
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
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