Real-Time Barcode Detection and Classification Using Deep Learning

Daniel Kold Hansen, Kamal Nasrollahi, Christoffer Bøgelund Rasmussen, Thomas B. Moeslund

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58 Citationer (Scopus)
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Abstract

Barcodes, in their different forms, can be found on almost any packages available in the market. Detecting and then decoding of barcodes have therefore great applications. We describe how to adapt the state-of-the- art deep learning-based detector of You Only Look Once (YOLO) for the purpose of detecting barcodes in a fast and reliable way. The detector is capable of detecting both 1D and QR barcodes. The detector achieves state-of-the-art results on the benchmark dataset of Muenster BarcodeDB with a detection rate of 0.991. The developed system can also find the rotation of both the 1D and QR barcodes, which gives the opportunity of rotating the detection accordingly which is shown to benefit the decoding process in a positive way. Both the detection and the rotation prediction shows real-time performance.
OriginalsprogEngelsk
TitelProceedings of the 9th International Joint Conference on Computational Intelligence - Volume 1: IJCCI
Vol/bind1
ForlagSCITEPRESS Digital Library
Publikationsdato2017
Sider321-327
ISBN (Trykt)978-989-758-274-5
DOI
StatusUdgivet - 2017
BegivenhedInternational Joint Conference on Computational Intelligence - Funchal, Portugal
Varighed: 1 nov. 20173 nov. 2017
Konferencens nummer: 9
http://www.ijcci.org/

Konference

KonferenceInternational Joint Conference on Computational Intelligence
Nummer9
Land/OmrådePortugal
ByFunchal
Periode01/11/201703/11/2017
Internetadresse

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