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Faculté des Sciences appliquées
Faculté des Sciences appliquées
MASTER THESIS
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Master thesis : Research of an appropriate neural network architecture for the fast and accurate detection of DataMatrixCode

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Lamaye, Victor ULiège
Promotor(s) : Louppe, Gilles ULiège
Date of defense : 27-Jun-2022/28-Jun-2022 • Permalink : http://hdl.handle.net/2268.2/14393
Details
Title : Master thesis : Research of an appropriate neural network architecture for the fast and accurate detection of DataMatrixCode
Translated title : [fr] Recherche d'une architecture de réseaux de neurones adaptée à la détection rapide de codes Data Matrix
Author : Lamaye, Victor ULiège
Date of defense  : 27-Jun-2022/28-Jun-2022
Advisor(s) : Louppe, Gilles ULiège
Committee's member(s) : Van Droogenbroeck, Marc ULiège
Fontaine, Pascal ULiège
Braga, Calvin 
Language : English
Discipline(s) : Engineering, computing & technology > Computer science
Institution(s) : Université de Liège, Liège, Belgique
Degree: Master : ingénieur civil en science des données, à finalité spécialisée
Faculty: Master thesis of the Faculté des Sciences appliquées

Abstract

[en] In a world where more and more progress is made in various fields using the computational power of modern computers, many industries are using barcodes for different purposes going from identifying products to retrieve information to locating oneself in areas of a warehouse.
Decoding barcodes is thus at the core of processes of certain companies. Moreover, this task has to be done effectively, in terms of time and accuracy, making it challenging in real world applications where the barcode may not be at the center of the image, partly occluded, distorted or very blurry. Classical computer vision methods and models can be effective for certain types of images but when conditions are poor, they don't seem to work that fine. Fortunately, deep learning especially in the computer vision research field has been having great success among the researchers, making the progress in object detection task better and better. This work aims at finding a neural network architecture capable of locating Data Matrix code at a high speed with great accuracy. This work is mainly based around You Only Look Once (Yolo) and its upgrades throughout the years, while exploring different networks for optimal speed. Firstly, Data Matrix code will be detected using bounding boxes with their axis parallel to the borders of the images and later on, we will detect them with their four corners to make it easier for a decoding gent to identify the code, while having small and rapid models able to be run on CPU.


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Author

  • Lamaye, Victor ULiège Université de Liège > Master ingé. civ. sc. don. à . fin.

Promotor(s)

Committee's member(s)

  • Van Droogenbroeck, Marc ULiège Université de Liège - ULiège > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Télécommunications
    ORBi View his publications on ORBi
  • Fontaine, Pascal ULiège Université de Liège - ULiège > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Systèmes informatiques distribués
    ORBi View his publications on ORBi
  • Braga, Calvin
  • Total number of views 16
  • Total number of downloads 1










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