@article {2357, title = {Improved QR Code Localization Using Boosted Cascade of Weak Classifiers}, journal = {Acta Cybernetica}, volume = {22}, year = {2015}, month = {2015}, pages = {21-33}, publisher = {University of Szeged}, type = {Journal article}, chapter = {21}, address = {Szeged, Hungary}, author = {P{\'e}ter Bodn{\'a}r and L{\'a}szl{\'o} G Ny{\'u}l} } @conference {2202, title = {Localization of Visual Codes using Fuzzy Inference System}, booktitle = {International Conference on Computer Vision Theory and Applications (VISAPP)}, year = {2015}, month = {March 2015}, pages = {345-352}, publisher = {SciTePress}, organization = {SciTePress}, type = {Conference paper}, address = {Berlin, Germany}, author = {P{\'e}ter Bodn{\'a}r and Ny{\'u}l, L{\'a}szl{\'o} G{\'a}bor}, editor = {J Braz and S Battiato and F Imai} } @conference {2099, title = {QR k{\'o}d lokaliz{\'a}ci{\'o} kaszk{\'a}dolt gyenge oszt{\'a}lyoz{\'o}k haszn{\'a}lat{\'a}val}, booktitle = {K{\'e}pfeldolgoz{\'o}k {\'e}s Alakfelismer{\H o}k T{\'a}rsas{\'a}g{\'a}nak 10. orsz{\'a}gos konferenci{\'a}ja}, year = {2015}, month = {Jan 2015}, pages = {712-721}, type = {Conference paper}, address = {Kecskem{\'e}t, Magyarorsz{\'a}g}, author = {P{\'e}ter Bodn{\'a}r and L{\'a}szl{\'o} G{\'a}bor Ny{\'u}l} } @conference {2098, title = {Vizu{\'a}lis k{\'o}dok lokaliz{\'a}ci{\'o}ja m{\'e}ly egyenir{\'a}ny{\'\i}tott neur{\'a}lis h{\'a}l{\'o} haszn{\'a}lat{\'a}val}, booktitle = {K{\'e}pfeldolgoz{\'o}k {\'e}s Alakfelismer{\H o}k T{\'a}rsas{\'a}g{\'a}nak 10. orsz{\'a}gos konferenci{\'a}ja.}, year = {2015}, month = {Jan 2015}, pages = {546-561}, type = {Conference paper}, address = {Kecskem{\'e}t, Magyarorsz{\'a}g}, author = {P{\'e}ter Bodn{\'a}r and L{\'a}szl{\'o} G{\'a}bor Ny{\'u}l and Tam{\'a}s Gr{\'o}sz and L{\'a}szl{\'o} T{\'o}th} } @inbook {1099, title = {Localization of Visual Codes in the DCT Domain Using Deep Rectier Neural Networks}, booktitle = {International Conference on Informatics in Control, Automation and Robotics (ICINCO)}, year = {2014}, note = {Art. No.: 6K{\"o}zl{\'e}sre elfogadva}, month = {2014}, publisher = {SCITEPRESS}, organization = {SCITEPRESS}, type = {Conference paper}, address = {Set{\'u}bal}, author = {P{\'e}ter Bodn{\'a}r and Tam{\'a}s Gr{\'o}sz and L{\'a}szl{\'o} T{\'o}th and L{\'a}szl{\'o} G{\'a}bor Ny{\'u}l}, editor = {Joaquim Filipe and Oleg Gusikhin and Kurosh Madani and Jurek Sasiadek} } @article {1095, title = {QR Code Localization Using Boosted Cascade of Weak Classifiers}, year = {2014}, month = {June 2014}, pages = {6 - 7}, publisher = {Institute of Informatics, University of Szeged}, type = {Abstract}, address = {Szeged}, author = {P{\'e}ter Bodn{\'a}r and L{\'a}szl{\'o} G{\'a}bor Ny{\'u}l} } @inbook {1097, title = {QR Code Localization Using Boosted Cascade of Weak Classifiers}, booktitle = {Image Analysis and Recognition (ICIAR)}, series = {Lecture Notes In Computer Science}, number = {8814}, year = {2014}, note = {Art. No.: 225Accepted for publication}, month = {Oct 2014}, publisher = {Springer-Verlag}, organization = {Springer-Verlag}, type = {Conference paper}, address = {Vilamura, Portugal}, abstract = {

Usage of computer-readable visual codes became common in oureveryday life at industrial environments and private use. The reading process of visual codes consists of two steps: localization and data decoding. Unsupervised localization is desirable at industrial setups and for visually impaired people. This paper examines localization efficiency of cascade classifiers using Haar-like features, Local Binary Patterns and Histograms of Oriented Gradients, trained for the finder patterns of QR codes and for the whole code region as well, and proposes improvements in post-processing.

}, author = {P{\'e}ter Bodn{\'a}r and L{\'a}szl{\'o} G{\'a}bor Ny{\'u}l}, editor = {Mohamed Kamel and Aur{\'e}lio Campilho} } @inbook {1098, title = {QR code localization using deep neural networks}, booktitle = {International Workshop on Machine Learning for Signal Processing}, year = {2014}, note = {Art. No.: 43Accepted for publication$\#$K{\"o}nyv Kiad{\'a}s helye ismeretlen }, month = {Sep 2014}, publisher = {IEEE}, organization = {IEEE}, type = {Conference paper}, address = {Sep 2014, Reims, France}, author = {Tam{\'a}s Gr{\'o}sz and P{\'e}ter Bodn{\'a}r and L{\'a}szl{\'o} T{\'o}th and L{\'a}szl{\'o} G{\'a}bor Ny{\'u}l}, editor = {Mboup Mamadou and Adali T{\"u}lay and Eric Moreau and Jan Larsen and Kevin Guelton} } @article {1080, title = {Barcode detection using local analysis, mathematical morphology, and clustering}, journal = {ACTA CYBERNETICA-SZEGED}, volume = {21}, year = {2013}, month = {2013}, pages = {21 - 35}, type = {Journal article}, abstract = {

Barcode detection is required in a wide range of real-lifeapplications. Imaging conditions and techniques vary considerably and each application has its own requirements for detection speed and accuracy. In our earlier works we built barcode detectors using morphological operations and uniform partitioning with several approaches and showed their behaviour on a set of test images. In this work, we extend those ideas with clustering, contrast measuring, distance transformation and probabilistic Hough transformation.

}, isbn = {0324-721X}, author = {P{\'e}ter Bodn{\'a}r and L{\'a}szl{\'o} G{\'a}bor Ny{\'u}l} } @conference {1065, title = {Barcode detection with uniform partitioning and distance transformation}, booktitle = {IASTED International Conference on Computer Graphics and Imaging (CGIM)}, year = {2013}, note = {doi: 10.2316/P.2013.797-022}, month = {Feb 2013}, pages = {48 - 53}, publisher = {IASTED - Acta Press}, organization = {IASTED - Acta Press}, type = {Conference paper}, address = {Innsbruck, Austria}, abstract = {

Barcode detection is required in a wide range of real-lifeapplications. Imaging conditions and techniques vary considerably and each application has its own requirements for detection speed and accuracy. In our earlier works we used uniform partitioning with several approaches for detection of various types of 1D and 2D barcodes and showed their behaviour on a set of test images. In this work, we extend the partitioning idea and replace scan-line based methods with distance transformation to improve accuracy.

}, doi = {10.2316/P.2013.797-022}, url = {http://www.actapress.com/PaperInfo.aspx?paperId=454988}, author = {P{\'e}ter Bodn{\'a}r and L{\'a}szl{\'o} G{\'a}bor Ny{\'u}l}, editor = {L Linsen} } @inbook {1081, title = {A Novel Method for Barcode Localization in Image Domain}, booktitle = {Image Analysis and Recognition (ICIAR) }, series = {Lecture Notes in Computer Science}, year = {2013}, note = {doi: 10.1007/978-3-642-39094-4_22}, month = {June 2013}, pages = {189 - 196}, publisher = {Springer-Verlag}, organization = {Springer-Verlag}, type = {Conference paper}, address = {Berlin}, abstract = {

Barcode localization is an essential step of the barcode readingprocess. For industrial environments, having high-resolution cameras and eventful scenarios, fast and reliable localization is crucial. Images acquired in those setups have limited parameters, however, they vary at each application. In earlier works we have already presented various barcode features to track for localization process. In this paper, we present a novel approach for fast barcode localization using a limited set of pixels in image domain.

}, doi = {10.1007/978-3-642-39094-4_22}, author = {P{\'e}ter Bodn{\'a}r and L{\'a}szl{\'o} G{\'a}bor Ny{\'u}l}, editor = {Mohamed Kamel and Aur{\'e}lio Campilho} } @conference {1068, title = {Vizu{\'a}lis k{\'o}dok lokaliz{\'a}l{\'a}s{\'a}nak jav{\'\i}t{\'a}sa egyszer{\H u} jellemz{\H o}k kombin{\'a}ci{\'o}j{\'a}val}, booktitle = {A K{\'e}pfeldolgoz{\'o}k {\'e}s Alakfelismer{\H o}k T{\'a}rsas{\'a}g{\'a}nak konferenci{\'a}ja - K{\'E}PAF 2013}, year = {2013}, month = {Jan 2013}, pages = {483 - 495}, publisher = {NJSZT-K{\'E}PAF}, organization = {NJSZT-K{\'E}PAF}, type = {Conference paper}, address = {Veszpr{\'e}m}, author = {P{\'e}ter Bodn{\'a}r and L{\'a}szl{\'o} G{\'a}bor Ny{\'u}l}, editor = {L{\'a}szl{\'o} Cz{\'u}ni} } @conference {1061, title = {Barcode Detection with Morphological Operations and Clustering}, booktitle = {Proceedings of the IASTED International Conference on Signal Processing, Pattern Recognition, and Applications (SPPRA)}, year = {2012}, note = {ScopusID: 84864778306doi: 10.2316/P.2012.778-014}, month = {June 2012}, pages = {51 - 57}, publisher = {IASTED - Acta Press}, organization = {IASTED - Acta Press}, type = {Conference paper}, address = {Crete, Greek}, abstract = {

Barcode detection has many applications and detection methods. Each application has its own requirements for speed and detection accuracy. Fine-tuning, upgrading or combining existing methods gives fast and robust solutions for detection. Modern computer vision techniques help the whole process to be fully automated. Different detection approaches are examined in this paper, and new methods are introduced.

}, doi = {10.2316/P.2012.778-014}, author = {P{\'e}ter Bodn{\'a}r and L{\'a}szl{\'o} G{\'a}bor Ny{\'u}l}, editor = {M Petrou and A D Sappa and A G Triantafyllidis} } @article {1062, title = {Barcode Detection with Uniform Partitioning and Morphological Operations}, year = {2012}, month = {June 2012}, pages = {4 - 5}, publisher = {University of Szeged, Institute of Informatics}, type = {Abstract}, address = {Szeged}, author = {P{\'e}ter Bodn{\'a}r and L{\'a}szl{\'o} G{\'a}bor Ny{\'u}l} } @conference {1063, title = {Improving barcode detection with combination of simple detectors}, booktitle = {Proceedings of the International Conference on Signal Image Technology \& Internet Systems (SITIS)}, year = {2012}, note = {ScopusID: 84874080233doi: 10.1109/SITIS.2012.52}, month = {Nov 2012}, pages = {300 - 306}, publisher = {IEEE}, organization = {IEEE}, type = {Conference paper}, address = {Naples, Italy}, abstract = {

Barcode detection is required in a wide range of real-life applications. Imaging conditions and techniques vary considerably and each application has its own requirements for detection speed and accuracy. In our earlier works we built barcode detectors using morphological operations and uniform partitioning with several approaches and showed their behaviour on a set of test images. In this work, we examine ensemble efficiency of those simple detectors using various aggregation methods. Using a combination of several simple features localization performance improves significantly.

}, doi = {10.1109/SITIS.2012.52}, author = {P{\'e}ter Bodn{\'a}r and L{\'a}szl{\'o} G{\'a}bor Ny{\'u}l}, editor = {Kokou Yetongnon and Richard Chbeir and Albert Dipanda and Luigi Gallo} }