<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Péter Bodnár</style></author><author><style face="normal" font="default" size="100%">László G Nyúl</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Improved QR Code Localization Using Boosted Cascade of Weak Classifiers</style></title><secondary-title><style face="normal" font="default" size="100%">Acta Cybernetica</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2015</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2015</style></date></pub-dates></dates><publisher><style face="normal" font="default" size="100%">University of Szeged</style></publisher><pub-location><style face="normal" font="default" size="100%">Szeged, Hungary</style></pub-location><volume><style face="normal" font="default" size="100%">22</style></volume><pages><style face="normal" font="default" size="100%">21-33</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><issue><style face="normal" font="default" size="100%">1</style></issue><work-type><style face="normal" font="default" size="100%">Journal article</style></work-type><section><style face="normal" font="default" size="100%">21</style></section></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Péter Bodnár</style></author><author><style face="normal" font="default" size="100%">Nyúl, László Gábor</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">J Braz</style></author><author><style face="normal" font="default" size="100%">S Battiato</style></author><author><style face="normal" font="default" size="100%">F Imai</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Localization of Visual Codes using Fuzzy Inference System</style></title><secondary-title><style face="normal" font="default" size="100%">International Conference on Computer Vision Theory and Applications (VISAPP)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2015</style></year><pub-dates><date><style  face="normal" font="default" size="100%">March 2015</style></date></pub-dates></dates><publisher><style face="normal" font="default" size="100%">SciTePress</style></publisher><pub-location><style face="normal" font="default" size="100%">Berlin, Germany</style></pub-location><pages><style face="normal" font="default" size="100%">345-352</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><work-type><style face="normal" font="default" size="100%">Conference paper</style></work-type></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Péter Bodnár</style></author><author><style face="normal" font="default" size="100%">László Gábor Nyúl</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">QR kód lokalizáció kaszkádolt gyenge osztályozók használatával</style></title><secondary-title><style face="normal" font="default" size="100%">Képfeldolgozók és Alakfelismerők Társaságának 10. országos konferenciája</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2015</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Jan 2015</style></date></pub-dates></dates><pub-location><style face="normal" font="default" size="100%">Kecskemét, Magyarország</style></pub-location><pages><style face="normal" font="default" size="100%">712-721</style></pages><language><style face="normal" font="default" size="100%">hun</style></language><work-type><style face="normal" font="default" size="100%">Conference paper</style></work-type></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Péter Bodnár</style></author><author><style face="normal" font="default" size="100%">László Gábor Nyúl</style></author><author><style face="normal" font="default" size="100%">Tamás Grósz</style></author><author><style face="normal" font="default" size="100%">László Tóth</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Vizuális kódok lokalizációja mély egyenirányított neurális háló használatával</style></title><secondary-title><style face="normal" font="default" size="100%">Képfeldolgozók és Alakfelismerők Társaságának 10. országos konferenciája.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2015</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Jan 2015</style></date></pub-dates></dates><pub-location><style face="normal" font="default" size="100%">Kecskemét, Magyarország</style></pub-location><pages><style face="normal" font="default" size="100%">546-561</style></pages><language><style face="normal" font="default" size="100%">hun</style></language><work-type><style face="normal" font="default" size="100%">Conference paper</style></work-type></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Péter Bodnár</style></author><author><style face="normal" font="default" size="100%">Tamás Grósz</style></author><author><style face="normal" font="default" size="100%">László Tóth</style></author><author><style face="normal" font="default" size="100%">László Gábor Nyúl</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Joaquim Filipe</style></author><author><style face="normal" font="default" size="100%">Oleg Gusikhin</style></author><author><style face="normal" font="default" size="100%">Kurosh Madani</style></author><author><style face="normal" font="default" size="100%">Jurek Sasiadek</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Localization of Visual Codes in the DCT Domain Using Deep Rectier Neural Networks</style></title><secondary-title><style face="normal" font="default" size="100%">International Conference on Informatics in Control, Automation and Robotics (ICINCO)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2014</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2014</style></date></pub-dates></dates><publisher><style face="normal" font="default" size="100%">SCITEPRESS</style></publisher><pub-location><style face="normal" font="default" size="100%">Setúbal</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language><work-type><style face="normal" font="default" size="100%">Conference paper</style></work-type><notes><style face="normal" font="default" size="100%">Art. No.: 6Közlésre elfogadva</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>13</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Péter Bodnár</style></author><author><style face="normal" font="default" size="100%">László Gábor Nyúl</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">QR Code Localization Using Boosted Cascade of Weak Classifiers</style></title><secondary-title><style face="normal" font="default" size="100%">Conference of PhD Students in Computer Science. Volume of Extended Abstracts</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2014</style></year><pub-dates><date><style  face="normal" font="default" size="100%">June 2014</style></date></pub-dates></dates><publisher><style face="normal" font="default" size="100%">Institute of Informatics, University of Szeged</style></publisher><pub-location><style face="normal" font="default" size="100%">Szeged</style></pub-location><pages><style face="normal" font="default" size="100%">6 - 7</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><work-type><style face="normal" font="default" size="100%">Abstract</style></work-type></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Péter Bodnár</style></author><author><style face="normal" font="default" size="100%">László Gábor Nyúl</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Mohamed Kamel</style></author><author><style face="normal" font="default" size="100%">Aurélio Campilho</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">QR Code Localization Using Boosted Cascade of Weak Classifiers</style></title><secondary-title><style face="normal" font="default" size="100%">Image Analysis and Recognition (ICIAR)</style></secondary-title><tertiary-title><style face="normal" font="default" size="100%">Lecture Notes In Computer Science</style></tertiary-title><alt-title><style face="normal" font="default" size="100%">LNCS</style></alt-title></titles><dates><year><style  face="normal" font="default" size="100%">2014</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Oct 2014</style></date></pub-dates></dates><number><style face="normal" font="default" size="100%">8814</style></number><publisher><style face="normal" font="default" size="100%">Springer-Verlag</style></publisher><pub-location><style face="normal" font="default" size="100%">Vilamura, Portugal</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;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.&lt;/p&gt;</style></abstract><work-type><style face="normal" font="default" size="100%">Conference paper</style></work-type><notes><style face="normal" font="default" size="100%">Art. No.: 225Accepted for publication</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Tamás Grósz</style></author><author><style face="normal" font="default" size="100%">Péter Bodnár</style></author><author><style face="normal" font="default" size="100%">László Tóth</style></author><author><style face="normal" font="default" size="100%">László Gábor Nyúl</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Mboup Mamadou</style></author><author><style face="normal" font="default" size="100%">Adali Tülay</style></author><author><style face="normal" font="default" size="100%">Eric Moreau</style></author><author><style face="normal" font="default" size="100%">Jan Larsen</style></author><author><style face="normal" font="default" size="100%">Kevin Guelton</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">QR code localization using deep neural networks</style></title><secondary-title><style face="normal" font="default" size="100%">International Workshop on Machine Learning for Signal Processing</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2014</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Sep 2014</style></date></pub-dates></dates><publisher><style face="normal" font="default" size="100%">IEEE</style></publisher><pub-location><style face="normal" font="default" size="100%">Sep 2014, Reims, France</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language><work-type><style face="normal" font="default" size="100%">Conference paper</style></work-type><notes><style face="normal" font="default" size="100%">Art. No.: 43Accepted for publication#Könyv  Kiadás helye ismeretlen
</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Péter Bodnár</style></author><author><style face="normal" font="default" size="100%">László Gábor Nyúl</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Barcode detection using local analysis, mathematical morphology, and clustering</style></title><secondary-title><style face="normal" font="default" size="100%">ACTA CYBERNETICA-SZEGED</style></secondary-title><short-title><style face="normal" font="default" size="100%">ACTA CYBERN-SZEGED</style></short-title></titles><dates><year><style  face="normal" font="default" size="100%">2013</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2013</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">21</style></volume><pages><style face="normal" font="default" size="100%">21 - 35</style></pages><isbn><style face="normal" font="default" size="100%">0324-721X</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;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.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">1</style></issue><work-type><style face="normal" font="default" size="100%">Journal article</style></work-type></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Péter Bodnár</style></author><author><style face="normal" font="default" size="100%">László Gábor Nyúl</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">L Linsen</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Barcode detection with uniform partitioning and distance transformation</style></title><secondary-title><style face="normal" font="default" size="100%">IASTED International Conference on Computer Graphics and Imaging (CGIM)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2013</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Feb 2013</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.actapress.com/PaperInfo.aspx?paperId=454988</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">IASTED - Acta Press</style></publisher><pub-location><style face="normal" font="default" size="100%">Innsbruck, Austria</style></pub-location><pages><style face="normal" font="default" size="100%">48 - 53</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;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.&lt;/p&gt;</style></abstract><work-type><style face="normal" font="default" size="100%">Conference paper</style></work-type><notes><style face="normal" font="default" size="100%">doi: 10.2316/P.2013.797-022</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Péter Bodnár</style></author><author><style face="normal" font="default" size="100%">László Gábor Nyúl</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Mohamed Kamel</style></author><author><style face="normal" font="default" size="100%">Aurélio Campilho</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">A Novel Method for Barcode Localization in Image Domain</style></title><secondary-title><style face="normal" font="default" size="100%">Image Analysis and Recognition (ICIAR) </style></secondary-title><tertiary-title><style face="normal" font="default" size="100%">Lecture Notes in Computer Science</style></tertiary-title><alt-title><style face="normal" font="default" size="100%">LNCS</style></alt-title></titles><dates><year><style  face="normal" font="default" size="100%">2013</style></year><pub-dates><date><style  face="normal" font="default" size="100%">June 2013</style></date></pub-dates></dates><publisher><style face="normal" font="default" size="100%">Springer-Verlag</style></publisher><pub-location><style face="normal" font="default" size="100%">Berlin</style></pub-location><pages><style face="normal" font="default" size="100%">189 - 196</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;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.&lt;/p&gt;</style></abstract><work-type><style face="normal" font="default" size="100%">Conference paper</style></work-type><notes><style face="normal" font="default" size="100%">doi: 10.1007/978-3-642-39094-4_22</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Péter Bodnár</style></author><author><style face="normal" font="default" size="100%">László Gábor Nyúl</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">László Czúni</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Vizuális kódok lokalizálásának javítása egyszerű jellemzők kombinációjával</style></title><secondary-title><style face="normal" font="default" size="100%">A Képfeldolgozók és Alakfelismerők Társaságának konferenciája - KÉPAF 2013</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2013</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Jan 2013</style></date></pub-dates></dates><publisher><style face="normal" font="default" size="100%">NJSZT-KÉPAF</style></publisher><pub-location><style face="normal" font="default" size="100%">Veszprém</style></pub-location><pages><style face="normal" font="default" size="100%">483 - 495</style></pages><language><style face="normal" font="default" size="100%">hun</style></language><work-type><style face="normal" font="default" size="100%">Conference paper</style></work-type></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Péter Bodnár</style></author><author><style face="normal" font="default" size="100%">László Gábor Nyúl</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">M Petrou</style></author><author><style face="normal" font="default" size="100%">A D Sappa</style></author><author><style face="normal" font="default" size="100%">A G Triantafyllidis</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Barcode Detection with Morphological Operations and Clustering</style></title><secondary-title><style face="normal" font="default" size="100%">Proceedings of the IASTED International Conference on Signal Processing, Pattern Recognition, and Applications (SPPRA)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2012</style></year><pub-dates><date><style  face="normal" font="default" size="100%">June 2012</style></date></pub-dates></dates><publisher><style face="normal" font="default" size="100%">IASTED - Acta Press</style></publisher><pub-location><style face="normal" font="default" size="100%">Crete, Greek</style></pub-location><pages><style face="normal" font="default" size="100%">51 - 57</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p class=&quot;first_paragraph&quot;&gt;&lt;span id=&quot;lblAbstract&quot;&gt;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.&lt;/span&gt;&lt;/p&gt;</style></abstract><work-type><style face="normal" font="default" size="100%">Conference paper</style></work-type><notes><style face="normal" font="default" size="100%">ScopusID: 84864778306doi: 10.2316/P.2012.778-014</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>13</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Péter Bodnár</style></author><author><style face="normal" font="default" size="100%">László Gábor Nyúl</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Barcode Detection with Uniform Partitioning and Morphological Operations</style></title><secondary-title><style face="normal" font="default" size="100%">Conference of PhD students in computer science. Volume of Extended Abstracts.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2012</style></year><pub-dates><date><style  face="normal" font="default" size="100%">June 2012</style></date></pub-dates></dates><publisher><style face="normal" font="default" size="100%">University of Szeged, Institute of Informatics</style></publisher><pub-location><style face="normal" font="default" size="100%">Szeged</style></pub-location><pages><style face="normal" font="default" size="100%">4 - 5</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><work-type><style face="normal" font="default" size="100%">Abstract</style></work-type></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Péter Bodnár</style></author><author><style face="normal" font="default" size="100%">László Gábor Nyúl</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Kokou Yetongnon</style></author><author><style face="normal" font="default" size="100%">Richard Chbeir</style></author><author><style face="normal" font="default" size="100%">Albert Dipanda</style></author><author><style face="normal" font="default" size="100%">Luigi Gallo</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Improving barcode detection with combination of simple detectors</style></title><secondary-title><style face="normal" font="default" size="100%">Proceedings of the International Conference on Signal Image Technology &amp; Internet Systems (SITIS)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2012</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Nov 2012</style></date></pub-dates></dates><publisher><style face="normal" font="default" size="100%">IEEE</style></publisher><pub-location><style face="normal" font="default" size="100%">Naples, Italy</style></pub-location><pages><style face="normal" font="default" size="100%">300 - 306</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;div class=&quot;article&quot;&gt;&lt;p&gt;&lt;span class=&quot;snippet&quot;&gt;Barcode&lt;/span&gt; &lt;span class=&quot;snippet&quot;&gt;detection&lt;/span&gt; is required in a wide range of real-life applications. Imaging conditions and techniques vary considerably and each application has its own requirements for &lt;span class=&quot;snippet&quot;&gt;detection&lt;/span&gt; speed and accuracy. In our earlier works we built &lt;span class=&quot;snippet&quot;&gt;barcode&lt;/span&gt; &lt;span class=&quot;snippet&quot;&gt;detectors&lt;/span&gt; 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 &lt;span class=&quot;snippet&quot;&gt;simple&lt;/span&gt; &lt;span class=&quot;snippet&quot;&gt;detectors&lt;/span&gt; using various aggregation methods. Using a &lt;span class=&quot;snippet&quot;&gt;combination&lt;/span&gt; of several &lt;span class=&quot;snippet&quot;&gt;simple&lt;/span&gt; features localization performance &lt;span class=&quot;snippet&quot;&gt;improves&lt;/span&gt; significantly.&lt;/p&gt;&lt;/div&gt;&lt;p&gt;&amp;nbsp;&lt;/p&gt;</style></abstract><work-type><style face="normal" font="default" size="100%">Conference paper</style></work-type><accession-num><style face="normal" font="default" size="100%">13227628 </style></accession-num><notes><style face="normal" font="default" size="100%">ScopusID: 84874080233doi: 10.1109/SITIS.2012.52</style></notes></record></records></xml>