<?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%">Attila Tanacs</style></author><author><style face="normal" font="default" size="100%">Joakim Lindbald</style></author><author><style face="normal" font="default" size="100%">Nataša Sladoje</style></author><author><style face="normal" font="default" size="100%">Zoltan Kato</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Estimation of linear deformations of 2D and 3D fuzzy objects</style></title><secondary-title><style face="normal" font="default" size="100%">PATTERN RECOGNITION</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%">Apr 2015</style></date></pub-dates></dates><publisher><style face="normal" font="default" size="100%">Elsevier</style></publisher><volume><style face="normal" font="default" size="100%">48</style></volume><pages><style face="normal" font="default" size="100%">1387-1399</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p id=&quot;sp0080&quot;&gt;Registration is a fundamental task in image processing, it is used to determine geometric correspondences between images taken at different times and/or from different viewpoints. Here we propose a general framework in &lt;em&gt;n&lt;/em&gt;-dimensions to solve binary shape/object matching problems without the need of establishing additional point or other type of correspondences. The approach is based on generating and solving polynomial systems of equations. We also propose an extension which, provided that a suitable segmentation method can produce a fuzzy border representation, further increases the registration precision. Via numerous synthetic and real test we examine the different solution techniques of the polynomial systems of equations. We take into account a direct analytical, an iterative least-squares, and a combined method. Iterative and combined approaches produce the most precise results. Comparison is made against competing methods for rigid-body problems. Our method is orders of magnitude faster and is able to recover alignment regardless of the magnitude of the deformation compared to the narrow capture range of others. The applicability of the proposed methods is demonstrated on real X-ray images of hip replacement implants and 3D CT volumes of the pelvic area. Since the images must be parsed through only once, our approach is especially suitable for solving registration problems of large images.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">4</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%">Attila Tanacs</style></author><author><style face="normal" font="default" size="100%">Joakim Lindblad</style></author><author><style face="normal" font="default" size="100%">Nataša Sladoje</style></author><author><style face="normal" font="default" size="100%">Zoltan Kato</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%">2D és 3D bináris objektumok lineáris deformáció-becslésének numerikus megoldási lehetőségei</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%">526 - 541</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%">Attila Tanacs</style></author><author><style face="normal" font="default" size="100%">Joakim Lindblad</style></author><author><style face="normal" font="default" size="100%">Nataša Sladoje</style></author><author><style face="normal" font="default" size="100%">Zoltan Kato</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Zoltan Kato</style></author><author><style face="normal" font="default" size="100%">Kálmán Palágyi</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">3D objektumok lineáris deformációinak becslése</style></title><secondary-title><style face="normal" font="default" size="100%">A Képfeldolgozók és Alakfelismerők Társaságának konferenciája - KÉPAF 2011</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2011</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Jan 2011</style></date></pub-dates></dates><publisher><style face="normal" font="default" size="100%">NJSZT</style></publisher><pub-location><style face="normal" font="default" size="100%">Szeged</style></pub-location><pages><style face="normal" font="default" size="100%">471 - 480</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>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Attila Tanacs</style></author><author><style face="normal" font="default" size="100%">Joakim Lindblad</style></author><author><style face="normal" font="default" size="100%">Nataša Sladoje</style></author><author><style face="normal" font="default" size="100%">Zoltan Kato</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Estimation of linear deformations of 3D objects</style></title><secondary-title><style face="normal" font="default" size="100%">IEEE International Conference on Image Processing (ICIP)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2010</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Sep 2010</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%">Hong Kong, Hong Kong</style></pub-location><pages><style face="normal" font="default" size="100%">153 - 156</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;We propose a registration method to find affine transformations between 3D objects by constructing and solving an overdetermined system of polynomial equations. We utilize voxel coverage information for more precise object boundary description. An iterative solution enables us to easily adjust the method to recover e.g. rigid-body and similarity transformations. Synthetic tests show the advantage of the voxel coverage representation, and reveal the robustness properties of our method against different types of segmentation errors. The method is tested on a real medical CT volume. © 2010 IEEE.&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%">UT: 000287728000038ScopusID: 78651064516doi: 10.1109/ICIP.2010.5650932</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%">Attila Tanacs</style></author><author><style face="normal" font="default" size="100%">Csaba Domokos</style></author><author><style face="normal" font="default" size="100%">Nataša Sladoje</style></author><author><style face="normal" font="default" size="100%">Joakim Lindblad</style></author><author><style face="normal" font="default" size="100%">Zoltan Kato</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Arnt-Borre Salberg</style></author><author><style face="normal" font="default" size="100%">Jon Yngve Hardeberg</style></author><author><style face="normal" font="default" size="100%">Robert Jenssen</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Recovering affine deformations of fuzzy shapes</style></title><secondary-title><style face="normal" font="default" size="100%">Image Analysis</style></secondary-title><tertiary-title><style face="normal" font="default" size="100%">Lecture Notes in Computer Science</style></tertiary-title><short-title><style face="normal" font="default" size="100%">LNCS</style></short-title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year><pub-dates><date><style  face="normal" font="default" size="100%">June 2009</style></date></pub-dates></dates><number><style face="normal" font="default" size="100%">5575</style></number><publisher><style face="normal" font="default" size="100%">Springer-Verlag</style></publisher><pub-location><style face="normal" font="default" size="100%">Oslo, Norway</style></pub-location><pages><style face="normal" font="default" size="100%">735 - 744</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Fuzzy sets and fuzzy techniques are attracting increasing attention nowadays in the field of image processing and analysis. It has been shown that the information preserved by using fuzzy representation based on area coverage may be successfully utilized to improve precision and accuracy of several shape descriptors; geometric moments of a shape are among them. We propose to extend an existing binary shape matching method to take advantage of fuzzy object representation. The result of a synthetic test show that fuzzy representation yields smaller registration errors in average. A segmentation method is also presented to generate fuzzy segmentations of real images. The applicability of the proposed methods is demonstrated on real X-ray images of hip replacement implants. © 2009 Springer Berlin Heidelberg.&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%">UT: 000268661000075ScopusID: 70350676212doi: 10.1007/978-3-642-02230-2_75</style></notes></record></records></xml>