<?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%">Csaba Domokos</style></author><author><style face="normal" font="default" size="100%">Jozsef Nemeth</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%">Nonlinear Shape Registration without Correspondences</style></title><secondary-title><style face="normal" font="default" size="100%">IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE</style></secondary-title><short-title><style face="normal" font="default" size="100%">IEEE T PATTERN ANAL</style></short-title></titles><dates><year><style  face="normal" font="default" size="100%">2012</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2012</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.inf.u-szeged.hu/~kato/papers/TPAMI-2010-03-0146.R2_Kato.pdf</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">IEEE</style></publisher><volume><style face="normal" font="default" size="100%">34</style></volume><pages><style face="normal" font="default" size="100%">943 - 958</style></pages><isbn><style face="normal" font="default" size="100%">0162-8828</style></isbn><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;In this paper, we propose a novel framework to estimate the parameters of a diffeomorphism that aligns a known &lt;span class=&quot;snippet&quot;&gt;shape&lt;/span&gt; and its distorted observation. Classical &lt;span class=&quot;snippet&quot;&gt;registration&lt;/span&gt; methods first establish &lt;span class=&quot;snippet&quot;&gt;correspondences&lt;/span&gt; between the &lt;span class=&quot;snippet&quot;&gt;shapes&lt;/span&gt; and then compute the transformation parameters from these landmarks. Herein, we trace back the problem to the solution of a system of &lt;span class=&quot;snippet&quot;&gt;nonlinear&lt;/span&gt; equations which directly gives the parameters of the aligning transformation. The proposed method provides a generic framework to recover any diffeomorphic deformation &lt;span class=&quot;snippet&quot;&gt;without&lt;/span&gt; established &lt;span class=&quot;snippet&quot;&gt;correspondences&lt;/span&gt;. It is easy to implement, not sensitive to the strength of the deformation, and robust against segmentation errors. The method has been applied to several commonly used transformation models. The performance of the proposed framework has been demonstrated on large synthetic data sets as well as in the context of various applications.&lt;/p&gt;&lt;/div&gt;&lt;p&gt;&amp;nbsp;&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">5</style></issue><work-type><style face="normal" font="default" size="100%">Journal article</style></work-type><accession-num><style face="normal" font="default" size="100%">12617610 </style></accession-num><notes><style face="normal" font="default" size="100%">UT: 000301747400009doi: 10.1109/TPAMI.2011.200</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%">Csaba Domokos</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%">Jan-Olof Eklundh</style></author><author><style face="normal" font="default" size="100%">Yuichi Ohta</style></author><author><style face="normal" font="default" size="100%">Steven Tanimoto</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Simultaneous Affine Registration of Multiple Shapes</style></title><secondary-title><style face="normal" font="default" size="100%">International Conference on Pattern Recognition (ICPR)</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%">Tsukuba, Japan</style></pub-location><pages><style face="normal" font="default" size="100%">9 - 12</style></pages><isbn><style face="normal" font="default" size="100%">978-1-4673-2216-4 </style></isbn><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;The problem of simultaneously estimating &lt;span class=&quot;snippet&quot;&gt;affine&lt;/span&gt; deformations between &lt;span class=&quot;snippet&quot;&gt;multiple&lt;/span&gt; objects occur in many applications. Herein, a direct method is proposed which provides the result as a solution of a linear system of equations without establishing correspondences between the objects. The key idea is to construct enough linearly independent equations using covariant functions, and then finding the solution simultaneously for all &lt;span class=&quot;snippet&quot;&gt;affine&lt;/span&gt; transformations. Quantitative evaluation confirms the performance of the method.&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%">13324478 </style></accession-num></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%">Csaba Domokos</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%">Affin Puzzle: Deformált objektumdarabok helyreállítása megfeleltetések nélkül</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><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.inf.u-szeged.hu/kepaf2011/pdfs/S05_03.pdf</style></url></web-urls></urls><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%">206 - 220</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><notes><style face="normal" font="default" size="100%">Kuba Attila Díjas cikk.</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>9</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Zoltán Kornél Török</style></author><author><style face="normal" font="default" size="100%">Csaba Domokos</style></author><author><style face="normal" font="default" size="100%">Jozsef Nemeth</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%">Nonlinear Shape Registration without Correspondences</style></title></titles><dates><year><style  face="normal" font="default" size="100%">2011</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2011///</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.inf.u-szeged.hu/~kato/software/planarhombinregdemo.html</style></url></web-urls></urls><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;This is the sample implementation and benchmark dataset of the nonlinear registration of 2D shapes described in the following papers: Csaba Domokos, Jozsef Nemeth, and Zoltan Kato. Nonlinear Shape Registration without Correspondences. IEEE Transactions on Pattern Analysis and Machine Intelligence, 34(5):943--958, May 2012. Note that the current demo program implements only planar homography deformations. Other deformations can be easily implemented based on the demo code.&lt;/p&gt;</style></abstract><work-type><style face="normal" font="default" size="100%">Software</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%">Csaba Domokos</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%">Kostas Daniilidis</style></author><author><style face="normal" font="default" size="100%">Petros Maragos</style></author><author><style face="normal" font="default" size="100%">Nikos Paragios</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Affine puzzle: Realigning deformed object fragments without correspondences</style></title><secondary-title><style face="normal" font="default" size="100%">European Conference on Computer Vision (ECCV)</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%">2010</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Sep 2010</style></date></pub-dates></dates><number><style face="normal" font="default" size="100%">6312</style></number><publisher><style face="normal" font="default" size="100%">Springer</style></publisher><pub-location><style face="normal" font="default" size="100%">Crete, Greece</style></pub-location><pages><style face="normal" font="default" size="100%">777 - 790</style></pages><isbn><style face="normal" font="default" size="100%">978-3-642-15551-2</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;This paper is addressing the problem of realigning broken objects without correspondences. We consider linear transformations between the object fragments and present the method through 2D and 3D affine transformations. The basic idea is to construct and solve a polynomial system of equations which provides the unknown parameters of the alignment. We have quantitatively evaluated the proposed algorithm on a large synthetic dataset containing 2D and 3D images. The results show that the method performs well and robust against segmentation errors. We also present experiments on 2D real images as well as on volumetric medical images applied to surgical planning. © 2010 Springer-Verlag.&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: 000286164000056ScopusID: 78149337447doi: 10.1007/978-3-642-15552-9_56</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%">Csaba Domokos</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%">Parametric estimation of affine deformations of planar shapes</style></title><secondary-title><style face="normal" font="default" size="100%">PATTERN RECOGNITION</style></secondary-title><short-title><style face="normal" font="default" size="100%">PATTERN RECOGN</style></short-title></titles><dates><year><style  face="normal" font="default" size="100%">2010</style></year><pub-dates><date><style  face="normal" font="default" size="100%">March 2010</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">43</style></volume><pages><style face="normal" font="default" size="100%">569 - 578</style></pages><isbn><style face="normal" font="default" size="100%">0031-3203</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><issue><style face="normal" font="default" size="100%">3</style></issue><work-type><style face="normal" font="default" size="100%">Journal article</style></work-type><notes><style face="normal" font="default" size="100%">UT: 000273094100003doi: 10.1016/j.patcog.2009.08.013</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%">Csaba Domokos</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%">Affine alignment of compound objects: A direct approach</style></title><secondary-title><style face="normal" font="default" size="100%">16th IEEE International Conference on Image Processing (ICIP), 2009</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Nov 2009</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%">Cairo, Egypt</style></pub-location><pages><style face="normal" font="default" size="100%">169 - 172</style></pages><isbn><style face="normal" font="default" size="100%">978-1-4244-5653-6 </style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;A direct approach for parametric estimation of 2D affine deformations between compound shapes is proposed. It provides the result as a least-square solution of a linear system of equations. The basic idea is to fit Gaussian densities over the objects yielding covariant functions, which preserves the effect of the unknown transformation. Based on these functions, linear equations are constructed by integrating nonlinear functions over appropriate domains. The main advantages are: linear complexity, easy implementation, works without any time consuming optimization or established correspondences. Comparative tests show that it outperforms state-of-the-art methods both in terms of precision, robustness and complexity. ©2009 IEEE.&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%">11150920</style></accession-num><notes><style face="normal" font="default" size="100%">UT: 000280464300043ScopusID: 77951939917doi: 10.1109/ICIP.2009.5414195</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>9</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Zsolt Katona</style></author><author><style face="normal" font="default" size="100%">Csaba Domokos</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%">Affine Registration of Planar Shapes</style></title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2009///</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.inf.u-szeged.hu/~kato/software/affbinregdemo.html</style></url></web-urls></urls><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;This is the sample implementation and benchmark dataset of the binary image registration algorithm described in the following paper: Csaba Domokos and Zoltan Kato. Parametric Estimation of Affine Deformations of Planar Shapes. Pattern Recognition, 43(3):569--578, March 2010.&lt;/p&gt;</style></abstract></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%">Jozsef Nemeth</style></author><author><style face="normal" font="default" size="100%">Csaba Domokos</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%">Nonlinear registration of binary shapes</style></title><secondary-title><style face="normal" font="default" size="100%">16th IEEE International Conference on Image Processing (ICIP)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Nov 2009</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%">Cairo, Egypt</style></pub-location><pages><style face="normal" font="default" size="100%">1101 - 1104</style></pages><isbn><style face="normal" font="default" size="100%">978-1-4244-5653-6 </style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;A novel approach is proposed to estimate the parameters of a diffeomorphism that aligns two binary images. Classical approaches usually define a cost function based on a similarity metric and then find the solution via optimization. Herein, we trace back the problem to the solution of a system of non-linear equations which directly provides the parameters of the aligning transformation. The proposed method works without any time consuming optimization step or established correspondences. The advantage of our algorithm is that it is easy to implement, less sensitive to the strength of the deformation, and robust against segmentation errors. The efficiency of the proposed approach has been demonstrated on a large synthetic dataset as well as in the context of an industrial application. ©2009 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: 000280464300275ScopusID: 77951946286doi: 10.1109/ICIP.2009.5413468</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><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>5</ref-type><contributors></contributors><titles><title><style face="normal" font="default" size="100%">Recovering planar homographies between 2D shapes</style></title><secondary-title><style face="normal" font="default" size="100%">12th International Conference on Computer Vision, ICCV 2009</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2009///</style></date></pub-dates></dates><publisher><style face="normal" font="default" size="100%">IEEE</style></publisher><pages><style face="normal" font="default" size="100%">2170 - 2176</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Images taken from different views of a planar object are related by planar homography. Recovering the parameters of such transformations is a fundamental problem in computer vision with various applications. This paper proposes a novel method to estimate the parameters of a homography that aligns two binary images. It is obtained by solving a system of nonlinear equations generated by integrating linearly independent functions over the domains determined by the shapes. The advantage of the proposed solution is that it is easy to implement, less sensitive to the strength of the deformation, works without established correspondences and robust against segmentation errors. The method has been tested on synthetic as well as on real images and its efficiency has been demonstrated in the context of two different applications: alignment of hip prosthesis X-ray images and matching of traffic signs. ©2009 IEEE.&lt;/p&gt;</style></abstract><notes><style face="normal" font="default" size="100%">UT: 000294955300280ScopusID: 77953177385doi: 10.1109/ICCV.2009.5459474</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors></contributors><titles><title><style face="normal" font="default" size="100%">Síkbeli alakzatok regisztrációja kovariáns függvények felhasználásával</style></title><secondary-title><style face="normal" font="default" size="100%">A Képfeldolgozók és Alakfelismerők Társaságának konferenciája - KÉPAF 2009</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Jan 2009</style></date></pub-dates></dates><publisher><style face="normal" font="default" size="100%">Akaprint</style></publisher><pub-location><style face="normal" font="default" size="100%">Budapest</style></pub-location><pages><style face="normal" font="default" size="100%">1 - 8</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><work-type><style face="normal" font="default" size="100%">Conference papers</style></work-type></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors></contributors><titles><title><style face="normal" font="default" size="100%">Síkhomográfia paramétereinek becslése bináris képeken</style></title><secondary-title><style face="normal" font="default" size="100%">A Képfeldolgozók és Alakfelismerők Társaságának konferenciája - KÉPAF 2009</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Jan 2009</style></date></pub-dates></dates><publisher><style face="normal" font="default" size="100%">Akaprint</style></publisher><pub-location><style face="normal" font="default" size="100%">Budapest</style></pub-location><pages><style face="normal" font="default" size="100%">1 - 8</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%">Csaba Domokos</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%">Aurélio Campilho</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Binary image registration using covariant gaussian densities</style></title><secondary-title><style face="normal" font="default" size="100%">Image Analysis and Recognition</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%">2008</style></year><pub-dates><date><style  face="normal" font="default" size="100%">June 2008</style></date></pub-dates></dates><number><style face="normal" font="default" size="100%">5112</style></number><publisher><style face="normal" font="default" size="100%">Springer</style></publisher><pub-location><style face="normal" font="default" size="100%">Póvoa de Varzim, Portugal</style></pub-location><pages><style face="normal" font="default" size="100%">455 - 464</style></pages><isbn><style face="normal" font="default" size="100%">978-3-540-69811-1</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;We consider the estimation of 2D affine transformations aligning a known binary shape and its distorted observation. The classical way to solve this registration problem is to find correspondences between the two images and then compute the transformation parameters from these landmarks. In this paper, we propose a novel approach where the exact transformation is obtained as a least-squares solution of a linear system. The basic idea is to fit a Gaussian density to the shapes which preserves the effect of the unknown transformation. It can also be regarded as a consistent coloring of the shapes yielding two rich functions defined over the two shapes to be matched. The advantage of the proposed solution is that it is fast, easy to implement, works without established correspondences and provides a unique and exact solution regardless of the magnitude of transformation. © 2008 Springer-Verlag 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: 000257302500045ScopusID: 47749098390doi: 10.1007/978-3-540-69812-8_45</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%">Csaba Domokos</style></author><author><style face="normal" font="default" size="100%">Zoltan Kato</style></author><author><style face="normal" font="default" size="100%">Joseph M Francos</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Parametric estimation of affine deformations of binary images</style></title><secondary-title><style face="normal" font="default" size="100%">Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2008</style></year><pub-dates><date><style  face="normal" font="default" size="100%">March 2008</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%">Las Vegas, NV, USA</style></pub-location><pages><style face="normal" font="default" size="100%">889 - 892</style></pages><isbn><style face="normal" font="default" size="100%">978-1-4244-1483-3 </style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;We consider the problem of planar object registration on binary images where the aligning transformation is restricted to the group of affine transformations. Previous approaches usually require established correspondences or the solution of nonlinear optimization problems. Herein we show that it is possible to formulate the problem as the solution of a system of up to third order polynomial equations. These equations are constructed in a simple way using some basic geometric information of binary images. It does not need established correspondences nor the solution of complex optimization problems. The resulting algorithm is fast and provides a direct solution regardless of the magnitude of transformation. ©2008 IEEE.&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%">9973096 </style></accession-num><notes><style face="normal" font="default" size="100%">UT: 000257456700223ScopusID: 51449098982doi: 10.1109/ICASSP.2008.4517753</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors></contributors><titles><title><style face="normal" font="default" size="100%">Parametric Estimation of Two-Dimensional Affine Transformations of Binary Images</style></title><secondary-title><style face="normal" font="default" size="100%">A Képfeldolgozók és Alakfelismerők Társaságának konferenciája - KÉPAF 2007</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2007</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Jan 2007</style></date></pub-dates></dates><publisher><style face="normal" font="default" size="100%">Képfeldolgozók és Alakfelismerők Társasága</style></publisher><pub-location><style face="normal" font="default" size="100%">Debrecen</style></pub-location><pages><style face="normal" font="default" size="100%">257 - 265</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></records></xml>