<?xml version="1.0" encoding="UTF-8"?><xml><records><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%">László Gábor Varga</style></author><author><style face="normal" font="default" size="100%">Péter Balázs</style></author><author><style face="normal" font="default" size="100%">Antal Nagy</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Paolo Di Giamberardino</style></author><author><style face="normal" font="default" size="100%">Daniela Iacoviello</style></author><author><style face="normal" font="default" size="100%">Renato M Natal Jorge</style></author><author><style face="normal" font="default" size="100%">Joao Manuel R S Taveres</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">An energy minimization reconstruction algorithm for multivalued discrete tomography</style></title><secondary-title><style face="normal" font="default" size="100%">Computational Modelling of Objects Represented in Images: Fundamentals, Methods and Applications III</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%">2012</style></date></pub-dates></dates><publisher><style face="normal" font="default" size="100%">CRC Press - Taylor and Frances Group</style></publisher><pub-location><style face="normal" font="default" size="100%">London</style></pub-location><pages><style face="normal" font="default" size="100%">179 - 185</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 new algorithm for multivalued discrete tomography, that reconstructs images from few projections by approximating the minimum of a suitably constructed energy function with a deterministic optimization method. We also compare the proposed algorithm to other reconstruction techniques on software phantom images, in order to prove its applicability.&lt;/p&gt;</style></abstract><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 Kardos</style></author><author><style face="normal" font="default" size="100%">Kálmán Palágyi</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Paolo Di Giamberardino</style></author><author><style face="normal" font="default" size="100%">Daniela Iacoviello</style></author><author><style face="normal" font="default" size="100%">Renato M Natal Jorge</style></author><author><style face="normal" font="default" size="100%">Joao Manuel R S Taveres</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Hexagonal parallel thinning algorithms based on sufficient conditions for topology preservation</style></title><secondary-title><style face="normal" font="default" size="100%">Computational Modelling of Objects Represented in Images: Fundamentals, Methods and Applications III</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%">2012</style></date></pub-dates></dates><publisher><style face="normal" font="default" size="100%">CRC Press - Taylor and Frances Group</style></publisher><pub-location><style face="normal" font="default" size="100%">London</style></pub-location><pages><style face="normal" font="default" size="100%">63 - 68</style></pages><isbn><style face="normal" font="default" size="100%">978-0-415-62134-2</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Thinning is a well-known technique for producing skeleton-like shape features from digital&lt;br&gt;binary objects in a topology preserving way. Most of the existing thinning algorithms presuppose that the input&lt;br&gt;images are sampled on orthogonal grids.This paper presents new sufficient conditions for topology preserving&lt;br&gt;reductions working on hexagonal grids (or triangular lattices) and eight new 2D hexagonal parallel thinning&lt;br&gt;algorithms that are based on our conditions.The proposed algorithms are capable of producing both medial lines&lt;br&gt;and topological kernels as well.&lt;/p&gt;</style></abstract><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%">László Gábor Varga</style></author><author><style face="normal" font="default" size="100%">Péter Balázs</style></author><author><style face="normal" font="default" size="100%">Antal Nagy</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Reneta P Barneva</style></author><author><style face="normal" font="default" size="100%">Valentin E Brimkov</style></author><author><style face="normal" font="default" size="100%">Herbert A Hauptman</style></author><author><style face="normal" font="default" size="100%">Renato M Natal Jorge</style></author><author><style face="normal" font="default" size="100%">João Manuel R S Tavares</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Direction-dependency of a binary tomographic reconstruction algorithm</style></title><secondary-title><style face="normal" font="default" size="100%">Computational Modeling of Objects Represented in Images</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%">May 2010</style></date></pub-dates></dates><number><style face="normal" font="default" size="100%">6026</style></number><publisher><style face="normal" font="default" size="100%">Springer Verlag</style></publisher><pub-location><style face="normal" font="default" size="100%">Buffalo, NY, USA</style></pub-location><pages><style face="normal" font="default" size="100%">242 - 253</style></pages><isbn><style face="normal" font="default" size="100%">978-3-642-12711-3</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;abstract-content formatted&quot; itemprop=&quot;description&quot;&gt;&lt;p class=&quot;a-plus-plus&quot;&gt;We study how the quality of an image reconstructed by a binary tomographic algorithm depends on the direction of the observed object in the scanner, if only a few projections are available. To do so we conduct experiments on a set of software phantoms by reconstructing them form different projection sets using an algorithm based on D.C. programming (a method for minimizing the difference of convex functions), and compare the accuracy of the corresponding reconstructions by two suitable approaches. Based on the experiments, we discuss consequences on applications arising from the field of non-destructive testing, as well.&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><notes><style face="normal" font="default" size="100%">UT: 000279020400022ScopusID: 77952365308doi: 10.1007/978-3-642-12712-0_22</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%">Gábor Németh</style></author><author><style face="normal" font="default" size="100%">Péter Kardos</style></author><author><style face="normal" font="default" size="100%">Kálmán Palágyi</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Reneta P Barneva</style></author><author><style face="normal" font="default" size="100%">Valentin E Brimkov</style></author><author><style face="normal" font="default" size="100%">Herbert A Hauptman</style></author><author><style face="normal" font="default" size="100%">Renato M Natal Jorge</style></author><author><style face="normal" font="default" size="100%">João Manuel R S Tavares</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Topology Preserving Parallel Smoothing for 3D Binary Images</style></title><secondary-title><style face="normal" font="default" size="100%">Proceedings of the Computational Modeling of Objects Represented in Images (CMORI)</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%">May 2010</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%">Buffalo, USA</style></pub-location><volume><style face="normal" font="default" size="100%">6026</style></volume><pages><style face="normal" font="default" size="100%">287 - 298</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;This paper presents a new algorithm for smoothing 3D binary images in a topology preserving way. Our algorithm is a reduction operator: some border points that are considered as extremities are removed. The proposed method is composed of two parallel reduction operators. We are to apply our smoothing algorithm as an iteration-by-iteration pruning for reducing the noise sensitivity of 3D parallel surface-thinning algorithms. An efficient implementation of our algorithm is sketched and its topological correctness for (26,6) pictures is proved. © 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%">ScopusID: 77952401887doi: 10.1007/978-3-642-12712-0_26</style></notes></record></records></xml>