<?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%">László Gábor Nyúl</style></author><author><style face="normal" font="default" size="100%">Antal Nagy</style></author><author><style face="normal" font="default" size="100%">Péter Balázs</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Martin Kampel</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Local uncertainty in binary tomographic reconstruction</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 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%">Feb 2013</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%">Calgary</style></pub-location><pages><style face="normal" font="default" size="100%">490 - 496</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 describe a new approach for the uncertainty problem arisingin the field of discrete tomography, when the low number of projections does not hold enough information for an accurate, and reliable reconstruction. In this case the lack of information results in uncertain parts on the reconstructed image which are not determined by the projections and cannot be reliably reconstructed without additional information. We provide a method that can approximate this local uncertainty of reconstructions, and show how each pixel of the reconstructed image is determined by a set of given projections. We also give experimental results for validating our approach.&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: 84876584488doi: 10.2316/P.2013.798-067</style></notes></record></records></xml>