<?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%">Jozsef Nemeth</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%">Jacques Blanc-Talon</style></author><author><style face="normal" font="default" size="100%">Andrzej Kasinski</style></author><author><style face="normal" font="default" size="100%">Wilfried Philips</style></author><author><style face="normal" font="default" size="100%">Dan Popescu</style></author><author><style face="normal" font="default" size="100%">Paul Scheunders</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Restoration of blurred binary images using discrete tomography</style></title><secondary-title><style face="normal" font="default" size="100%">Advanced Concepts for Intelligent Vision Systems (ACIVS)</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><short-title><style face="normal" font="default" size="100%">LNCS</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><number><style face="normal" font="default" size="100%">8192</style></number><publisher><style face="normal" font="default" size="100%">Springer Verlag</style></publisher><pub-location><style face="normal" font="default" size="100%">Berlin; Heidelberg; New York; London; Paris; Tokyo</style></pub-location><pages><style face="normal" font="default" size="100%">80 - 90</style></pages><isbn><style face="normal" font="default" size="100%">978-3-319-02894-1</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;Enhancement of degraded images of binary shapes is an important task in many image processing applications, &lt;em class=&quot;a-plus-plus&quot;&gt;e.g.&lt;/em&gt; to provide appropriate image quality for optical character recognition. Although many image restoration methods can be found in the literature, most of them are developed for grayscale images. In this paper we propose a novel binary image restoration algorithm. As a first step, it restores the projections of the shape using 1-dimensional deconvolution, then reconstructs the image from these projections using a discrete tomography technique. The method does not require any parameter setting or prior knowledge like an estimation of the signal-to-noise ratio. Numerical experiments on a synthetic dataset show that the proposed algorithm is robust to the level of the noise. The efficiency of the method has also been demonstrated on real out-of-focus alphanumeric images.&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%">ScopusID: 84890864720doi: 10.1007/978-3-319-02895-8_8</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%">Kálmán Palágyi</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Jacques Blanc-Talon</style></author><author><style face="normal" font="default" size="100%">Wilfried Philips</style></author><author><style face="normal" font="default" size="100%">Dan Popescu</style></author><author><style face="normal" font="default" size="100%">Paul Scheunders</style></author><author><style face="normal" font="default" size="100%">Pavel Zemčík</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">3D Parallel Thinning Algorithms Based on Isthmuses</style></title><secondary-title><style face="normal" font="default" size="100%">Advanced Concepts for Intelligent Vision Systems (ACIVS)</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><short-title><style face="normal" font="default" size="100%">Conference Paper</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%">Sep 2012</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1007/978-3-642-33140-4_29</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">Springer Verlag</style></publisher><pub-location><style face="normal" font="default" size="100%">Brno, Czech Republic</style></pub-location><volume><style face="normal" font="default" size="100%">7517</style></volume><pages><style face="normal" font="default" size="100%">325 - 335</style></pages><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 widely used technique to obtain skeleton-like shape features (i.e., centerlines and medial surfaces) from digital binary objects. Conventional thinning algorithms preserve endpoints to provide important geometric information relative to the object to be represented. An alternative strategy is also proposed that preserves isthmuses (i.e., generalization of curve/surface interior points). In this paper we present ten 3D parallel isthmus-based thinning algorithm variants that are derived from some sufficient conditions for topology preserving reductions. &lt;tt&gt; &lt;/tt&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%">N1 10.1007/978-3-642-33140-4_29</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%">Jozsef Nemeth</style></author><author><style face="normal" font="default" size="100%">Zoltan Kato</style></author><author><style face="normal" font="default" size="100%">Ian Jermyn</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Jacques Blanc-Talon</style></author><author><style face="normal" font="default" size="100%">Wilfried Philips</style></author><author><style face="normal" font="default" size="100%">Dan Popescu</style></author><author><style face="normal" font="default" size="100%">Paul Scheunders</style></author><author><style face="normal" font="default" size="100%">Richard Kleihorst</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">A Multi-Layer 'Gas of Circles' Markov Random Field Model for the Extraction of Overlapping Near-Circular Objects</style></title><secondary-title><style face="normal" font="default" size="100%">Advances Concepts for Intelligent Vision Systems (ACIVS)</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%">2011</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Aug 2011</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.inf.u-szeged.hu/ipcg/publications/Year/2011.complete.xml#Nemeth-etal2011</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">6915</style></number><publisher><style face="normal" font="default" size="100%">Springer-Verlag</style></publisher><pub-location><style face="normal" font="default" size="100%">Ghent, Belgium</style></pub-location><pages><style face="normal" font="default" size="100%">171 - 182</style></pages><isbn><style face="normal" font="default" size="100%">978-3-642-23686-0</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 propose a multi-layer binary Markov random field (MRF) model that assigns high probability to object configurations in the image domain consisting of an unknown number of possibly touching or overlapping near-circular objects of approximately a given size. Each layer has an associated binary field that specifies a region corresponding to objects. Overlapping objects are represented by regions in different layers. Within each layer, long-range interactions favor connected components of approximately circular shape, while regions in different layers that overlap are penalized. Used as a prior coupled with a suitable data likelihood, the model can be used for object extraction from images, e.g. cells in biological images or densely-packed tree crowns in remote sensing images. We present a theoretical and experimental analysis of the model, and demonstrate its performance on various synthetic and biomedical images.&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: 000306962700016</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%">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%">Jacques Blanc-Talon</style></author><author><style face="normal" font="default" size="100%">Don Bone</style></author><author><style face="normal" font="default" size="100%">Wilfried Philips</style></author><author><style face="normal" font="default" size="100%">Dan Popescu</style></author><author><style face="normal" font="default" size="100%">Paul Scheunders</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Projection selection algorithms for discrete tomography</style></title><secondary-title><style face="normal" font="default" size="100%">Advanced Concepts for Intelligent Vision Systems</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%">Dec 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%">Sydney, Australia </style></pub-location><pages><style face="normal" font="default" size="100%">390 - 401</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%">UT: 000287941400037ScopusID: 78650892305doi: 10.1007/978-3-642-17688-3_37</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%">Peter Horvath</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Wilfried Philips</style></author><author><style face="normal" font="default" size="100%">Dan Popescu</style></author><author><style face="normal" font="default" size="100%">Paul Scheunders</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">A Multispectral Data Model for Higher-Order Active Contours and its Application to Tree Crown Extraction</style></title><secondary-title><style face="normal" font="default" size="100%">Proceedings of the Advanced Concepts for Intelligent Vision Systems (ACIVS)</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%">2007</style></date></pub-dates></dates><pub-location><style face="normal" font="default" size="100%">Delft, Netherlands</style></pub-location><volume><style face="normal" font="default" size="100%">4678</style></volume><pages><style face="normal" font="default" size="100%">200-211</style></pages><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 Nyúl</style></author><author><style face="normal" font="default" size="100%">Judit Kanyó</style></author><author><style face="normal" font="default" size="100%">Eörs Máté</style></author><author><style face="normal" font="default" size="100%">Géza Makay</style></author><author><style face="normal" font="default" size="100%">Emese Balogh</style></author><author><style face="normal" font="default" size="100%">Márta Fidrich</style></author><author><style face="normal" font="default" size="100%">Attila Kuba</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">André Gagalowitz</style></author><author><style face="normal" font="default" size="100%">Wilfried Philips</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Method for automatically segmenting the spinal cord and canal from 3D CT images</style></title><secondary-title><style face="normal" font="default" size="100%">Computer Analysis of Images and Patterns</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2005</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2005</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; Heidelberg</style></pub-location><pages><style face="normal" font="default" size="100%">456 - 463</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><notes><style face="normal" font="default" size="100%">UT: 000232301200056</style></notes></record></records></xml>