Chlamydiae are obligate intracellular bacteria that propagate in the inclusion, a specific niche inside the host cell. The standard method for counting chlamydiae is the immunofluorescent staining and manual counting of chlamydial inclusions. High or medium throughput estimation of the reduction in chlamydia inclusions should be the basis of testing antichlamydial compounds and other drugs that positively or negatively influence chlamydial growth, yet low-throughput manual counting is the common approach. To overcome the time-consuming and subjective manual counting we developed an automatic inclusion counting system based on a commercially available DNA chip scanner. Fluorescently labeled inclusions are detected by the scanner, and the image is processed by ChlamyCount, a custom plugin of the ImageJ software environment. ChlamyCount was able to measure the inclusion counts over a one log dynamic range with high correlation to the theoretical counts. ChlamyCount was capable of accurately determining the minimum inhibitory concentration of the novel antimicrobial compound PCC00213 and the already known antichlamydial antibiotics moxifloxacin and tetracycline. ChlamyCount was also able to measure the chlamydial growth altering effect of drugs that influence host-bacterium interaction such as interferon-gamma, DEAE-dextran and cycloheximide. ChlamyCount is an easily adaptable system for testing antichlamydial antimicrobials and other compounds that influence Chlamydia-host interactions.

VL - 58 SN - 0066-4804 IS - 1 N1 - UT: 000329581100051ScopusID: 84891513311doi: 10.1128/AAC.01400-13online megjelent 2013 JO - ANTIMICROB AGENTS CH ER - TY - JOUR T1 - Local and global uncertainty in binary tomographic reconstruction JF - COMPUTER VISION AND IMAGE UNDERSTANDING Y1 - 2014 A1 - László Gábor Varga A1 - László Gábor Nyúl A1 - Antal Nagy A1 - Péter Balázs AB -In binary tomography the goal is to reconstruct the innerstructure of homogeneous objects from their projections. This is usually required from a low number of projections, which are also likely to be aﬀected by noise and measurement errors. In general, the distorted and incomplete projection data holds insuﬃcient information for the correct reconstruction of the original object. In this paper, we describe two methods for approximating the local uncertainty of the reconstructions, i.e., identifying how the information stored in the projections determine each part of the reconstructed image. These methods can measure the uncertainty of the reconstruction without any knowledge from the original object itself. Moreover, we provide a global uncertainty measure that can assess the information content of a projection set and predict the error to be expected in the reconstruction of a homogeneous object. We also give an experimental evaluation of our proposed methods, mention some of their possible applications, and describe how the uncertainty measure can be used to improve the performance of the DART reconstruction algorithm.

SN - 1077-3142 N1 - Art. No.: S1077-3142(14)00117-9doi: 10.1016/j.cviu.2014.05.006Article in Press JO - COMPUT VIS IMAGE UND ER - TY - JOUR T1 - APPLICATION OF DNA CHIP SCANNING TECHNOLOGY FOR THE AUTOMATIC DETECTION OF CHLAMYDIA TRACHOMATIS AND CHLAMYDIA PNEUMONIAE INCLUSIONS JF - ACTA MICROBIOLOGICA ET IMMUNOLOGICA HUNGARICA Y1 - 2013 A1 - Ildikó Lantos A1 - Anita Bogdanov A1 - Valéria Endrész A1 - Szabolcs Urbán A1 - Judit Deák A1 - Katalin Burián A1 - K Önder A1 - Péter Balázs A1 - Dezső P Virók VL - 60 SN - 1217-8950 IS - Suppl. 1. N1 - doi: 10.1556/AMicr.60.2013.Suppl.1 JO - ACTA MICROBIOL IMMUNOL HUNG ER - TY - CONF T1 - Bináris képek rekonstrukciója két vetületből és morfológiai vázból T2 - A Képfeldolgozók és Alakfelismerők Társaságának konferenciája - KÉPAF 2013 Y1 - 2013 A1 - Norbert Hantos A1 - Péter Balázs A1 - Kálmán Palágyi ED - László Czúni JF - A Képfeldolgozók és Alakfelismerők Társaságának konferenciája - KÉPAF 2013 PB - NJSZT-KÉPAF CY - Veszprém ER - TY - CONF T1 - A comparison of heuristics for reconstructing hv-convex binary matrices from horizontal and vertical projections T2 - A Képfeldolgozók és Alakfelismerők Társaságának konferenciája - KÉPAF 2013 Y1 - 2013 A1 - Zoltán Ozsvár A1 - Péter Balázs ED - László Czúni JF - A Képfeldolgozók és Alakfelismerők Társaságának konferenciája - KÉPAF 2013 PB - NJSZT-KÉPAF CY - Veszprém ER - TY - JOUR T1 - Complexity results for reconstructing binary images with disjoint components from horizontal and vertical projections JF - DISCRETE APPLIED MATHEMATICS Y1 - 2013 A1 - Péter Balázs VL - 161 SN - 0166-218X N1 - UT: 000322689900002ScopusID: 84874628675doi: 10.1016/j.dam.2013.02.004 JO - DISCRETE APPL MATH ER - TY - CHAP T1 - Directional Convexity Measure for Binary Tomography T2 - Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications Y1 - 2013 A1 - Tamás Sámuel Tasi A1 - László Gábor Nyúl A1 - Péter Balázs ED - Gabriella Sanniti di Baja ED - Jose Ruiz-Shulcloper AB -There is an increasing demand for a new measure of convexity fordiscrete sets for various applications. For example, the well- known measures for h-, v-, and hv-convexity of discrete sets in binary tomography pose rigorous criteria to be satisfied. Currently, there is no commonly accepted, unified view on what type of discrete sets should be considered nearly hv-convex, or to what extent a given discrete set can be considered convex, in case it does not satisfy the strict conditions. We propose a novel directional convexity measure for discrete sets based on various properties of the configuration of 0s and 1s in the set. It can be supported by proper theory, is easy to compute, and according to our experiments, it behaves intuitively. We expect it to become a useful alternative to other convexity measures in situations where the classical definitions cannot be used.

JF - Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications PB - Springer Verlag CY - Berlin; Heidelberg UR - http://link.springer.com/chapter/10.1007%2F978-3-642-41827-3_2 N1 - ScopusID: 84893169866doi: 10.1007/978-3-642-41827-3_2 ER - TY - JOUR T1 - Dynamic angle selection in binary tomography JF - COMPUTER VISION AND IMAGE UNDERSTANDING Y1 - 2013 A1 - Joost K Batenburg A1 - Willem Jan Palenstijn A1 - Péter Balázs A1 - Jan Sijbers AB -In this paper, we present an algorithm for the dynamic selection of projection angles in binary tomography. Based on the information present in projections that have already been measured, a new projection angle is computed, which aims to maximize the information gained by adding this projection to the set of measurements. The optimization model used for angle selection is based on a characterization of solutions of the binary reconstruction problem, and a related definition of information gain. From this formal model, an algorithm is obtained by several approximation steps. Results from a series of simulation experiments demonstrate that the proposed angle selection scheme is indeed capable of finding angles for which the reconstructed image is much more accurate than for the standard angle selection scheme. © 2012 Elsevier Inc. All rights reserved.

VL - 117 SN - 1077-3142 IS - 4 N1 - UT: 000315556800002ScopusID: 84871533054doi: 10.1016/j.cviu.2012.07.005 JO - COMPUT VIS IMAGE UND ER - TY - JOUR T1 - An empirical study of reconstructing hv-convex binary matrices from horizontal and vertical projections JF - ACTA CYBERNETICA-SZEGED Y1 - 2013 A1 - Zoltán Ozsvár A1 - Péter Balázs AB -The reconstruction of hv-convex binary matrices (or equivalently, binary images) from their horizontal and vertical projections is proved to be NP-hard. In this paper we take a closer look at the difficulty of the problem. We investigate different heuristic reconstruction algorithms of the class, and compare them from the viewpoint of running-time and reconstruction quality. Using a large set of test images of different sizes and with varying number of components, we show that the reconstruction quality can depend not only on the size of the image, but on the number and location of its components, too. We also reveal that the reconstruction time can also be affected by the number of the so-called switching components present in the image.

VL - 21 SN - 0324-721X JO - ACTA CYBERN-SZEGED ER - TY - CONF T1 - Gradiens módszerek automatikus súlyozásán alapuló diszkrét tomográfiai eljárás T2 - A Képfeldolgozók és Alakfelismerők Társaságának konferenciája - KÉPAF 2013 Y1 - 2013 A1 - László Gábor Varga A1 - Péter Balázs A1 - Antal Nagy ED - László Czúni JF - A Képfeldolgozók és Alakfelismerők Társaságának konferenciája - KÉPAF 2013 PB - NJSZT-KÉPAF CY - Veszprém ER - TY - CHAP T1 - Local uncertainty in binary tomographic reconstruction T2 - Proceedings of the IASTED International Conference on Signal Processing, Pattern Recognition and Applications (SPPRA 2013) Y1 - 2013 A1 - László Gábor Varga A1 - László Gábor Nyúl A1 - Antal Nagy A1 - Péter Balázs ED - Martin Kampel AB -

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.

JF - Proceedings of the IASTED International Conference on Signal Processing, Pattern Recognition and Applications (SPPRA 2013) PB - IASTED - Acta Press CY - Calgary N1 - ScopusID: 84876584488doi: 10.2316/P.2013.798-067 ER - TY - THES T1 - Prior Information, Machine Learning, and Direction Dependency in Binary Tomography T2 - Institute of Informatics Y1 - 2013 A1 - Péter Balázs JF - Institute of Informatics PB - University of Szeged CY - Szeged, Hungary ER - TY - CHAP T1 - Reconstruction and Enumeration of hv-Convex Polyominoes with Given Horizontal Projection T2 - Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications (CIARP) Y1 - 2013 A1 - Norbert Hantos A1 - Péter Balázs ED - Jose Ruiz-Shulcloper ED - Gabriella Sanniti di Baja JF - Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications (CIARP) T3 - Lecture Notes in Computer Science PB - Springer CY - Heidelberg; London; New York SN - 978-3-642-41821-1 N1 - ScopusID: 84893181366doi: 10.1007/978-3-642-41822-8_13 ER - TY - JOUR T1 - The reconstruction of polyominoes from horizontal and vertical projections and morphological skeleton is NP-complete JF - FUNDAMENTA INFORMATICAE Y1 - 2013 A1 - Norbert Hantos A1 - Péter Balázs VL - 125 SN - 0169-2968 IS - 3-4 N1 - UT: 000322028300009ScopusID: 84881495517doi: 10.3233/FI-2013-868 JO - FUND INFOR ER - TY - CHAP T1 - Restoration of blurred binary images using discrete tomography T2 - Advanced Concepts for Intelligent Vision Systems (ACIVS) Y1 - 2013 A1 - Jozsef Nemeth A1 - Péter Balázs ED - Jacques Blanc-Talon ED - Andrzej Kasinski ED - Wilfried Philips ED - Dan Popescu ED - Paul Scheunders AB -Enhancement of degraded images of binary shapes is an important task in many image processing applications, *e.g.* 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.

JF - Advanced Concepts for Intelligent Vision Systems (ACIVS) T3 - Lecture Notes in Computer Science PB - Springer Verlag CY - Berlin; Heidelberg; New York; London; Paris; Tokyo SN - 978-3-319-02894-1 N1 - ScopusID: 84890864720doi: 10.1007/978-3-319-02895-8_8 JO - LNCS ER - TY - CONF T1 - A uniqueness result for reconstructing hv-convex polyominoes from horizontal and vertical projections and morphological skeleton T2 - Proceedings of International Symposium on Image and Signal Processing and Analysis (ISPA) Y1 - 2013 A1 - Norbert Hantos A1 - Péter Balázs ED - Giovanni Ramponi ED - Sven Lončarić ED - Alberto Carini ED - Karen Egiazarian AB -

In this article we study the uniqueness of the reconstruction in a special class of 4-connected hv-convex images, using two projections and the so-called morphological skeleton. Generally, if just the two projections are given, there can be exponentially many hv-convex 4-connected images satisfying them. Knowing the morphological skeleton in addition, we can reduce the number of solutions. In the studied class, the images are defined by two parameters. We show that the uniqueness of their reconstruction depends only on the values of those parameters.

JF - Proceedings of International Symposium on Image and Signal Processing and Analysis (ISPA) PB - IEEE CY - Trieste ER - TY - Generic T1 - Artificial intelligence methods in discrete tomography Y1 - 2012 A1 - Mihály Gara A1 - Péter Balázs AB -

Tomography is an imaging procedure to examine the internal structure of objects. The crosssection

images are constructed with the aid of the object’s projections. It is often necessary to

minimize the number of those projections to avoid the damage or destruction of the examined

object, since in most cases the projections are made by destructive rays.

Sometimes the number of available projections are so small that conventional methods cannot

provide satisfactory results. In these cases Discrete Tomograpy can provide acceptable solutions,

but it can only be used with the assumption the object is made of only a few materials,

thus only a small number of intensity values appear in the reconstructed cross-section image.

Although there are a lot of discrete tomographic reconstruction algorithms, only a few papers

deal with the determination of intensity values of the image, in advance. In our work we

try to fill this gap by using different learning methods. During the learning and classification

we used the projection values as input arguments.

In the second part of our talk we concentrate on Binary Tomography (a special kind of Discrete

Tomography)where it is supposed that the object is composed of onematerial. Thus, there

can be only two intensities on the cross-section image - one for the object points and one for

the background. Here, we compared our earlier presented binary tomographic evolutionary

reconstruction algorithm to two others. We present the details of the above-mentioned reconstruction

method and our experimental results. This paper is based on our previous works.

In binary tomography, the goal is to reconstruct binary images from a small set of their projections. However, especially when only two projections are used, the task can be extremely underdetermined. In this paper, we show how to reduce ambiguity by using the morphological skeleton of the image as a priori. Three different variants of our method based on Simulated Annealing are tested using artificial binary images, and compared by reconstruction time and error. © 2012 Springer-Verlag.

JF - Combinatorial Image Analysis T3 - Lecture Notes in Computer Science PB - Springer Verlag CY - Berlin; Heidelberg; New York; London; Paris; Tokyo N1 - ScopusID: 84869986820doi: 10.1007/978-3-642-34732-0_20 JO - LNCS ER - TY - CONF T1 - Binary tomography using two projections and morphological skeleton T2 - Conference of PhD Students in Computer Science Y1 - 2012 A1 - Norbert Hantos A1 - Péter Balázs A1 - Kálmán Palágyi JF - Conference of PhD Students in Computer Science PB - Univ Szeged Institute of Informatics CY - Szeged VL - Volume of Extended Abstracts ER - TY - CHAP T1 - A central reconstruction based strategy for selecting projection angles in binary tomography T2 - Image Analysis and Recognition Y1 - 2012 A1 - Péter Balázs A1 - Joost K Batenburg ED - Aurélio Campilho ED - Mohamed Kamel AB -In this paper we propose a novel strategy for selecting projection angles in binary tomography which yields significantly more accurate reconstructions than others. In contrast with previous works which are of experimental nature, the method we present is based on theoretical observations. We report on experiments for different phantom images to show the effectiveness and roboustness of our procedure. The practically important case of noisy projections is also studied. © 2012 Springer-Verlag.

JF - Image Analysis and Recognition T3 - Lecture Notes in Computer Science PB - Springer CY - Berlin; Heidelberg; New York; London; Paris; Tokyo N1 - ScopusID: 84864128031doi: 10.1007/978-3-642-31295-3_45 JO - LNCS ER - TY - CONF T1 - Chlamydia inklúziók automatizált számolása fluoreszcens DNS-chip szkenner segítségével T2 - 11. Cserháti István Emlékülés : Fiatalok Tudományos Fóruma Y1 - 2012 A1 - Anita Bogdanov A1 - Szabolcs Urbán A1 - Valéria Endrész A1 - Katalin Burián A1 - Péter Balázs A1 - Judit Deák A1 - Dezső P Virók ED - Tamás Forster ED - András Farkas ED - Miklós Csanády JF - 11. Cserháti István Emlékülés : Fiatalok Tudományos Fóruma PB - SZTE ÁOK II. sz. Belgyógyászati Klinika és Kardiológiai Központ CY - Szeged ER - TY - Generic T1 - Empirical studies of reconstructing hv-convex binary matrices from horizontal and vertical projections Y1 - 2012 A1 - Zoltán Ozsvár A1 - Péter Balázs JF - Conference of PhD students in computer science. Volume of Extended Abstracts. PB - University of Szeged, Institute of Informatics CY - Szeged ER - TY - CHAP T1 - An energy minimization reconstruction algorithm for multivalued discrete tomography T2 - Computational Modelling of Objects Represented in Images: Fundamentals, Methods and Applications III Y1 - 2012 A1 - László Gábor Varga A1 - Péter Balázs A1 - Antal Nagy ED - Paolo Di Giamberardino ED - Daniela Iacoviello ED - Renato M Natal Jorge ED - Joao Manuel R S Taveres AB -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.

JF - Computational Modelling of Objects Represented in Images: Fundamentals, Methods and Applications III PB - CRC Press - Taylor and Frances Group CY - London ER - TY - Generic T1 - Extracting geometrical features of discrete images from their projections Y1 - 2012 A1 - Tamás Sámuel Tasi A1 - Péter Balázs JF - Conference of PhD students in computer science. Volume of Extended Abstracts. PB - University of Szeged, Institute of Informatics CY - Szeged ER - TY - CHAP T1 - Machine learning as a preprocessing phase in discrete tomography T2 - Applications of Discrete Geometry and Mathematical Morphology (WADGMM) Y1 - 2012 A1 - Mihály Gara A1 - Tamás Sámuel Tasi A1 - Péter Balázs ED - Ullrich Köthe ED - Annick Montanvert ED - Pierre Soille AB -In this paper we investigate for two well-known machine learning methods, decision trees and neural networks, how they classify discrete images from their projections. As an example, we present classification results when the task is to guess the number of intensity values of the discrete image. Machine learning can be used in Discrete Tomography as a preprocessing step in order to choose the proper reconstruction algorithm or - with the aid of the knowledge acquired - to improve its accuracy. We also show how to design new evolutionary reconstruction methods that can exploit the information gained by machine learning classifiers. © 2012 Springer-Verlag.

JF - Applications of Discrete Geometry and Mathematical Morphology (WADGMM) T3 - Lecture Notes in Computer Science PB - Springer Verlag CY - Berlin; Heidelberg; New York; London; Paris; Tokyo N1 - ScopusID: 84865454250doi: 10.1007/978-3-642-32313-3_8 JO - LNCS ER - TY - Generic T1 - A novel optimization-based reconstruction algorithm for multivalued discrete tomography Y1 - 2012 A1 - László Gábor Varga A1 - Péter Balázs A1 - Antal Nagy JF - Conference of PhD students in computer science. Volume of extended abstracts. PB - University of Szeged, Institute of Informatics CY - Szeged ER - TY - CONF T1 - An optimization-based reconstruction algorithm for multivalued discrete tomography T2 - Veszprém Optimization Conference: Advanced Algorithms (Vocal) Y1 - 2012 A1 - László Gábor Varga A1 - Péter Balázs A1 - Antal Nagy JF - Veszprém Optimization Conference: Advanced Algorithms (Vocal) PB - University of Pannonia CY - Veszprém ER - TY - CONF T1 - Perimeter estimation of some discrete sets from horizontal and vertical projections T2 - IASTED International Conference on Signal Processing, Pattern Recognition and Applications (SPPRA) Y1 - 2012 A1 - Tamás Sámuel Tasi A1 - M Hegedűs A1 - Péter Balázs ED - M Petrou ED - A D Sappa ED - A G Triantafyllidis AB -In this paper, we design neural networks to estimate the perimeter of simple and more complex discrete sets from their horizontal and vertical projections. The information extracted this way can be useful to simplify the problem of reconstructing the discrete set from its projections, which task is in focus of discrete tomography. Beside presenting experimental results with neural networks, we also reveal some statistical properties of the perimeter of the studied discrete sets.

JF - IASTED International Conference on Signal Processing, Pattern Recognition and Applications (SPPRA) PB - IASTED ACTA Press CY - Crete, Greek N1 - ScopusID: 84864772360doi: 10.2316/P.2012.778-017 ER - TY - CONF T1 - Solving binary tomography from morphological skeleton via optimization T2 - Veszprém Optimization Conference: Advanced Algorithms (VOCAL) Y1 - 2012 A1 - Norbert Hantos A1 - Péter Balázs A1 - Kálmán Palágyi JF - Veszprém Optimization Conference: Advanced Algorithms (VOCAL) PB - University of Pannonia CY - Veszprém ER - TY - CONF T1 - Bináris tomográfiai rekonstrukció objektum alapú evolúciós algoritmussal T2 - A Képfeldolgozók és Alakfelismerők Társaságának konferenciája - KÉPAF 2011 Y1 - 2011 A1 - Mihály Gara A1 - Péter Balázs ED - Zoltan Kato ED - Kálmán Palágyi JF - A Képfeldolgozók és Alakfelismerők Társaságának konferenciája - KÉPAF 2011 PB - NJSZT CY - Szeged ER - TY - JOUR T1 - Direction-dependency of binary tomographic reconstruction algorithms JF - GRAPHICAL MODELS Y1 - 2011 A1 - László Gábor Varga A1 - Péter Balázs A1 - Antal Nagy AB -In this work we study the relation between the quality of a binary tomographic reconstruction and the choice of angles of the projections. We conduct experiments on a set of software phantoms by reconstructing them from different projection sets using three different discrete tomography reconstruction algorithms, and compare the accuracy of the corresponding reconstructions with suitable approaches. To validate our results for possible real-world applications, we conduct the experiments by adding random noise of different characteristics to the simulated projection data, and by applying small topological changes on the phantom images as well. In addition, we also discuss some consequences of the angle-selection dependency and possible practical applications arising from the field of non-destructive testing, too.

VL - 73 SN - 1524-0703 IS - 6 N1 - UT: 000296999100028ScopusID: 80054709026doi: 10.1016/j.gmod.2011.06.006 JO - GRAPH MODELS ER - TY - BOOK T1 - Képrekonstrukció Y1 - 2011 A1 - Péter Balázs ED - Lehel Juhász PB - Typotex Kiadó CY - Budapest ER - TY - CONF T1 - Mediánszűrés alkalmazása algebrai rekonstrukciós módszerekben T2 - A Képfeldolgozók és Alakfelismerők Társaságának konferenciája - KÉPAF 2011 Y1 - 2011 A1 - Norbert Hantos A1 - Péter Balázs ED - Zoltan Kato ED - Kálmán Palágyi JF - A Képfeldolgozók és Alakfelismerők Társaságának konferenciája - KÉPAF 2011 PB - NJSZT CY - Szeged ER - TY - JOUR T1 - Projection selection dependency in binary tomography JF - ACTA CYBERNETICA-SZEGED Y1 - 2011 A1 - László Gábor Varga A1 - Péter Balázs A1 - Antal Nagy AB -It has already been shown that the choice of projection angles can significantly influence the quality of reconstructions in discrete tomography. In this contribution we summarize and extend the previous results by explaining and demonstrating tile effects of projection selection dependency, in a set of experimental software tests. We perform reconstructions of software phantoms, by using different binary tomography reconstruction algorithms, from different equiangular and non-equiangular projections sets, under various conditions (i.e., when the objects to be reconstructed undergo slight topological changes, or the projection data is affected by noise) and compare the results with suitable approaches. Based on our observations, we reveal regularities in the resulting data and discuss possible consequences of such projection selection dependency in binary tomography.

PB - University of Szeged, Institute of Informatics CY - Szeged VL - 20 SN - 0324-721X IS - 1 N1 - ScopusID: 79960679541 JO - ACTA CYBERN-SZEGED ER - TY - CONF T1 - Tehetséggondozó program a Szegedi Tudományegyetem Informatikai Tanszékcsoport BSc szakjain T2 - Informatika a felsőoktatásban 2011 konferencia Y1 - 2011 A1 - Péter Balázs A1 - Zoltán L Németh ED - László Cser ED - Miklós Herdon JF - Informatika a felsőoktatásban 2011 konferencia PB - Debreceni Egyetem Informatikai Kar CY - Debrecen ER - TY - CONF T1 - Vetületi irányfüggőség a bináris tomográfiában T2 - A Képfeldolgozók és Alakfelismerők Társaságának konferenciája - KÉPAF 2011 Y1 - 2011 A1 - László Gábor Varga A1 - Péter Balázs A1 - Antal Nagy ED - Zoltan Kato ED - Kálmán Palágyi JF - A Képfeldolgozók és Alakfelismerők Társaságának konferenciája - KÉPAF 2011 PB - NJSZT CY - Szeged ER - TY - CONF T1 - Binary tomographic reconstruction with an object-based evolutionary algorithm T2 - Conference of PhD Students in Computer Science. Volume of Extended Abstracts Y1 - 2010 A1 - Mihály Gara A1 - Péter Balázs JF - Conference of PhD Students in Computer Science. Volume of Extended Abstracts PB - University of Szeged CY - Szeged ER - TY - CHAP T1 - Direction-dependency of a binary tomographic reconstruction algorithm T2 - Computational Modeling of Objects Represented in Images Y1 - 2010 A1 - László Gábor Varga A1 - Péter Balázs A1 - Antal Nagy ED - Reneta P Barneva ED - Valentin E Brimkov ED - Herbert A Hauptman ED - Renato M Natal Jorge ED - João Manuel R S Tavares AB -

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.

JF - Computational Modeling of Objects Represented in Images T3 - Lecture Notes in Computer Science PB - Springer Verlag CY - Buffalo, NY, USA SN - 978-3-642-12711-3 N1 - UT: 000279020400022ScopusID: 77952365308doi: 10.1007/978-3-642-12712-0_22 JO - LNCS ER - TY - CHAP T1 - Image enhancement by median filters in algebraic reconstruction methods: an experimental study T2 - Advances in Visual Computing Y1 - 2010 A1 - Norbert Hantos A1 - Péter Balázs ED - George Bebis ED - Richard Boyle ED - Bahram Parvin ED - Darko Koracin ED - Ronald Chung ED - Riad Hammound ED - Muhammad Hussain ED - Tan Kar-Han ED - Roger Crawfis ED - Daniel Thalmann ED - David Kao ED - Lisa Avila AB -

Algebraic methods for image reconstruction provide good solutions even if only few projections are available. However, they can create noisy images if the number of iterations or the computational time is limited. In this paper, we show how to decrease the effect of noise by using median filters during the iterations. We present an extensive study by applying filters of different sizes and in various times of the reconstruction process. Also, our test images are of different structural complexity. Our study concentrates on the ART and its discrete variant DART reconstruction methods.

JF - Advances in Visual Computing T3 - Lecture Notes in Computer Science PB - Springer Verlag CY - Las Vegas, NV, USA SN - 978-3-642-17276-2 N1 - UT: 000290358400035ScopusID: 78650793785doi: 10.1007/978-3-642-17277-9_35 JO - LNCS ER - TY - CHAP T1 - Machine learning for supporting binary tomographic reconstruction T2 - Workshop on Applications of Discrete Geometry in Mathematical Morphology Y1 - 2010 A1 - Péter Balázs A1 - Mihály Gara A1 - Tamás Sámuel Tasi ED - Ullrich Köthe ED - Annick Montanvert ED - Pierre Soille JF - Workshop on Applications of Discrete Geometry in Mathematical Morphology T3 - Lecture Notes in Computer Science PB - Springer CY - Istambul, Turkey JO - LNCS ER - TY - CONF T1 - Median filtering in algebraic reconstruction methods T2 - Conference of PhD Students in Computer Science. Volume of Extended Abstracts. Y1 - 2010 A1 - Norbert Hantos A1 - Péter Balázs JF - Conference of PhD Students in Computer Science. Volume of Extended Abstracts. PB - University of Szeged CY - Szeged, Hungary ER - TY - CONF T1 - Object rotation effects on binary tomographic reconstruction T2 - Conference of PhD Students in Computer Science. Volume of Extended Abstracts Y1 - 2010 A1 - László Gábor Varga A1 - Péter Balázs A1 - Antal Nagy JF - Conference of PhD Students in Computer Science. Volume of Extended Abstracts PB - University of Szeged CY - Szeged, Hungary ER - TY - CONF T1 - Obtaining geometrical properties of binary images from two projections using neural networks T2 - Conference of PhD Students in Computer Science. Volume of Extended Abstracts Y1 - 2010 A1 - Tamás Sámuel Tasi A1 - Péter Balázs JF - Conference of PhD Students in Computer Science. Volume of Extended Abstracts PB - University of Szeged CY - Szeged, Hungary ER - TY - CHAP T1 - Projection selection algorithms for discrete tomography T2 - Advanced Concepts for Intelligent Vision Systems Y1 - 2010 A1 - László Gábor Varga A1 - Péter Balázs A1 - Antal Nagy ED - Jacques Blanc-Talon ED - Don Bone ED - Wilfried Philips ED - Dan Popescu ED - Paul Scheunders JF - Advanced Concepts for Intelligent Vision Systems PB - Springer Verlag CY - Sydney, Australia N1 - UT: 000287941400037ScopusID: 78650892305doi: 10.1007/978-3-642-17688-3_37 ER - TY - JOUR T1 - A benchmark set for the reconstruction of hv-convex discrete sets JF - DISCRETE APPLIED MATHEMATICS Y1 - 2009 A1 - Péter Balázs PB - Elsevier VL - 157 SN - 0166-218X IS - 16 N1 - UT: 000271375400009ScopusID: 70249142878doi: 10.1016/j.dam.2009.02.019 JO - DISCRETE APPL MATH ER - TY - CONF T1 - Döntési fákon alapuló előfeldolgozás a bináris tomográfiában T2 - A Képfeldolgozók és Alakfelismerők Társaságának konferenciája - KÉPAF 2009 Y1 - 2009 A1 - Mihály Gara A1 - Péter Balázs ED - Dmitrij Chetverikov ED - Tamas Sziranyi JF - A Képfeldolgozók és Alakfelismerők Társaságának konferenciája - KÉPAF 2009 PB - Akaprint CY - Budapest N1 - 8 pages ER - TY - CHAP T1 - An evolutionary approach for object-based image reconstruction using learnt priors T2 - Image Analysis Y1 - 2009 A1 - Péter Balázs A1 - Mihály Gara ED - Arnt-Borre Salberg ED - Jon Yngve Hardeberg ED - Robert Jenssen AB -

In this paper we present a novel algorithm for reconstructingbinary images containing objects which can be described by some parameters. In particular, we investigate the problem of reconstructing binary images representing disks from four projections. We develop a genetic algorithm for this and similar problems. We also discuss how prior information on the number of disks can be incorporated into the reconstruction in order to obtain more accurate images. In addition, we present a method to exploit such kind of knowledge from the projections themselves. Experiments on artificial data are also conducted. © 2009 Springer Berlin Heidelberg.

JF - Image Analysis T3 - Lecture Notes in Computer Science PB - Springer-Verlag CY - Oslo, Norway SN - 978-3-642-02229-6 N1 - UT: 000268661000053ScopusID: 70350650400doi: 10.1007/978-3-642-02230-2_53 JO - LNCS ER - TY - JOUR T1 - Learning connectedness and convexity of binary images from their projections JF - PURE MATHEMATICS AND APPLICATIONS Y1 - 2009 A1 - Mihály Gara A1 - Tamás Sámuel Tasi A1 - Péter Balázs VL - 20 SN - 1218-4586 IS - 1-2 JO - PU.M.A PURE MATH APPL ER - TY - CONF T1 - Neutron tomography with prior information T2 - 5th Conference on Applied Inverse Problems Y1 - 2009 A1 - Péter Balázs JF - 5th Conference on Applied Inverse Problems VL - Abstracts ER - TY - CONF T1 - Reconstruction of binary images with disjoint components from horizontal and vertical projections T2 - A Képfeldolgozók és Alakfelismerők Társaságának konferenciája - KÉPAF 2009 Y1 - 2009 A1 - Péter Balázs ED - Dmitrij Chetverikov ED - Tamas Sziranyi JF - A Képfeldolgozók és Alakfelismerők Társaságának konferenciája - KÉPAF 2009 PB - Akaprint CY - Budapest N1 - 8 pages ER - TY - CHAP T1 - Reconstruction of canonical hv-convex discrete sets from horizontal and vertical projections T2 - Combinatorial Image Analysis Y1 - 2009 A1 - Péter Balázs ED - Petra Wiederhold ED - Reneta P Barneva AB -The problem of reconstructing some special hv-convex discretesets from their two orthogonal projections is considered. In general, the problem is known to be NP-hard, but it is solvable in polynomial time if the discrete set to be reconstructed is also 8-connected. In this paper, we define an intermediate class - the class of hv-convex canonical discrete sets - and give a constructive proof that the above problem remains computationally tractable for this class, too. We also discuss some further theoretical consequences and present experimental results as well. © Springer-Verlag Berlin Heidelberg 2009.

JF - Combinatorial Image Analysis PB - Springer Verlag CY - Berlin; Heidelberg; New York; London; Paris; Tokyo SN - 978-3-642-10208-0 N1 - UT: 000279344100022ScopusID: 78650444641doi: 10.1007/978-3-642-10210-3_22 ER - TY - JOUR T1 - On the ambiguity of reconstructing hv-convex binary matrices with decomposable configurations JF - ACTA CYBERNETICA-SZEGED Y1 - 2008 A1 - Péter Balázs AB -`Reconstructing binary matrices from their row, column, diagonal, and antidiagonal sums (also called projections) plays a central role in discrete tomography. One of the main difficulties in this task is that in certain cases the projections do not uniquely determine the binary matrix. This can yield an extremely large number of (sometimes very different) solutions. This ambiguity can be reduced by having some prior knowledge about the matrix to be reconstructed. The main challenge here is to find classes of binary matrices where ambiguity is drastically reduced or even completely eliminated. The goal of this paper is to study the class of $hv$-convex matrices which have decomposable configurations from the viewpoint of ambiguity. First, we give a negative result in the case of three projections. Then, we present a heuristic for the reconstruction using four projections and analyze its performance in quality and running time.`

In binary tomography, several algorithms are known for reconstructing binary images having some geometrical properties from their projections. In order to choose the appropriate reconstruction algorithm it is necessary to have a priori information of the image to be reconstructed. In this way we can improve the speed and reduce the ambiguity of the reconstruction. Our work is concerned with the problem of retrieving geometrical information from the projections themselves. We investigate whether it is possible to determine geometric features of binary images if only their projections are known. Most of the reconstruction algorithms based on geometrical information suppose $hv$-convexity or connectedness about the image to be reconstructed. We investigate those properties in detail, and also the task of separating 4- and 8-connected images. We suggest decision trees for the classification, and show some preliminary experimental results of applying them for the class of $hv$-convex and connected discrete sets. ` `

We present a general framework for reconstructing binary images with disjoint components from the horizontal and vertical projections. We develop a backtracking algorithm that works for binary images having components from an arbitrary class. Thus, a priori knowledge about the components of the image to be reconstructed can be incorporated into the reconstruction process. In addition, we show how to extend the algorithm to obtain a branch-and-bound scheme useful to reconstruct images satisfying some further properties (for example similarity to a model image) as much as possible. Experimental results are also presented.

PB - World Scientific VL - 14 SN - 0218-6543 IS - 2 N1 - ScopusID: 76849116810doi: 10.1142/S0218654308001142 JO - INT J SHAPE MODEL ER - TY - JOUR T1 - A framework for generating some discrete sets with disjoint components by using uniform distributions JF - THEORETICAL COMPUTER SCIENCE Y1 - 2008 A1 - Péter Balázs PB - Elsevier VL - 406 SN - 0304-3975 IS - 1-2 N1 - UT: 000260289400004ScopusID: 51549107301doi: 10.1016/j.tcs.2008.06.010 JO - THEOR COMPUT SCI ER - TY - CHAP T1 - A képfeldolgozás kutatása a Szegedi Tudományegyetemen T2 - Informatika a felsőoktatásban 2008 Y1 - 2008 A1 - Péter Balázs A1 - Balázs Erdőhelyi A1 - Endre Katona A1 - Zoltan Kato A1 - Eörs Máté A1 - Antal Nagy A1 - László Gábor Nyúl A1 - Kálmán Palágyi A1 - Attila Tanacs ED - Attila Pethő ED - Miklós Herdon AB - A digitális képfeldolgozás kutatásának a Szegedi TudományegyetemTermészettudományi és Informatikai Karán, az Informatikai Tanszékcsoport Képfeldolgozás és Számítógépes Grafika Tanszékén közel négy évtizedes hagyománya van. A Tanszék valamennyi munkatársa nemzetközileg elismert kutatómunkát folytat, melyet már több száz rangos publikáció fémjelez. Számos, a képfeldolgozás kutatásában vezető egyetemmel és kutatóintézettel építettünk ki szoros kapcsolatot és folytattunk eredményes kutatómunkát, aktív résztvevői vagyunk a hazai és a nemzetközi tudományos közéletnek. A legfontosabb, jelenleg is folyó kutatásaink: orvosi képek feldolgozása, diszkrét tomográfia, képszegmentálás, térinformatika, távérzékelés, képregisztráció, vázkijelölés, műtéti tervezés. JF - Informatika a felsőoktatásban 2008 PB - Debreceni Egyetem Informatikai Kar CY - Debrecen UR - http://www.agr.unideb.hu/if2008/kiadvany/papers/E62.pdf N1 - Art. No.: E62 ER - TY - CHAP T1 - On the number of hv-convex discrete sets T2 - Combinatorial Image Analysis Y1 - 2008 A1 - Péter Balázs ED - Valentin E Brimkov ED - Reneta P Barneva ED - Herbert A Hauptman AB -

One of the basic problems in discrete tomography is thereconstruction of discrete sets from few projections. Assuming that the set to be reconstructed fulfills some geometrical properties is a commonly used technique to reduce the number of possibly many different solutions of the same reconstruction problem. The class of hv-convex discrete sets and its subclasses have a well-developed theory. Several reconstruction algorithms as well as some complexity results are known for those classes. The key to achieve polynomial-time reconstruction of an hv- convex discrete set is to have the additional assumption that the set is connected as well. This paper collects several statistics on hv-convex discrete sets, which are of great importance in the analysis of algorithms for reconstructing such kind of discrete sets. © 2008 Springer-Verlag Berlin Heidelberg.

JF - Combinatorial Image Analysis T3 - Lecture Notes in Computer Science PB - Springer Verlag CY - Buffalo, NY, USA SN - 978-3-540-78274-2 N1 - UT: 000254600100010ScopusID: 70249110264doi: 10.1007/978-3-540-78275-9_10 JO - LNCS ER - TY - CHAP T1 - Reconstruction of binary images with few disjoint components from two projections T2 - Advances in Visual Computing Y1 - 2008 A1 - Péter Balázs ED - George Bebis ED - Richard Boyle ED - Bahram Parvin ED - Darko Koracin ED - Paolo Remagnino ED - Fatih Porikli ED - Jörg Peters ED - James Klosowski ED - Laura Arns ED - Yu Ka Chun ED - Theresa-Marie Rhyne ED - Laura Monroe AB -We present a general framework for reconstructing binary imageswith few disjoint components from the horizontal and vertical projections. We develop a backtracking algorithm that works for binary images having components from an arbitrary class. Thus, a priori information about the components of the image to be reconstructed can be incorporated into the reconstruction process. In addition, we can keep control over the number of components which can increase the speed and accuracy of the reconstruction. Experimental results are also presented. © 2008 Springer Berlin Heidelberg.

JF - Advances in Visual Computing T3 - Lecture Notes in Computer Science PB - Springer Verlag CY - Las Vegas, NV, USA SN - 978-3-540-89645-6 N1 - UT: 000262709700114ScopusID: 70149090157doi: 10.1007/978-3-540-89646-3_114 JO - LNCS ER - TY - THES T1 - Binary Tomography Using Geometrical Priors: Uniqueness and Reconstruction Results Y1 - 2007 A1 - Péter Balázs PB - University of Szeged CY - Szeged, Hungary ER - TY - CHAP T1 - Decomposition Algorithms for Reconstructing Discrete Sets with Disjoint Components T2 - ADVANCES IN DISCRETE TOMOGRAPHY AND ITS APPLICATIONS Y1 - 2007 A1 - Péter Balázs ED - Gábor T Herman ED - Attila Kuba AB -The reconstruction of discrete sets from their projections is a frequently studied field in discrete tomography with applications in electron microscopy, image processing, radiology, and so on. Several efficient reconstruction algorithms have been developed for certain classes of discrete sets having some good geometrical properties. On the other hand, it has been shown that the reconstruction under certain circumstances can be very time-consuming, even NP-hard. In this chapter we show how prior information that the set to be reconstructed consists of several components can be exploited in order to facilitate the reconstruction. We present some general techniques to decompose a discrete set into components knowing only its projections and thus reduce the reconstruction of a general discrete set to the reconstruction of single components, which is usually a simpler task.

JF - ADVANCES IN DISCRETE TOMOGRAPHY AND ITS APPLICATIONS T3 - Applied and Numerical Harmonic Analysis PB - Birkhauser Boston CY - Cambridge SN - 978-0-8176-3614-2 N1 - UT: 000271523600010doi: 10.1007/978-0-8176-4543-4_8 ER - TY - JOUR T1 - A decomposition technique for reconstructing discrete sets from four projections JF - IMAGE AND VISION COMPUTING Y1 - 2007 A1 - Péter Balázs AB -The reconstruction of discrete sets from four projections is in general an NP-hard problem. In this paper we study the class of decomposable discrete sets and give an efficient reconstruction algorithm for this class using four projections. It is also shown that an arbitrary discrete set which is Q-convex along the horizontal and vertical directions and consists of several components is decomposable. As a consequence of decomposability we get that in a subclass of *hv*-convex discrete sets the reconstruction from four projections can also be solved in polynomial time. Possible extensions of our method are also discussed.

One of the basic problems in discrete tomography is thereconstruction of discrete sets from few projections. Assuming that the set to be reconstructed fulfils some geometrical properties is a commonly used technique to reduce the number of possibly many different solutions of the same reconstruction problem. Since the reconstruction from two projections in the class of so-called hv-convex sets is NP-hard this class is suitable to test the efficiency of newly developed reconstruction algorithms. However, until now no method was known to generate sets of this class from uniform random distribution and thus only ad hoc comparison of several reconstruction techniques was possible. In this paper we first describe a method to generate some special hv-convex discrete sets from uniform random distribution. Moreover, we show that the developed generation technique can easily be adapted to other classes of discrete sets, even for the whole class of hv- convexes. Several statistics are also presented which are of great importance in the analysis of algorithms for reconstructing hv-convex sets. © Springer-Verlag Berlin Heidelberg 2007.

JF - Image Analysis T3 - Lecture Notes in Computer Science PB - Springer Verlag CY - Aalborg, Denmark SN - 978-3-540-73039-2 N1 - UT: 000247364000035ScopusID: 38049002073 JO - LNCS ER - TY - CHAP T1 - Reconstructing some hv-convex binary images from three or four projections T2 - Proccedings of the 5th International Symposium on Image and Signal Processing and Analysis Y1 - 2007 A1 - Péter Balázs ED - M Petrou ED - T Saramaki ED - Aytul Ercil ED - Sven Lončarić AB -The reconstruction of binary images from their projections is animportant problem in discrete tomography. The main challenge in this task is that in certain cases the projections do not uniquely determine the binary image. This can yield an extremely large number of (sometimes very different) solutions. Moreover, under certain circumstances the reconstruction becomes NP-hard. A commonly used technique to reduce ambiguity and to avoid intractability is to suppose that the image to be reconstructed arises from a certain class of images having some geometrical properties. This paper studies the reconstruction problem in the class of hv-convex images having their components in so-called decomposable configurations. First, we give a negative result showing that there can be exponentially many images of the above class having the same three projections. Then, we present a heuristic that uses four projections to reconstruct an hv-convex image with decomposable configuration. We also analyze the performance of our heuristic from the viewpoints of accuracy and running time.

JF - Proccedings of the 5th International Symposium on Image and Signal Processing and Analysis PB - IEEE CY - Istanbul, Turkey SN - 978-953-184-116-0 N1 - UT: 000253387900025ScopusID: 7949129892doi: 10.1109/ISPA.2007.4383678 ER - TY - CONF T1 - Uniform generation of hv-convex discrete sets T2 - A Képfeldolgozók és Alakfelismerők Társaságának konferenciája - KÉPAF 2007 Y1 - 2007 A1 - Péter Balázs ED - Attila Fazekas ED - András Hajdú JF - A Képfeldolgozók és Alakfelismerők Társaságának konferenciája - KÉPAF 2007 PB - Képfeldolgozók és Alakfelismerők Társasága CY - Debrecen ER - TY - CONF T1 - On the ambiguity of reconstructing decomposable hv-convex binary matrices T2 - Conference of PhD Students in Computer Science Y1 - 2006 A1 - Péter Balázs ED - Tibor Csendes ED - Péter Gábor Szabó ED - Mariann Sebő ED - Balázs Bánhelyi ED - Judit Jász ED - Gabriella Nagyné Hecskó JF - Conference of PhD Students in Computer Science VL - Volume of Extenden Abstracts ER - TY - CHAP T1 - The number of line-convex directed polyominoes having the same orthogonal projections T2 - Discrete Geometry for Computer Imagery Y1 - 2006 A1 - Péter Balázs ED - Attila Kuba ED - László Gábor Nyúl ED - Kálmán Palágyi AB -The number of line-convex directed polyominoes with givenhorizontal and vertical projections is studied. It is proven that diagonally convex directed polyominoes are uniquely determined by their orthogonal projections. The proof of this result is algorithmical. As a counterpart, we show that ambiguity can be exponential if antidiagonal convexity is assumed about the polyomino. Then, the results are generalised to polyominoes having convexity property along arbitrary lines. © Springer-Verlag Berlin Heidelberg 2006.

JF - Discrete Geometry for Computer Imagery PB - Springer-Verlag CY - Berlin, Heidelberg N1 - UT: 000241649600007ScopusID: 33845210215 ER - TY - JOUR T1 - Reconstruction of 8-connected but not 4-connected hv-convex discrete sets JF - DISCRETE APPLIED MATHEMATICS Y1 - 2005 A1 - Péter Balázs A1 - Emese Balogh A1 - Attila Kuba VL - 147 SN - 0166-218X N1 - UT: 000228118600002ScopusID: 14744285148doi: 10.1016/j.dam.2004.09.009 JO - DISCRETE APPL MATH ER - TY - CHAP T1 - Reconstruction of decomposable discrete sets from four projections T2 - Discrete Geometry for Computer Imagery Y1 - 2005 A1 - Péter Balázs ED - Eric Andres ED - Guillaume Damiand ED - Pascal Lienhardt AB -In this paper we introduce the class of decomposable discretesets and give a polynomial algorithm for reconstructing discrete sets of this class from four projections. It is also shown that the class of decomposable discrete sets is more general than the class S′8 of hv-convex 8-but not 4-connected discrete sets which was studied in [3]. As a consequence we also get that the reconstruction from four projections in S′8can be solved in O(mn) time. © Springer-Verlag Berlin Heidelberg 2005.

JF - Discrete Geometry for Computer Imagery PB - Springer Verlag CY - Berlin; Heidelberg; New York; London; Paris; Tokyo N1 - UT: 000229183900010ScopusID: 24344465865 ER - TY - JOUR T1 - Reconstruction of discrete sets from four projections: strong decomposability JF - ELECTRONIC NOTES IN DISCRETE MATHEMATICS Y1 - 2005 A1 - Péter Balázs VL - 20 SN - 1571-0653 N1 - ScopusID: 34247130130doi: 10.1016/j.endm.2005.05.072 JO - ELECTRON NOTES DISCRETE MATH ER - TY - CONF T1 - Reconstruction of discrete sets from four projections: Decomposable cases T2 - Conference of PhD Students in Computer Science Y1 - 2004 A1 - Péter Balázs A1 - Attila Kuba ED - Tibor Csendes ED - Péter Gábor Szabó ED - Mariann Sebő ED - Balázs Bánhelyi ED - Judit Jász ED - Gabriella Nagyné Hecskó JF - Conference of PhD Students in Computer Science VL - Volume of Extended Abstracts ER - TY - CHAP T1 - A fast algorithm for reconstructing hv-convex 8-connected but not 4-connected discrete sets T2 - Discrete Geometry for Computer Imagery Y1 - 2003 A1 - Péter Balázs A1 - Emese Balogh A1 - Attila Kuba ED - Ingela Nyström ED - Gabriella Sanniti di Baja ED - Stina Svensson JF - Discrete Geometry for Computer Imagery PB - Springer Verlag CY - Berlin; Heidelberg; New York; London; Paris; Tokyo N1 - UT: 000187499600037ScopusID: 0242460250 ER - TY - CONF T1 - A fast algorithm for reconstructing hv-convex 8-connected but not 4-connected discrete sets T2 - Conference of PhD Students in Computer Science Y1 - 2002 A1 - Péter Balázs A1 - Emese Balogh A1 - Attila Kuba ED - Tibor Csendes ED - Lajos Schrettner ED - Mariann Sebő ED - Péter Gábor Szabó ED - B Tóth ED - Tamás Vinkó JF - Conference of PhD Students in Computer Science VL - Volume of Extended Abstracts ER -