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.

%B ANTIMICROBIAL AGENTS AND CHEMOTHERAPY %V 58 %P 405 - 413 %8 2014 %@ 0066-4804 %G eng %N 1 %9 Journal article %! ANTIMICROB AGENTS CH %0 Journal Article %J COMPUTER VISION AND IMAGE UNDERSTANDING %D 2014 %T Local and global uncertainty in binary tomographic reconstruction %A László Gábor Varga %A László Gábor Nyúl %A Antal Nagy %A Péter Balázs %XIn 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.

%B COMPUTER VISION AND IMAGE UNDERSTANDING %8 2014 %@ 1077-3142 %G eng %9 Journal article %! COMPUT VIS IMAGE UND %R 10.1016/j.cviu.2014.05.006 %0 Journal Article %J ACTA MICROBIOLOGICA ET IMMUNOLOGICA HUNGARICA %D 2013 %T APPLICATION OF DNA CHIP SCANNING TECHNOLOGY FOR THE AUTOMATIC DETECTION OF CHLAMYDIA TRACHOMATIS AND CHLAMYDIA PNEUMONIAE INCLUSIONS %B ACTA MICROBIOLOGICA ET IMMUNOLOGICA HUNGARICA %V 60 %P 173 - 174 %8 2013 %@ 1217-8950 %G eng %N Suppl. 1. %9 Journal article %! ACTA MICROBIOL IMMUNOL HUNG %0 Conference Paper %B A Képfeldolgozók és Alakfelismerők Társaságának konferenciája - KÉPAF 2013 %D 2013 %T Bináris képek rekonstrukciója két vetületből és morfológiai vázból %B A Képfeldolgozók és Alakfelismerők Társaságának konferenciája - KÉPAF 2013 %I NJSZT-KÉPAF %C Veszprém %P 182 - 193 %8 Jan 2013 %G eng %9 Conference paper %0 Conference Paper %B A Képfeldolgozók és Alakfelismerők Társaságának konferenciája - KÉPAF 2013 %D 2013 %T A comparison of heuristics for reconstructing hv-convex binary matrices from horizontal and vertical projections %A Zoltán Ozsvár %A Péter Balázs %E László Czúni %B A Képfeldolgozók és Alakfelismerők Társaságának konferenciája - KÉPAF 2013 %I NJSZT-KÉPAF %C Veszprém %P 168 - 181 %8 Jan 2013 %G eng %9 Conference paper %0 Journal Article %J DISCRETE APPLIED MATHEMATICS %D 2013 %T Complexity results for reconstructing binary images with disjoint components from horizontal and vertical projections %A Péter Balázs %B DISCRETE APPLIED MATHEMATICS %V 161 %P 2224 - 2235 %8 2013 %@ 0166-218X %G eng %9 Journal article %! DISCRETE APPL MATH %0 Book Section %B Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications %D 2013 %T Directional Convexity Measure for Binary Tomography %A Tamás Sámuel Tasi %A László Gábor Nyúl %A Péter Balázs %E Gabriella Sanniti di Baja %E Jose Ruiz-Shulcloper %XThere 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.

%B Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications %I Springer Verlag %C Berlin; Heidelberg %P 9 - 16 %8 2013 %G eng %U http://link.springer.com/chapter/10.1007%2F978-3-642-41827-3_2 %9 Conference paper %R 10.1007/978-3-642-41827-3_2 %0 Journal Article %J COMPUTER VISION AND IMAGE UNDERSTANDING %D 2013 %T Dynamic angle selection in binary tomography %A Joost K Batenburg %A Willem Jan Palenstijn %A Péter Balázs %A Jan Sijbers %XIn 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.

%B COMPUTER VISION AND IMAGE UNDERSTANDING %V 117 %P 306 - 318 %8 2013 %@ 1077-3142 %G eng %N 4 %9 Journal article %! COMPUT VIS IMAGE UND %R 10.1016/j.cviu.2012.07.005 %0 Journal Article %J ACTA CYBERNETICA-SZEGED %D 2013 %T An empirical study of reconstructing hv-convex binary matrices from horizontal and vertical projections %A Zoltán Ozsvár %A Péter Balázs %XThe 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.

%B ACTA CYBERNETICA-SZEGED %V 21 %P 149 - 163 %8 2013 %@ 0324-721X %G eng %9 Journal article %! ACTA CYBERN-SZEGED %0 Conference Paper %B A Képfeldolgozók és Alakfelismerők Társaságának konferenciája - KÉPAF 2013 %D 2013 %T Gradiens módszerek automatikus súlyozásán alapuló diszkrét tomográfiai eljárás %A László Gábor Varga %A Péter Balázs %A Antal Nagy %E László Czúni %B A Képfeldolgozók és Alakfelismerők Társaságának konferenciája - KÉPAF 2013 %I NJSZT-KÉPAF %C Veszprém %P 210 - 223 %8 Jan 2013 %G eng %9 Conference paper %0 Book Section %B Proceedings of the IASTED International Conference on Signal Processing, Pattern Recognition and Applications (SPPRA 2013) %D 2013 %T Local uncertainty in binary tomographic reconstruction %A László Gábor Varga %A László Gábor Nyúl %A Antal Nagy %A Péter Balázs %E Martin Kampel %X

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.

%B Proceedings of the IASTED International Conference on Signal Processing, Pattern Recognition and Applications (SPPRA 2013) %I IASTED - Acta Press %C Calgary %P 490 - 496 %8 Feb 2013 %G eng %9 Conference paper %R 10.2316/P.2013.798-067 %0 Thesis %B Institute of Informatics %D 2013 %T Prior Information, Machine Learning, and Direction Dependency in Binary Tomography %A Péter Balázs %B Institute of Informatics %I University of Szeged %C Szeged, Hungary %8 2013 %G eng %9 Thesis %0 Book Section %B Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications (CIARP) %D 2013 %T Reconstruction and Enumeration of hv-Convex Polyominoes with Given Horizontal Projection %A Norbert Hantos %A Péter Balázs %E Jose Ruiz-Shulcloper %E Gabriella Sanniti di Baja %B Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications (CIARP) %S Lecture Notes in Computer Science %I Springer %C Heidelberg; London; New York %P 100 - 107 %8 Nov 2013 %@ 978-3-642-41821-1 %G eng %9 Conference paper %R 10.1007/978-3-642-41822-8_13 %0 Journal Article %J FUNDAMENTA INFORMATICAE %D 2013 %T The reconstruction of polyominoes from horizontal and vertical projections and morphological skeleton is NP-complete %A Norbert Hantos %A Péter Balázs %B FUNDAMENTA INFORMATICAE %V 125 %P 343 - 359 %8 2013 %@ 0169-2968 %G eng %N 3-4 %9 Journal article %! FUND INFOR %0 Book Section %B Advanced Concepts for Intelligent Vision Systems (ACIVS) %D 2013 %T Restoration of blurred binary images using discrete tomography %A Jozsef Nemeth %A Péter Balázs %E Jacques Blanc-Talon %E Andrzej Kasinski %E Wilfried Philips %E Dan Popescu %E Paul Scheunders %XEnhancement 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.

%B Advanced Concepts for Intelligent Vision Systems (ACIVS) %S Lecture Notes in Computer Science %I Springer Verlag %C Berlin; Heidelberg; New York; London; Paris; Tokyo %P 80 - 90 %8 2013 %@ 978-3-319-02894-1 %G eng %9 Conference paper %! LNCS %R 10.1007/978-3-319-02895-8_8 %0 Conference Paper %B Proceedings of International Symposium on Image and Signal Processing and Analysis (ISPA) %D 2013 %T A uniqueness result for reconstructing hv-convex polyominoes from horizontal and vertical projections and morphological skeleton %A Norbert Hantos %A Péter Balázs %E Giovanni Ramponi %E Sven Lončarić %E Alberto Carini %E Karen Egiazarian %X

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.

%B Proceedings of International Symposium on Image and Signal Processing and Analysis (ISPA) %I IEEE %C Trieste %P 788 - 793 %8 Sep 2013 %G eng %9 Conference paper %M 14027951 %R 10.1109/ISPA.2013.6703845 %0 Generic %D 2012 %T Artificial intelligence methods in discrete tomography %A Mihály Gara %A Péter Balázs %X

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.

%B Combinatorial Image Analysis %S Lecture Notes in Computer Science %I Springer Verlag %C Berlin; Heidelberg; New York; London; Paris; Tokyo %P 263 - 273 %8 Nov 2012 %G eng %9 Conference paper %! LNCS %R 10.1007/978-3-642-34732-0_20 %0 Conference Paper %B Conference of PhD Students in Computer Science %D 2012 %T Binary tomography using two projections and morphological skeleton %B Conference of PhD Students in Computer Science %I Univ Szeged Institute of Informatics %C Szeged %V Volume of Extended Abstracts %P 20 %8 June 2012 %G eng %0 Book Section %B Image Analysis and Recognition %D 2012 %T A central reconstruction based strategy for selecting projection angles in binary tomography %A Péter Balázs %A Joost K Batenburg %E Aurélio Campilho %E Mohamed Kamel %XIn 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.

%B Image Analysis and Recognition %S Lecture Notes in Computer Science %I Springer %C Berlin; Heidelberg; New York; London; Paris; Tokyo %P 382 - 391 %8 June 2012 %G eng %9 Conference paper %! LNCS %R 10.1007/978-3-642-31295-3_45 %0 Conference Paper %B 11. Cserháti István Emlékülés : Fiatalok Tudományos Fóruma %D 2012 %T Chlamydia inklúziók automatizált számolása fluoreszcens DNS-chip szkenner segítségével %B 11. Cserháti István Emlékülés : Fiatalok Tudományos Fóruma %I SZTE ÁOK II. sz. Belgyógyászati Klinika és Kardiológiai Központ %C Szeged %P 37 %8 2012.11.23 %G eng %0 Generic %D 2012 %T Empirical studies of reconstructing hv-convex binary matrices from horizontal and vertical projections %A Zoltán Ozsvár %A Péter Balázs %B Conference of PhD students in computer science. Volume of Extended Abstracts. %I University of Szeged, Institute of Informatics %C Szeged %P 44 %8 June 2012 %G eng %9 Abstract %0 Book Section %B Computational Modelling of Objects Represented in Images: Fundamentals, Methods and Applications III %D 2012 %T An energy minimization reconstruction algorithm for multivalued discrete tomography %A László Gábor Varga %A Péter Balázs %A Antal Nagy %E Paolo Di Giamberardino %E Daniela Iacoviello %E Renato M Natal Jorge %E Joao Manuel R S Taveres %XWe 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.

%B Computational Modelling of Objects Represented in Images: Fundamentals, Methods and Applications III %I CRC Press - Taylor and Frances Group %C London %P 179 - 185 %8 2012 %G eng %9 Conference paper %R 10.1201/b12753-1 %0 Generic %D 2012 %T Extracting geometrical features of discrete images from their projections %A Tamás Sámuel Tasi %A Péter Balázs %B Conference of PhD students in computer science. Volume of Extended Abstracts. %I University of Szeged, Institute of Informatics %C Szeged %P 52 %8 June 2012 %G eng %9 Abstract %0 Book Section %B Applications of Discrete Geometry and Mathematical Morphology (WADGMM) %D 2012 %T Machine learning as a preprocessing phase in discrete tomography %A Mihály Gara %A Tamás Sámuel Tasi %A Péter Balázs %E Ullrich Köthe %E Annick Montanvert %E Pierre Soille %XIn 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.

%B Applications of Discrete Geometry and Mathematical Morphology (WADGMM) %S Lecture Notes in Computer Science %I Springer Verlag %C Berlin; Heidelberg; New York; London; Paris; Tokyo %P 109 - 124 %8 Aug 2012 %G eng %9 Conference paper %! LNCS %R 10.1007/978-3-642-32313-3_8 %0 Generic %D 2012 %T A novel optimization-based reconstruction algorithm for multivalued discrete tomography %A László Gábor Varga %A Péter Balázs %A Antal Nagy %B Conference of PhD students in computer science. Volume of extended abstracts. %I University of Szeged, Institute of Informatics %C Szeged %P 57 %8 June 2012 %G eng %9 Abstract %0 Conference Paper %B Veszprém Optimization Conference: Advanced Algorithms (Vocal) %D 2012 %T An optimization-based reconstruction algorithm for multivalued discrete tomography %A László Gábor Varga %A Péter Balázs %A Antal Nagy %B Veszprém Optimization Conference: Advanced Algorithms (Vocal) %I University of Pannonia %C Veszprém %P 39 - 40 %8 Dec 2012 %G eng %9 Conference paper %0 Conference Paper %B IASTED International Conference on Signal Processing, Pattern Recognition and Applications (SPPRA) %D 2012 %T Perimeter estimation of some discrete sets from horizontal and vertical projections %A Tamás Sámuel Tasi %A M Hegedűs %A Péter Balázs %E M Petrou %E A D Sappa %E A G Triantafyllidis %XIn 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.

%B IASTED International Conference on Signal Processing, Pattern Recognition and Applications (SPPRA) %I IASTED ACTA Press %C Crete, Greek %P 174 - 181 %8 June 2012 %G eng %9 Conference paper %R 10.2316/P.2012.778-017 %0 Conference Paper %B Veszprém Optimization Conference: Advanced Algorithms (VOCAL) %D 2012 %T Solving binary tomography from morphological skeleton via optimization %A Norbert Hantos %A Péter Balázs %A Kálmán Palágyi %B Veszprém Optimization Conference: Advanced Algorithms (VOCAL) %I University of Pannonia %C Veszprém %P 42 %8 Dec 2012 %G eng %9 Conference paper %0 Conference Paper %B A Képfeldolgozók és Alakfelismerők Társaságának konferenciája - KÉPAF 2011 %D 2011 %T Bináris tomográfiai rekonstrukció objektum alapú evolúciós algoritmussal %B A Képfeldolgozók és Alakfelismerők Társaságának konferenciája - KÉPAF 2011 %I NJSZT %C Szeged %P 117 - 127 %8 Jan 2011 %G eng %9 Conference paper %0 Journal Article %J GRAPHICAL MODELS %D 2011 %T Direction-dependency of binary tomographic reconstruction algorithms %A László Gábor Varga %A Péter Balázs %A Antal Nagy %XIn 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.

%B GRAPHICAL MODELS %V 73 %P 365 - 375 %8 Nov 2011 %@ 1524-0703 %G eng %N 6 %9 Journal article %! GRAPH MODELS %R 10.1016/j.gmod.2011.06.006 %0 Book %D 2011 %T Képrekonstrukció %I Typotex Kiadó %C Budapest %8 2011 %G eng %9 Book %0 Conference Paper %B A Képfeldolgozók és Alakfelismerők Társaságának konferenciája - KÉPAF 2011 %D 2011 %T Mediánszűrés alkalmazása algebrai rekonstrukciós módszerekben %A Norbert Hantos %A Péter Balázs %E Zoltan Kato %E Kálmán Palágyi %B A Képfeldolgozók és Alakfelismerők Társaságának konferenciája - KÉPAF 2011 %I NJSZT %C Szeged %P 106 - 116 %8 Jan 2011 %G eng %9 Conference paper %0 Journal Article %J ACTA CYBERNETICA-SZEGED %D 2011 %T Projection selection dependency in binary tomography %A László Gábor Varga %A Péter Balázs %A Antal Nagy %XIt 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.

%B ACTA CYBERNETICA-SZEGED %I University of Szeged, Institute of Informatics %C Szeged %V 20 %P 167 - 187 %8 2011 %@ 0324-721X %G eng %N 1 %9 Journal article %! ACTA CYBERN-SZEGED %0 Conference Paper %B Informatika a felsőoktatásban 2011 konferencia %D 2011 %T Tehetséggondozó program a Szegedi Tudományegyetem Informatikai Tanszékcsoport BSc szakjain %A Péter Balázs %A Zoltán L Németh %E László Cser %E Miklós Herdon %B Informatika a felsőoktatásban 2011 konferencia %I Debreceni Egyetem Informatikai Kar %C Debrecen %P 905 - 912 %8 Aug 2011 %G hun %9 Conference paper %0 Conference Paper %B A Képfeldolgozók és Alakfelismerők Társaságának konferenciája - KÉPAF 2011 %D 2011 %T Vetületi irányfüggőség a bináris tomográfiában %A László Gábor Varga %A Péter Balázs %A Antal Nagy %E Zoltan Kato %E Kálmán Palágyi %B A Képfeldolgozók és Alakfelismerők Társaságának konferenciája - KÉPAF 2011 %I NJSZT %C Szeged %P 92 - 105 %8 Jan 2011 %G hun %9 Conference paper %0 Conference Paper %B Conference of PhD Students in Computer Science. Volume of Extended Abstracts %D 2010 %T Binary tomographic reconstruction with an object-based evolutionary algorithm %A Mihály Gara %A Péter Balázs %B Conference of PhD Students in Computer Science. Volume of Extended Abstracts %I University of Szeged %C Szeged %P 31 %8 June 2010 %G eng %9 Abstract %0 Book Section %B Computational Modeling of Objects Represented in Images %D 2010 %T Direction-dependency of a binary tomographic reconstruction algorithm %A László Gábor Varga %A Péter Balázs %A Antal Nagy %E Reneta P Barneva %E Valentin E Brimkov %E Herbert A Hauptman %E Renato M Natal Jorge %E João Manuel R S Tavares %X

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.

%B Computational Modeling of Objects Represented in Images %S Lecture Notes in Computer Science %I Springer Verlag %C Buffalo, NY, USA %P 242 - 253 %8 May 2010 %@ 978-3-642-12711-3 %G eng %9 Conference paper %! LNCS %R 10.1007/978-3-642-12712-0_22 %0 Book Section %B Advances in Visual Computing %D 2010 %T Image enhancement by median filters in algebraic reconstruction methods: an experimental study %A Norbert Hantos %A Péter Balázs %E George Bebis %E Richard Boyle %E Bahram Parvin %E Darko Koracin %E Ronald Chung %E Riad Hammound %E Muhammad Hussain %E Tan Kar-Han %E Roger Crawfis %E Daniel Thalmann %E David Kao %E Lisa Avila %X

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.

%B Advances in Visual Computing %S Lecture Notes in Computer Science %I Springer Verlag %C Las Vegas, NV, USA %P 339 - 348 %8 Nov-Dec 2010 %@ 978-3-642-17276-2 %G eng %9 Conference paper %! LNCS %R 10.1007/978-3-642-17277-9_35 %0 Book Section %B Workshop on Applications of Discrete Geometry in Mathematical Morphology %D 2010 %T Machine learning for supporting binary tomographic reconstruction %A Péter Balázs %A Mihály Gara %A Tamás Sámuel Tasi %E Ullrich Köthe %E Annick Montanvert %E Pierre Soille %B Workshop on Applications of Discrete Geometry in Mathematical Morphology %S Lecture Notes in Computer Science %I Springer %C Istambul, Turkey %P 101 - 105 %8 Aug 2010 %G eng %9 Conference paper %! LNCS %0 Conference Paper %B Conference of PhD Students in Computer Science. Volume of Extended Abstracts. %D 2010 %T Median filtering in algebraic reconstruction methods %B Conference of PhD Students in Computer Science. Volume of Extended Abstracts. %I University of Szeged %C Szeged, Hungary %P 36 %8 June 2010 %G eng %9 Abstract %0 Conference Paper %B Conference of PhD Students in Computer Science. Volume of Extended Abstracts %D 2010 %T Object rotation effects on binary tomographic reconstruction %A László Gábor Varga %A Péter Balázs %A Antal Nagy %B Conference of PhD Students in Computer Science. Volume of Extended Abstracts %I University of Szeged %C Szeged, Hungary %P 76 %8 June 2010 %G eng %9 Abstract %0 Conference Paper %B Conference of PhD Students in Computer Science. Volume of Extended Abstracts %D 2010 %T Obtaining geometrical properties of binary images from two projections using neural networks %A Tamás Sámuel Tasi %A Péter Balázs %B Conference of PhD Students in Computer Science. Volume of Extended Abstracts %I University of Szeged %C Szeged, Hungary %P 69 %8 June 2010 %G eng %9 Abstract %0 Book Section %B Advanced Concepts for Intelligent Vision Systems %D 2010 %T Projection selection algorithms for discrete tomography %A László Gábor Varga %A Péter Balázs %A Antal Nagy %E Jacques Blanc-Talon %E Don Bone %E Wilfried Philips %E Dan Popescu %E Paul Scheunders %B Advanced Concepts for Intelligent Vision Systems %I Springer Verlag %C Sydney, Australia %P 390 - 401 %8 Dec 2010 %G eng %9 Conference paper %0 Journal Article %J DISCRETE APPLIED MATHEMATICS %D 2009 %T A benchmark set for the reconstruction of hv-convex discrete sets %A Péter Balázs %B DISCRETE APPLIED MATHEMATICS %I Elsevier %V 157 %P 3447 - 3456 %8 Aug 2009 %@ 0166-218X %G eng %N 16 %9 Journal article %! DISCRETE APPL MATH %R 10.1016/j.dam.2009.02.019 %0 Conference Paper %B A Képfeldolgozók és Alakfelismerők Társaságának konferenciája - KÉPAF 2009 %D 2009 %T Döntési fákon alapuló előfeldolgozás a bináris tomográfiában %B A Képfeldolgozók és Alakfelismerők Társaságának konferenciája - KÉPAF 2009 %I Akaprint %C Budapest %P nincs számozás %8 Jan 2009 %G hun %9 Conference paper %0 Book Section %B Image Analysis %D 2009 %T An evolutionary approach for object-based image reconstruction using learnt priors %A Péter Balázs %A Mihály Gara %E Arnt-Borre Salberg %E Jon Yngve Hardeberg %E Robert Jenssen %X

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.

%B Image Analysis %S Lecture Notes in Computer Science %I Springer-Verlag %C Oslo, Norway %P 520 - 529 %8 June 2009 %@ 978-3-642-02229-6 %G eng %9 Conference paper %! LNCS %R 10.1007/978-3-642-02230-2_53 %0 Journal Article %J PURE MATHEMATICS AND APPLICATIONS %D 2009 %T Learning connectedness and convexity of binary images from their projections %A Mihály Gara %A Tamás Sámuel Tasi %A Péter Balázs %B PURE MATHEMATICS AND APPLICATIONS %V 20 %P 27 - 48 %8 2009 %@ 1218-4586 %G eng %N 1-2 %9 Journal article %! PU.M.A PURE MATH APPL %0 Conference Paper %B 5th Conference on Applied Inverse Problems %D 2009 %T Neutron tomography with prior information %B 5th Conference on Applied Inverse Problems %V Abstracts %P 38 %8 July 2009 %G eng %9 Conference paper %0 Conference Paper %B A Képfeldolgozók és Alakfelismerők Társaságának konferenciája - KÉPAF 2009 %D 2009 %T Reconstruction of binary images with disjoint components from horizontal and vertical projections %B A Képfeldolgozók és Alakfelismerők Társaságának konferenciája - KÉPAF 2009 %I Akaprint %C Budapest %8 Jan 2009 %G eng %9 Conference paper %0 Book Section %B Combinatorial Image Analysis %D 2009 %T Reconstruction of canonical hv-convex discrete sets from horizontal and vertical projections %A Péter Balázs %E Petra Wiederhold %E Reneta P Barneva %XThe 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.

%B Combinatorial Image Analysis %I Springer Verlag %C Berlin; Heidelberg; New York; London; Paris; Tokyo %P 280 - 288 %8 Nov 2009 %@ 978-3-642-10208-0 %G eng %9 Conference paper %R 10.1007/978-3-642-10210-3_22 %0 Journal Article %J ACTA CYBERNETICA-SZEGED %D 2008 %T On the ambiguity of reconstructing hv-convex binary matrices with decomposable configurations %A Péter Balázs %X`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.

%B INTERNATIONAL JOURNAL OF SHAPE MODELLING %I World Scientific %V 14 %P 189 - 207 %8 Dec 2008 %@ 0218-6543 %G eng %N 2 %9 Journal article %! INT J SHAPE MODEL %R 10.1142/S0218654308001142 %0 Journal Article %J THEORETICAL COMPUTER SCIENCE %D 2008 %T A framework for generating some discrete sets with disjoint components by using uniform distributions %A Péter Balázs %B THEORETICAL COMPUTER SCIENCE %I Elsevier %V 406 %P 15 - 23 %8 Oct 2008 %@ 0304-3975 %G eng %N 1-2 %9 Journal article %! THEOR COMPUT SCI %R 10.1016/j.tcs.2008.06.010 %0 Book Section %B Informatika a felsőoktatásban 2008 %D 2008 %T A képfeldolgozás kutatása a Szegedi Tudományegyetemen %X 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. %B Informatika a felsőoktatásban 2008 %I Debreceni Egyetem Informatikai Kar %C Debrecen %8 2008/// %G eng %U http://www.agr.unideb.hu/if2008/kiadvany/papers/E62.pdf %0 Book Section %B Combinatorial Image Analysis %D 2008 %T On the number of hv-convex discrete sets %A Péter Balázs %E Valentin E Brimkov %E Reneta P Barneva %E Herbert A Hauptman %X

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.

%B Combinatorial Image Analysis %S Lecture Notes in Computer Science %I Springer Verlag %C Buffalo, NY, USA %P 112 - 123 %8 Apr 2008 %@ 978-3-540-78274-2 %G eng %9 Conference paper %! LNCS %R 10.1007/978-3-540-78275-9_10 %0 Book Section %B Advances in Visual Computing %D 2008 %T Reconstruction of binary images with few disjoint components from two projections %A Péter Balázs %E George Bebis %E Richard Boyle %E Bahram Parvin %E Darko Koracin %E Paolo Remagnino %E Fatih Porikli %E Jörg Peters %E James Klosowski %E Laura Arns %E Yu Ka Chun %E Theresa-Marie Rhyne %E Laura Monroe %XWe 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.

%B Advances in Visual Computing %S Lecture Notes in Computer Science %I Springer Verlag %C Las Vegas, NV, USA %P 1147 - 1156 %8 Dec 2008 %@ 978-3-540-89645-6 %G eng %9 Conference paper %! LNCS %R 10.1007/978-3-540-89646-3_114 %0 Thesis %D 2007 %T Binary Tomography Using Geometrical Priors: Uniqueness and Reconstruction Results %A Péter Balázs %I University of Szeged %C Szeged, Hungary %8 2007 %G eng %9 PhD thesis %0 Book Section %B ADVANCES IN DISCRETE TOMOGRAPHY AND ITS APPLICATIONS %D 2007 %T Decomposition Algorithms for Reconstructing Discrete Sets with Disjoint Components %A Péter Balázs %E Gábor T Herman %E Attila Kuba %XThe 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.

%B ADVANCES IN DISCRETE TOMOGRAPHY AND ITS APPLICATIONS %S Applied and Numerical Harmonic Analysis %I Birkhauser Boston %C Cambridge %P 153 - 173 %8 2007 %@ 978-0-8176-3614-2 %G eng %9 Book chapter %R 10.1007/978-0-8176-4543-4_8 %0 Journal Article %J IMAGE AND VISION COMPUTING %D 2007 %T A decomposition technique for reconstructing discrete sets from four projections %A Péter Balázs %XThe 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.

%B Image Analysis %S Lecture Notes in Computer Science %I Springer Verlag %C Aalborg, Denmark %P 344 - 353 %8 June 2007 %@ 978-3-540-73039-2 %G eng %9 Conference paper %! LNCS %R 10.1007/978-3-540-73040-8_35 %0 Book Section %B Proccedings of the 5th International Symposium on Image and Signal Processing and Analysis %D 2007 %T Reconstructing some hv-convex binary images from three or four projections %A Péter Balázs %E M Petrou %E T Saramaki %E Aytul Ercil %E Sven Lončarić %XThe 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.

%B Proccedings of the 5th International Symposium on Image and Signal Processing and Analysis %I IEEE %C Istanbul, Turkey %P 136 - 140 %8 Sep 2007 %@ 978-953-184-116-0 %G eng %9 Conference paper %R 10.1109/ISPA.2007.4383678 %0 Conference Paper %B A Képfeldolgozók és Alakfelismerők Társaságának konferenciája - KÉPAF 2007 %D 2007 %T Uniform generation of hv-convex discrete sets %B A Képfeldolgozók és Alakfelismerők Társaságának konferenciája - KÉPAF 2007 %I Képfeldolgozók és Alakfelismerők Társasága %C Debrecen %P 63 - 70 %8 Jan 2007 %G eng %9 Conference paper %0 Conference Paper %B Conference of PhD Students in Computer Science %D 2006 %T On the ambiguity of reconstructing decomposable hv-convex binary matrices %B Conference of PhD Students in Computer Science %V Volume of Extenden Abstracts %P 17 %8 June 2006 %G eng %0 Book Section %B Discrete Geometry for Computer Imagery %D 2006 %T The number of line-convex directed polyominoes having the same orthogonal projections %XThe 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.

%B Discrete Geometry for Computer Imagery %I Springer-Verlag %C Berlin, Heidelberg %P 77 - 85 %8 2006/// %G eng %0 Journal Article %J DISCRETE APPLIED MATHEMATICS %D 2005 %T Reconstruction of 8-connected but not 4-connected hv-convex discrete sets %B DISCRETE APPLIED MATHEMATICS %V 147 %P 149 - 168 %8 2005/// %@ 0166-218X %G eng %! DISCRETE APPL MATH %0 Book Section %B Discrete Geometry for Computer Imagery %D 2005 %T Reconstruction of decomposable discrete sets from four projections %XIn 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.

%B Discrete Geometry for Computer Imagery %I Springer Verlag %C Berlin; Heidelberg; New York; London; Paris; Tokyo %P 104 - 114 %8 2005/// %G eng %0 Journal Article %J ELECTRONIC NOTES IN DISCRETE MATHEMATICS %D 2005 %T Reconstruction of discrete sets from four projections: strong decomposability %B ELECTRONIC NOTES IN DISCRETE MATHEMATICS %V 20 %P 329 - 345 %8 2005/// %@ 1571-0653 %G eng %! ELECTRON NOTES DISCRETE MATH %0 Conference Paper %B Conference of PhD Students in Computer Science %D 2004 %T Reconstruction of discrete sets from four projections: Decomposable cases %B Conference of PhD Students in Computer Science %V Volume of Extended Abstracts %P 22 %8 July 2004 %G eng %0 Book Section %B Discrete Geometry for Computer Imagery %D 2003 %T A fast algorithm for reconstructing hv-convex 8-connected but not 4-connected discrete sets %B Discrete Geometry for Computer Imagery %I Springer Verlag %C Berlin; Heidelberg; New York; London; Paris; Tokyo %P 388 - 397 %8 2003/// %G eng %0 Conference Paper %B Conference of PhD Students in Computer Science %D 2002 %T A fast algorithm for reconstructing hv-convex 8-connected but not 4-connected discrete sets %B Conference of PhD Students in Computer Science %V Volume of Extended Abstracts %P 19 %8 July 2002 %G eng