Research interest:
Scientific talks:
Further conference attendance:
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Foreign activities:
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Scientific publications:
Download my selected publications
Download the list of my independent citations
Book chapter:
[1]
P. Balázs: Decomposition algorithms for
reconstructing discrete sets with disjoint components, In G.T. Herman, A. Kuba
(Eds.), Advances in Discrete Tomography
and Its Applications, Birkhäuser, Boston, pp. 153-173, 2007.
Journal articles:
[1]
P. Balázs, E. Balogh, A. Kuba: Reconstruction of
8-connected but not 4-connected hv-convex
discrete sets, Discrete Applied
Mathematics (Elsevier) 147
149-168 (2005), IF: 0.585
[2]
P. Balázs: A decomposition technique for
reconstructing discrete sets from four projections, Image and Vision Computing (Elsevier) 25:10 1609-1619 (2007), IF: 1.027
[3]
P. Balázs: On the ambiguity of reconstructing hv-convex binary matrices with
decomposable configurations, Acta
Cybernetica 18(3) 367-377 (2008)
[4]
P. Balázs: A framework for generating
some discrete sets with disjoint components by using uniform
distributions, Theoretical
Computer Science (Elsevier) 406 15-23
(2008), IF: 0.806
[5]
P. Balázs: Discrete tomographic
reconstruction of binary images with disjoint components using shape
information,
International Journal of Shape
Modeling
(World Scientific)
14:2 189-207 (2008)
[6]
P. Balázs: A benchmark set for the reconstruction of hv-convex discrete sets, Discrete Applied Mathematics
(Elsevier)
157 3447-3456 (2009), IF: 0.816
[7]
M. Gara, T.S. Tasi, P. Balázs: Learning connectedness and convexity of binary images from their projections, Pure Mathematics and Applications
20:1-2 27-48 (2009)
[8]
L. Varga, P. Balázs, A. Nagy: Projection selection dependency in binary tomography, Acta Cybernetica
20(1) 167-187 (2011)
[9]
L. Varga, P. Balázs, A. Nagy:
Direction-dependency of binary tomographic reconstruction
algorithms, Graphical Models
(Elsevier) 73 365-375 (2011), IF: 1.000
[10]
K.J. Batenburg, W.J. Palenstijn, P. Balázs, J. Sijbers:
Dynamic angle selection in binary tomography,
Computer Vision and Image Understanding
(Elsevier) 117(4) 306-318 (2013), IF: 1.340*
[11]
N. Hantos, P. Balázs:
The reconstruction of polyominoes from horizontal and vertical projections
and morphological skeleton is NP-complete,
Fundamenta Informaticae,
accepted, IF: 0.365*
[12]
P. Balázs:
Complexity results for reconstructing binary images with disjoint
components from horizontal and vertical projections,
Discrete Applied Mathematics,
accepted, IF: 0.795*
[13]
Z. Ozsvár, P. Balázs:
An empirical study of reconstructing hv-convex
binary matrices from horizontal and vertical projections,
Acta Cybernetica,
accepted
Selected
conference papers:
[1]
P. Balázs, E. Balogh, A. Kuba: A fast algorithm
for reconstructing hv-convex
8-connected but not 4-connected discrete sets, 11th International Conference on Discrete Geometry for
Computer Imagery, Naples, Italy, November 2003, Proceedings, Lecture Notes in
Computer Science (Springer) 2886
388-397 (2003)
[2]
P. Balázs: Reconstruction of decomposable
discrete sets from four projections, 12th
International Conference on Discrete Geometry for Computer Imagery, Poitiers,
France, April 2005, Proceedings, Lecture Notes in Computer Science
(Springer) 3429 104-114 (2005)
[3]
P. Balázs: Reconstruction of discrete sets from
four projections: strong decomposability, Workshop
on Discrete Tomography and Its Applications, New York City, USA, June 2005,
Proceedings, Electronic Notes in Discrete Mathematics (Elsevier) 20 329-345 (2005)
[4]
P. Balázs: The number of line-convex directed
polyominoes having the same orthogonal projections, 13th International Conference on Discrete Geometry for
Computer Imagery, Szeged, Hungary, October 2006, Proceedings, Lecture Notes in
Computer Science (Springer) 4245 77-85 (2006)
[5]
P. Balázs: Generation and empirical
investigation of hv-convex discrete
sets, 15th Scandinavian
Conference on Image Analysis, Aalborg, Denmark, June 2007, Proceedings, Lecture
Notes in Computer Science (Springer) 4522 344-353 (2007)
[6] P. Balázs:
Reconstructing some hv-convex binary
images from three or four projections, Abstracts
of the 5th International Symposium on Image and Signal Processing
and Analysis,
[7]
P. Balázs: On the number of hv-convex discrete
sets, 12th
International Workshop on Combinatorial Image Analysis, Buffalo, USA,
April 2008, Proceedings, Lecture
Notes in Computer Science (Springer) 4958 112-123
(2008)
[8]
P. Balázs, M. Gara: Decision trees in binary tomography for
supporting the reconstruction of hv-convex connected images,
10th International Conference on Advanced Concepts for Intelligent Vision Systems 2008, Juan-les-Pins, France,
October 2008, Proceedings, Lecture
Notes in Computer Science (Springer) 5259 433-443
(2008)
[9]
P. Balázs: Reconstruction of binary images
with few disjoint components from two projections,
4th International Symposium on Visual Computing 2008, Las Vegas, USA,
December 2008, Proceedings, Lecture
Notes in Computer Science (Springer) 5359 1147-1156
(2008)
[10]
P. Balázs, M. Gara: An evolutionary approach for object based image reconstruction using learnt priors, 16th Scandinavian
Conference on Image Analysis, Oslo, Norway, June 2009, Proceedings, Lecture
Notes in Computer Science (Springer) 5575 520-529 (2009)
[11]
P. Balázs: Reconstruction of canonical hv-convex discrete
sets from horizontal and vertical projections, 13th
International Workshop on Combinatorial Image Analysis, Playa del Carmen, Mexico,
November 2009, Proceedings, Lecture
Notes in Computer Science (Springer) 5852 280-288
(2009)
[12]
L. Varga, P. Balázs, A. Nagy: Direction-dependency of a binary tomographic reconstruction
algorithm, 2nd
International Symposium on Computational Modeling of Objects Represented in Images, Buffalo, USA,
May 2010, Proceedings, Lecture
Notes in Computer Science (Springer) 6026 242-253
(2010)
[13]
N. Hantos, P. Balázs: Image enhancement by median filters in algebraic reconstruction methods: an experimental study,
6th International Symposium on Visual Computing, Las Vegas, USA,
November 2010, Proceedings, Lecture
Notes in Computer Science (Springer) 6455 339-348
(2010)
[14]
L. Varga, P. Balázs, A. Nagy: Projection selection algorithms for discrete tomography, 12th
International Conference on Advanced Concepts for Intelligent Vision Systems, Sydney, Australia,
December 2010, Proceedings, Lecture
Notes in Computer Science (Springer) 6474 390-401
(2010)
[15]
T.S. Tasi, M. Hegedűs, P. Balázs: Perimeter estimation of some discrete sets from horizontal and vertical projections, 9th
IASTED International Conference on Signal Processing, Pattern Recognition and Applications, Crete, Greece, June 2012, Proceedings, pp. 174-181
(2012)
[16]
P. Balázs, K.J. Batenburg: A central reconstruction based strategy for selecting projection angles in binary tomography, 9th
International Conference on Image Analysis and Recognition, Aveiro, Portugal,
June 2012, Proceedings, Lecture
Notes in Computer Science (Springer) 7325 382-391
(2012)
[17]
M. Gara, T.S. Tasi, P. Balázs: Machine learning as a preprocessing phase in discrete tomography, 1st
International Workshop on Applications of Discrete Geometry and Mathematical Morphology, Istanbul, Turkey,
August 2010, Revised Selected Papers, Lecture
Notes in Computer Science (Springer) 7346 109-124
(2012)
[18]
L. Varga, P. Balázs, A. Nagy: An energy minimization reconstruction algorithm for multivalued discrete tomography, 3rd
International Symposium on Computational Modelling of Objects Represented
in Images, Rome, Italy, September 2012, Proceedings (Taylor &
Francis), pp. 179-185 (2012)
[19]
N. Hantos, P. Balázs, K. Palágyi: Binary
image reconstruction from two projections and skeletal information, 15th
International Workshop on Combinatorial Image Analysis, Austin, TX, USA,
November 2012, Proceedings, Lecture
Notes in Computer Science (Springer) 7655 263-273
(2012)
[20]
L. Varga. L.G. Nyúl, A. Nagy, P. Balázs: Local uncertainty in binary tomographic reconstruction, 10th
IASTED International Conference on Signal Processing, Pattern Recognition and Applications, Innsbruck, Austria, February 2013,
Proceedings, pp. 490-496
(2013)
Further
conference papers:
[1] P. Balázs, E.
Balogh, A. Kuba: A fast algorithm for reconstructing hv-convex 8-connected but not 4-connected discrete sets, Volume of Extended Abstracts of the 3rd
Conference of PhD Students in Computer Science, Szeged, Hungary, 1-4 July, 2002,
pp. 19.
[2] P. Balázs, A.
Kuba: Reconstruction of discrete sets from four projections: Decomposable
cases, Volume of Extended Abstracts of
the 4th Conference of PhD Students in Computer Science, Szeged,
Hungary, 1-4 July, 2004, pp. 22.
[3] P. Balázs: On
the ambiguity of reconstructing decomposable hv-convex binary matrices, Volume
of Extended Abstracts of the 5th Conference of PhD Students in
Computer Science, Szeged, Hungary, 27-30 June, 2006, pp. 17.
[4] P. Balázs:
Uniform generation of hv-convex
discrete sets, Abstracts of the 6th
Conference of the Hungarian Association of Image Processing and Pattern
Recognition,
[5] M. Gara, P. Balázs: Determination of geometric features of binary images from their projections by using
decision trees, Volume
of Extended Abstracts of the 6th Conference of PhD Students in
Computer Science, Szeged, Hungary, 2-5 July, 2008, pp. 26.
[6] P. Balázs: Reconstruction of binary images with disjoint components from horizontal and vertical
projections, Abstracts of the 7th
Conference of the Hungarian Association of Image Processing and Pattern
Recognition,
[7] M. Gara, P. Balázs:
Preprocessing in binary tomography based on decision trees, Abstracts of
the 7th
Conference of the Hungarian Association of Image Processing and Pattern
Recognition,
[8] P. Balázs:
Neutron tomography with prior information, Abstracts of
the 5th
Conference on Applied Inverse Problems,
[9] M. Gara, P. Balázs: Binary tomographic reconstruction with an object-based evolutionary algorithm, Volume
of Extended Abstracts of the 7th Conference of PhD Students in
Computer Science, Szeged, Hungary, 29 June - 2 July, 2010, pp. 31.
[10] N. Hantos, P. Balázs: Median filtering in algebraic reconstruction methods, Volume
of Extended Abstracts of the 7th Conference of PhD Students in
Computer Science, Szeged, Hungary, 29 June - 2 July, 2010, pp. 36.
[11] T.S. Tasi, P. Balázs: Obtaining geometrical properties of binary images from two projections using
neural networks, Volume
of Extended Abstracts of the 7th Conference of PhD Students in
Computer Science, Szeged, Hungary, 29 June - 2 July, 2010, pp. 69.
[12] L. Varga, P. Balázs, A. Nagy: Object Rotation effects on binary tomographic reconstruction, Volume
of Extended Abstracts of the 7th Conference of PhD Students in
Computer Science, Szeged, Hungary, 29 June - 2 July, 2010, pp. 76.
[13] P. Balázs, M. Gara, T.S. Tasi: Machine learning for supporting binary
tomographic reconstruction, Proceedings of the Workshop on Applications of Discrete Geometry in Mathematical Morphology,
Istanbul, Turkey, 22 August, 2010, pp. 101-105.
[14]
L.
Varga, P. Balázs, A. Nagy:
Projection direction dependency in binary tomography, Abstracts of the 8th
Conference of the Hungarian Association of Image Processing and Pattern
Recognition,
[15]
N.
Hantos, P. Balázs:
Median filtering in algebraic reconstruction methods, Abstracts of the 8th
Conference of the Hungarian Association of Image Processing and Pattern
Recognition,
[16]
M. Gara,
P. Balázs:
Binary tomographic reconstruction with an object-based evolutionary
algorithm, Abstracts of the 8th
Conference of the Hungarian Association of Image Processing and Pattern
Recognition,
[17]
M. Gara,
P. Balázs:
Artificial intelligence methods in discrete tomography,
Volume
of Extended Abstracts of the 8th Conference of PhD Students in
Computer Science, Szeged, Hungary, 28-30 June, 2012, pp.
16.
[18]
N.
Hantos, P. Balázs, K. Palágyi:
Binary tomography using two projections and morphological skeleton,
Volume
of Extended Abstracts of the 8th Conference of PhD Students in
Computer Science, Szeged, Hungary, 28-30 June, 2012, pp.
20.
[19]
Z. Ozsvár, P. Balázs:
Empirical studies of reconstructing hv-convex binary matrices from horizontal and vertical projections, Volume
of Extended Abstracts of the 8th Conference of PhD Students in
Computer Science, Szeged, Hungary, 28-30 June, 2012, pp.
44.
[20]
T.S.
Tasi, P. Balázs:
Extracting geometrical features of discrete images from their projections,
Volume
of Extended Abstracts of the 8th Conference of PhD Students in
Computer Science, Szeged, Hungary, 28-30 June, 2012, pp.
52.
[21]
L.
Varga, A. Nagy, P. Balázs:
A novel optimization-based reconstruction algorithm for multivalued
discrete tomography,
Volume
of Extended Abstracts of the 8th Conference of PhD Students in
Computer Science, Szeged, Hungary, 28-30 June, 2012, pp.
57.
[22] A. Bogdanov, Sz. Urbán, V. Endrész, K. Burián, P. Balázs, J. Deák, D. Virók:
Automatic counting of chlamydial inclusions using a fluorescent DNA chip scanner,
Abstracts of the 11th István Cserháti Memorial Meeting for Young Researchers, Szeged, Hungary, 23-24 November, 2012,
pp. 37. (in Hungarian)
[23] L. Varga, P. Balázs, A. Nagy:
An optimization-based reconstruction algorithm for multivalued discrete tomography,
Program and Abstracts of the 5th Veszprém Optimization Conference: Advanced Algorithms VOCAL 2012, Veszprém, Hungary,
11-14 December, 2012,
pp. 39.
[24] N. Hantos, P. Balázs, K. Palágyi:
Solving binary tomography from morphological skeleton via optimization,
Program and Abstracts of the 5th Veszprém Optimization Conference: Advanced Algorithms VOCAL 2012, Veszprém,
Hungary, 11-14 December, 2012,
pp. 42.
[25] N.
Hantos, P. Balázs, K. Palágyi: Reconstruction of binary images from two
projections and morphological skeleton,
Abstracts of the 9th
Conference of the Hungarian Association of Image Processing and Pattern
Recognition,
[26] Z. Ozsvár, P. Balázs:
A comparison of heuristics for reconstructing hv-convex binary matrices from horizontal and vertical projections, Abstracts of the 9th
Conference of the Hungarian Association of Image Processing and Pattern
Recognition,
[27] L. Varga, P. Balázs, A. Nagy:
Discrete tomography by automatic weighting of gradient descents,
Abstracts of the 9th
Conference of the Hungarian Association of Image Processing and Pattern
Recognition,