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Publications of Péter Balázs
2009
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Learning connectedness and convexity of binary images from their projections. PURE MATHEMATICS AND APPLICATIONS. 2009;20(1-2):27-48.
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Reconstruction of binary images with disjoint components from horizontal and vertical projections. In: A Képfeldolgozók és Alakfelismerők Társaságának konferenciája - KÉPAF 2009. Budapest: Akaprint; 2009.
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Döntési fákon alapuló előfeldolgozás a bináris tomográfiában. In: A Képfeldolgozók és Alakfelismerők Társaságának konferenciája - KÉPAF 2009. Budapest: Akaprint; 2009. n. nincs számozás.
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Neutron tomography with prior information. In: 5th Conference on Applied Inverse Problems. Vol Abstracts.; 2009. 3. 38.
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Reconstruction of canonical hv-convex discrete sets from horizontal and vertical projections. In: Wiederhold P, Barneva RP, editors. Combinatorial Image Analysis. Berlin; Heidelberg; New York; London; Paris; Tokyo: Springer Verlag; 2009. 2. p. 280-288p.
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A benchmark set for the reconstruction of hv-convex discrete sets. DISCRETE APPLIED MATHEMATICS. 2009;157(16):3447-3456.
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An evolutionary approach for object-based image reconstruction using learnt priors. In: Salberg A-B, Hardeberg JYngve, Jenssen R, editors. Image Analysis. Oslo, Norway: Springer-Verlag; 2009. 5. p. 520-529p. (Lecture Notes in Computer Science).
2008
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Decision trees in binary tomography for supporting the reconstruction of hv-convex connected images. In: Proceedings of the Advanced Concepts for Intelligent Vision Systems. Vol 5259. Juan-les-Pins, France: Springer; 2008. 4. p. 433-443p. (Lecture Notes in Computer Science; vol 5259).
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Determination of geometric features of binary images from their projections by using decision trees. In: Palágyi K, Bánhelyi B, Gergely T, Matievics I, editors. Conference of PhD Students in Computer Science. Volume of Extended Abstracts. Szeged, Hungary: University of Szeged; 2008. 2. 26.
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Reconstruction of binary images with few disjoint components from two projections. In: Bebis G, Boyle R, Parvin B, Koracin D, Remagnino P, Porikli F et al., editors. Advances in Visual Computing. Las Vegas, NV, USA: Springer Verlag; 2008. 1. p. 1147-1156p. (Lecture Notes in Computer Science).