Jelenlegi hely
Publications of Péter Balázs
2013
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Restoration of blurred binary images using discrete tomography. In: Blanc-Talon J, Kasinski A, Philips W, Popescu D, Scheunders P, editors. Advanced Concepts for Intelligent Vision Systems (ACIVS). Berlin; Heidelberg; New York; London; Paris; Tokyo: Springer Verlag; 2013. 8. p. 80-90p. (LNCS).
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Dynamic angle selection in binary tomography. COMPUTER VISION AND IMAGE UNDERSTANDING. 2013;117(4):306-318.
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An empirical study of reconstructing hv-convex binary matrices from horizontal and vertical projections. ACTA CYBERNETICA-SZEGED. 2013;21:149-163.
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Bináris képek rekonstrukciója két vetületből és morfológiai vázból. In: Czúni L, editor. A Képfeldolgozók és Alakfelismerők Társaságának konferenciája - KÉPAF 2013. Veszprém: NJSZT-KÉPAF; 2013. 1. p. 182-193p.
2012
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Binary image reconstruction from two projections and skeletal information. In: Barneva RP, Brimkov VE, Aggarwal JK, editors. Combinatorial Image Analysis. Berlin; Heidelberg; New York; London; Paris; Tokyo: Springer Verlag; 2012. 2. p. 263-273p. (Lecture Notes in Computer Science).
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Solving binary tomography from morphological skeleton via optimization. In: Veszprém Optimization Conference: Advanced Algorithms (VOCAL). Veszprém: University of Pannonia; 2012. 4. 42.
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An optimization-based reconstruction algorithm for multivalued discrete tomography. In: Veszprém Optimization Conference: Advanced Algorithms (Vocal). Veszprém: University of Pannonia; 2012. 3. p. 39-40p.
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Extracting geometrical features of discrete images from their projections. Szeged: University of Szeged, Institute of Informatics; 2012.
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A novel optimization-based reconstruction algorithm for multivalued discrete tomography. Szeged: University of Szeged, Institute of Informatics; 2012.
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Machine learning as a preprocessing phase in discrete tomography. In: Köthe U, Montanvert A, Soille P, editors. Applications of Discrete Geometry and Mathematical Morphology (WADGMM). Berlin; Heidelberg; New York; London; Paris; Tokyo: Springer Verlag; 2012. 1. p. 109-124p. (Lecture Notes in Computer Science).