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 - CHAP T1 - Hexagonal parallel thinning algorithms based on sufficient conditions for topology preservation T2 - Computational Modelling of Objects Represented in Images: Fundamentals, Methods and Applications III Y1 - 2012 A1 - Péter Kardos A1 - Kálmán Palágyi ED - Paolo Di Giamberardino ED - Daniela Iacoviello ED - Renato M Natal Jorge ED - Joao Manuel R S Taveres AB -Thinning is a well-known technique for producing skeleton-like shape features from digital

binary objects in a topology preserving way. Most of the existing thinning algorithms presuppose that the input

images are sampled on orthogonal grids.This paper presents new sufficient conditions for topology preserving

reductions working on hexagonal grids (or triangular lattices) and eight new 2D hexagonal parallel thinning

algorithms that are based on our conditions.The proposed algorithms are capable of producing both medial lines

and topological kernels as well.

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 - Topology Preserving Parallel Smoothing for 3D Binary Images T2 - Proceedings of the Computational Modeling of Objects Represented in Images (CMORI) Y1 - 2010 A1 - Gábor Németh A1 - Péter Kardos A1 - Kálmán Palágyi ED - Reneta P Barneva ED - Valentin E Brimkov ED - Herbert A Hauptman ED - Renato M Natal Jorge ED - João Manuel R S Tavares AB -

This paper presents a new algorithm for smoothing 3D binary images in a topology preserving way. Our algorithm is a reduction operator: some border points that are considered as extremities are removed. The proposed method is composed of two parallel reduction operators. We are to apply our smoothing algorithm as an iteration-by-iteration pruning for reducing the noise sensitivity of 3D parallel surface-thinning algorithms. An efficient implementation of our algorithm is sketched and its topological correctness for (26,6) pictures is proved. © 2010 Springer-Verlag.

JF - Proceedings of the Computational Modeling of Objects Represented in Images (CMORI) PB - Springer Verlag CY - Buffalo, USA VL - 6026 N1 - ScopusID: 77952401887doi: 10.1007/978-3-642-12712-0_26 ER -