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Content available remote Scale Invariance in Projection Selection Using Binary Tomography
Lékó Gábor, Balázs Péter
Fundamenta Informaticae
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2020
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Vol. 172, nr 2
129--142
EN
In this paper, we propose two strategies of reducing the amount of data needed for binary tomographic reconstructions. We study how the direction dependency changes by reducing the resolution of an image and we point out how to specify the most informative angles for the original image using its downscaled version. We also show how to predict the final acceptable resolution. Applications of the proposed strategies are also mentioned.
2
Content available remote A Measure of Directional Convexity Inspired by Binary Tomography
Balázs P., Ozsvár Z., Tasi T. S., Nyúl L. G.
Fundamenta Informaticae
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2015
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Vol. 141, nr 2/3
151--167
EN
Inspired by binary tomography, we present a measure of directional convexity of binary images combining various properties of the configuration of 0s and 1s in the binary image. The measure can be supported by proper theory, is easy to compute, and as shown in our experiments, behaves intuitively. The measure can be useful in numerous applications of digital image processing and pattern recognition, and especially in binary tomography. We show in detail an application of this latter one, by providing a novel reconstruction algorithm for almost hv-convex binary images. We also present experimental results and mention some of the possible generalizations of the measure.
3
Content available remote Random Generation of hv-Convex Polyominoes with Given Horizontal Projection
Hantos N., Balázs P.
Fundamenta Informaticae
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2014
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Vol. 135, nr 1/2
103--115
EN
We provide a quadratic-time algorithm for generating hv-convex polyominoes according to a given horizontal projection. The method can be used to generate hv-convex polyominoes with the prescribed projection and with a fixed or arbitrary horizontal dimension, from a uniform random distribution.
4
Content available remote Aligning Projection Images from Binary Volumes
Bleichrodt F., de Beenhouwer J., Sijbers J., Batenburg K. J.
Fundamenta Informaticae
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2014
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Vol. 135, nr 1/2
21--42
EN
In tomography, slight differences between the geometry of the scanner hardware and the geometric model used in the reconstruction lead to alignment artifacts. To exploit high-resolution detectors used in many applications of tomography, alignment of the projection data is essential. Markerless alignment algorithms are the preferred choice over alignment with markers, in case a fully automatic tomography pipeline is required. Moreover, marker based alignment is often not feasible or even possible. At the same time, markerless alignment methods often fail in scenarios where only a small number of projections are available. In this case, the angular separation between projection images is large and therefore the correlation between them is low. This is a property that most markerless algorithms rely on. The intermediate reconstruction problem of alignment by projection matching is highly underdetermined in the limited data case. Therefore, we propose a projection matching method that incorporates prior knowledge of the ground truth. We focus on reconstructing binary volumes. A discrete tomography algorithm is employed to generate intermediate reconstructions. This type of reconstruction algorithm does not rely heavily on correlated projection images. Our numerical results suggest that alignment using discrete tomography projection matching produces much better results in the limited angle case, when compared to a projection matching method that employs an algebraic reconstruction method.
5
Content available remote The Reconstruction of Polyominoes from Horizontal and Vertical Projections and Morphological Skeleton is NP-complete
Hantos N., Balázs P.
Fundamenta Informaticae
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2013
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Vol. 125, nr 3/4
343--359
EN
Reconstruction of binary images from their projections is one of the main tasks in many image processing areas, therefore determining the computational complexity of those problems is essential. The reconstruction complexity is highly dependent on the requirements of the image. In this paper, we will show that the reconstruction is NP-complete if the horizontal and vertical projections and the morphological skeleton of the image are given, and it is supposed that the image is 4-connected.
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