Binary image reconstruction from two projections and skeletal information

Norbert Hantos, Péter Balázs, K. Palágyi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Citations (Scopus)

Abstract

In binary tomography, the goal is to reconstruct binary images from a small set of their projections. However, especially when only two projections are used, the task can be extremely underdetermined. In this paper, we show how to reduce ambiguity by using the morphological skeleton of the image as a priori. Three different variants of our method based on Simulated Annealing are tested using artificial binary images, and compared by reconstruction time and error.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages263-273
Number of pages11
Volume7655 LNCS
DOIs
Publication statusPublished - 2012
Event15th International Workshop on Combinatorial Image Analysis, IWCIA 2012 - Austin, TX, United States
Duration: Nov 28 2012Nov 30 2012

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7655 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other15th International Workshop on Combinatorial Image Analysis, IWCIA 2012
CountryUnited States
CityAustin, TX
Period11/28/1211/30/12

Fingerprint

Binary images
Binary Image
Image Reconstruction
Image reconstruction
Projection
Tomography
Simulated annealing
Skeleton
Simulated Annealing
Binary
Ambiguity

Keywords

  • Binary tomography
  • Morphological skeleton
  • Reconstruction
  • Simulated annealing

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Hantos, N., Balázs, P., & Palágyi, K. (2012). Binary image reconstruction from two projections and skeletal information. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7655 LNCS, pp. 263-273). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7655 LNCS). https://doi.org/10.1007/978-3-642-34732-0_20

Binary image reconstruction from two projections and skeletal information. / Hantos, Norbert; Balázs, Péter; Palágyi, K.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 7655 LNCS 2012. p. 263-273 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7655 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Hantos, N, Balázs, P & Palágyi, K 2012, Binary image reconstruction from two projections and skeletal information. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 7655 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 7655 LNCS, pp. 263-273, 15th International Workshop on Combinatorial Image Analysis, IWCIA 2012, Austin, TX, United States, 11/28/12. https://doi.org/10.1007/978-3-642-34732-0_20
Hantos N, Balázs P, Palágyi K. Binary image reconstruction from two projections and skeletal information. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 7655 LNCS. 2012. p. 263-273. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-642-34732-0_20
Hantos, Norbert ; Balázs, Péter ; Palágyi, K. / Binary image reconstruction from two projections and skeletal information. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 7655 LNCS 2012. pp. 263-273 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
@inproceedings{a3f9eadbebd940b69086efb6593dceb6,
title = "Binary image reconstruction from two projections and skeletal information",
abstract = "In binary tomography, the goal is to reconstruct binary images from a small set of their projections. However, especially when only two projections are used, the task can be extremely underdetermined. In this paper, we show how to reduce ambiguity by using the morphological skeleton of the image as a priori. Three different variants of our method based on Simulated Annealing are tested using artificial binary images, and compared by reconstruction time and error.",
keywords = "Binary tomography, Morphological skeleton, Reconstruction, Simulated annealing",
author = "Norbert Hantos and P{\'e}ter Bal{\'a}zs and K. Pal{\'a}gyi",
year = "2012",
doi = "10.1007/978-3-642-34732-0_20",
language = "English",
isbn = "9783642347313",
volume = "7655 LNCS",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
pages = "263--273",
booktitle = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

}

TY - GEN

T1 - Binary image reconstruction from two projections and skeletal information

AU - Hantos, Norbert

AU - Balázs, Péter

AU - Palágyi, K.

PY - 2012

Y1 - 2012

N2 - In binary tomography, the goal is to reconstruct binary images from a small set of their projections. However, especially when only two projections are used, the task can be extremely underdetermined. In this paper, we show how to reduce ambiguity by using the morphological skeleton of the image as a priori. Three different variants of our method based on Simulated Annealing are tested using artificial binary images, and compared by reconstruction time and error.

AB - In binary tomography, the goal is to reconstruct binary images from a small set of their projections. However, especially when only two projections are used, the task can be extremely underdetermined. In this paper, we show how to reduce ambiguity by using the morphological skeleton of the image as a priori. Three different variants of our method based on Simulated Annealing are tested using artificial binary images, and compared by reconstruction time and error.

KW - Binary tomography

KW - Morphological skeleton

KW - Reconstruction

KW - Simulated annealing

UR - http://www.scopus.com/inward/record.url?scp=84869986820&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84869986820&partnerID=8YFLogxK

U2 - 10.1007/978-3-642-34732-0_20

DO - 10.1007/978-3-642-34732-0_20

M3 - Conference contribution

SN - 9783642347313

VL - 7655 LNCS

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 263

EP - 273

BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

ER -