A Measure of Directional Convexity Inspired by Binary Tomography

Péter Balázs, Zoltán Ozsvár, Tamás S. Tasi, László G. Nyúl

Research output: Contribution to journalArticle

7 Citations (Scopus)

Abstract

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.

Original languageEnglish
Pages (from-to)151-167
Number of pages17
JournalFundamenta Informaticae
Volume141
Issue number2-3
DOIs
Publication statusPublished - Oct 24 2015

Keywords

  • Binary Tomography
  • Convexity Measure
  • Digital Geometry
  • Reconstruction from Projections
  • hv-Convexity

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Algebra and Number Theory
  • Information Systems
  • Computational Theory and Mathematics

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