Texture: Plus ça change, …

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

Abstract

This paper presents an edge finder for textured images. Using rough constraints on the size of image regions, it estimates the local amount of variation in image values. These estimates are constructed so that they do not rise at boundaries. This enables subsequent smoothing and edge detection to find coarse-scale boundaries to the full available resolution, while ignoring changes within uniformly textured regions. This method extends easily to vector valued images, e.g. 3-color images or texture features. Significant groups of outlier values are also identified, enabling the edge finder to detect cracks separating regions as well as certain changes in texture phase.

Original languageEnglish (US)
Title of host publicationComputer Vision - ECCV 1992 - 2nd European Conference on Computer Vision, Proceedings
EditorsGiulio Sandini
PublisherSpringer-Verlag Berlin Heidelberg
Pages151-159
Number of pages9
ISBN (Print)9783540554264
DOIs
StatePublished - Jan 1 1992
Externally publishedYes
Event2nd European Conference on Computer Vision, ECCV 1992 - Santa Margherita Ligure, Italy
Duration: May 19 1992May 22 1992

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume588 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other2nd European Conference on Computer Vision, ECCV 1992
CountryItaly
CitySanta Margherita Ligure
Period5/19/925/22/92

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Fingerprint Dive into the research topics of 'Texture: Plus ça change, …'. Together they form a unique fingerprint.

  • Cite this

    Fleck, M. M. (1992). Texture: Plus ça change, …. In G. Sandini (Ed.), Computer Vision - ECCV 1992 - 2nd European Conference on Computer Vision, Proceedings (pp. 151-159). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 588 LNCS). Springer-Verlag Berlin Heidelberg. https://doi.org/10.1007/3-540-55426-2_17