Morphological hat-transform scale spaces and their use in texture classification

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

6 Citations (Scopus)
311 Downloads (Pure)

Abstract

In this paper we present a multi-scale morphological method for use in texture classification. A connected operator similar to the morphological hat-transform is defined, and two scale-space representations are built. The most important features are extracted from the scale spaces by unsupervised cluster analysis, and the resulting pattern vectors provide the input of a decision tree classifier. We obtain 93.5 % correct classification for the Brodatz texture database.
Original languageEnglish
Title of host publication2003 INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, VOL 1, PROCEEDINGS
Place of PublicationNEW YORK
PublisherUniversity of Groningen, Johann Bernoulli Institute for Mathematics and Computer Science
Pages329-332
Number of pages4
ISBN (Print)0-7803-7750-8
Publication statusPublished - 2003
EventIEEE International Conference on Image Processing - , Spain
Duration: 14-Sept-200317-Sept-2003

Publication series

NameIEEE International Conference on Image Processing (ICIP)
PublisherIEEE
ISSN (Print)1522-4880

Other

OtherIEEE International Conference on Image Processing
Country/TerritorySpain
Period14/09/200317/09/2003

Fingerprint

Dive into the research topics of 'Morphological hat-transform scale spaces and their use in texture classification'. Together they form a unique fingerprint.

Cite this