Multifractals, texture, and image analysis

Author

Vehel, Jacques Levy ; Mignot, Pascal ; Berroir, Jean-Paul

Author_Institution

INRIA, Le Chesnay, France

fYear

1992

fDate

15-18 Jun 1992

Firstpage

661

Lastpage

664

Abstract

Image analysis using texture and multifractal paradigms is addressed. Multifractal theory and its application to image description are discussed, and it is shown that this approach allows the discrete signal to be worked on directly. A system for texture classification that is based on a learning scheme and does not make use of any a priori model is introduced. Image segmentation is then considered, and the notion of mixed classes, which allows accurate detection of texture boundaries on complex images, is introduced

Keywords

fractals; image texture; complex images; discrete signal; image analysis; image description; image segmentation; learning scheme; mixed classes; multifractals; texture boundaries; texture classification; Coordinate measuring machines; Fractals; Geometry; Image analysis; Image segmentation; Image texture analysis; Meteorology; Performance evaluation; Physics; Signal analysis;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer Vision and Pattern Recognition, 1992. Proceedings CVPR '92., 1992 IEEE Computer Society Conference on

Conference_Location

Champaign, IL

ISSN

1063-6919

Print_ISBN

0-8186-2855-3

Type

conf

DOI

10.1109/CVPR.1992.223207

Filename

223207

Link To Document

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3206857