The Open UniversitySkip to content
 

Genetic algorithms for automatic feature selection in a textureclassification system

Stolpmann, Alexander and Dooley, Laurence S. (1998). Genetic algorithms for automatic feature selection in a textureclassification system. In: 4th International Conference on Signal Processing Proceedings (Yüan, Pao-tsung and Tang, Xiaofang eds.), IEEE Press, Piscataway, New Jersey, USA,, pp. 1229–1232.

Full text available as:
[img]
Preview
PDF (Not Set) - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
Download (427Kb)
DOI (Digital Object Identifier) Link: http://doi.org/10.1109/ICOSP.1998.770840
Google Scholar: Look up in Google Scholar

Abstract

This paper describes the use of genetic algorithms as feature selectors in a texture classification system. This is part of a system developed within a research project concerning the classification of genuine texture. An attempt is made to underline why an automatic feature selector is a useful part of the texture classification system. Furthermore a way of including the genetic algorithms into the system and the necessary feedback structure is explained

Item Type: Conference Item
ISBN: 0-7803-4325-5, 978-0-7803-4325-2
Keywords: feature extraction; feedback; genetic algorithms; image classification; image texture; automatic feature selection; feature selectors; feedback structure; genetic algorithms; texture classification system
Academic Unit/Department: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Computing and Communications
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Interdisciplinary Research Centre: Centre for Research in Computing (CRC)
Item ID: 16640
Depositing User: Laurence Dooley
Date Deposited: 02 Jun 2009 14:04
Last Modified: 04 Oct 2016 11:24
URI: http://oro.open.ac.uk/id/eprint/16640
Share this page:

Altmetrics

Scopus Citations

Download history for this item

These details should be considered as only a guide to the number of downloads performed manually. Algorithmic methods have been applied in an attempt to remove automated downloads from the displayed statistics but no guarantee can be made as to the accuracy of the figures.

▼ Automated document suggestions from open access sources

Actions (login may be required)

Policies | Disclaimer

© The Open University   + 44 (0)870 333 4340   general-enquiries@open.ac.uk