Contourlet transform and support vector machines for image analysis and processing

Stamos Katsigiannis

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

Abstract

In this work, a method for image analysis and processing and its application in natural and real medical images is presented. The Contourlet Transform (CT) was used to extract statistical texture features from texture images and Support Vector Machines (SVMs) were utilized for the classification process. A variety of filter and parameter combinations were tested in the experimental procedure in order to assess the efficiency of the method. This image analysis and processing procedure was applied to natural images taken from the publicly available Vistex library, and to real thyroid ultrasound (US) images. The evaluation of experimental results demonstrate the CT’s potential in feature extraction and shows that CT based texture features can be successfully utilized for texture representation.
Original languageEnglish
Title of host publication1st International Conference for undergraduate and graduate students in Informatics and Related Applications
Subtitle of host publicationEUREKA! 2010
Number of pages10
Publication statusPublished - 1 Oct 2010
Event1st International Conference for Undergraduate and Postgraduate students in Computer Engineering, Informatics, related technologies and Applications - Patras - Ancient Olympia, Greece
Duration: 15 Oct 201016 Oct 2010
http://www.uom.gr/modules.php?op=modload&name=News&file=article&tmima=1&categorymenu=7&sid=3465

Conference

Conference1st International Conference for Undergraduate and Postgraduate students in Computer Engineering, Informatics, related technologies and Applications
Abbreviated titleEUREKA! 2010
Country/TerritoryGreece
CityPatras - Ancient Olympia
Period15/10/1016/10/10
Internet address

Keywords

  • contourlet transform
  • feature extraction
  • texture analysis
  • ultrasound images
  • htyroid
  • support vector machines

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