An Unsupervised Optimization of Structuring Elements for Noise Removal Using GA

• OKUNO Hiroyuki

  Faculty of Engineering Science, Kansai University

• HANADA Yoshiko

  Faculty of Engineering Science, Kansai University

• MUNEYASU Mitsuji

  Faculty of Engineering Science, Kansai University

• ASANO Akira

  Graduate School of Engineering, Hiroshima University

Abstract

In this paper we propose an unsupervised method of optimizing structuring elements (SEs) used for impulse noise reduction in texture images through the opening operation which is one of the morphological operations. In this method, a genetic algorithm (GA), which can effectively search wide search spaces, is applied and the size of the shape of the SE is included in the design variables. Through experiments, it is shown that our new approach generally outperforms the conventional method.

Journal

• IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences

  IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences E93-A (11), 2196-2199, 2010

  The Institute of Electronics, Information and Communication Engineers

Keywords

• morphological filter
• structure element
• genetic algorithm

Details

• CRID: 1390282681288508288
• NII Article ID: 10027985033
• NII Book ID: AA10826239
• DOI: 10.1587/transfun.e93.a.2196
• ISSN: 17451337
• ISSN: 09168508
• Web Site: http://www.jstage.jst.go.jp/article/transfun/E93.A/11/E93.A_11_2196/_pdf
• Text Lang: en
• Data Source:
  • JaLC
  • Crossref
  • CiNii Articles
  • KAKEN
• Abstract License Flag: Disallowed