The Science and Information (SAI) Organization
  • Home
  • About Us
  • Journals
  • Conferences
  • Contact Us

Publication Links

  • IJACSA
  • Author Guidelines
  • Publication Policies
  • Digital Archiving Policy
  • Promote your Publication
  • Metadata Harvesting (OAI2)

IJACSA

  • About the Journal
  • Call for Papers
  • Editorial Board
  • Author Guidelines
  • Submit your Paper
  • Current Issue
  • Archives
  • Indexing
  • Fees/ APC
  • Reviewers
  • Apply as a Reviewer

IJARAI

  • About the Journal
  • Archives
  • Indexing & Archiving

Special Issues

  • Home
  • Archives
  • Proposals
  • Guest Editors
  • SUSAI-EE 2025
  • ICONS-BA 2025
  • IoT-BLOCK 2025

Future of Information and Communication Conference (FICC)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Computing Conference

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Intelligent Systems Conference (IntelliSys)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Future Technologies Conference (FTC)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact
  • Home
  • Archives
  • Indexing

DOI: 10.14569/IJARAI.2013.020211
PDF

Texture Based Image Retrieval Using Framelet Transform–Gray Level Co-occurrence Matrix(GLCM)

Author 1: S. Sulochana
Author 2: R.Vidhya

International Journal of Advanced Research in Artificial Intelligence(IJARAI), Volume 2 Issue 2, 2013.

  • Abstract and Keywords
  • How to Cite this Article
  • {} BibTeX Source

Abstract: This paper presents a novel content based image retrieval (CBIR) system based on Framelet Transform combined with gray level co-occurrence matrix (GLCM).The proposed method is shift invariant which captured edge information more accurately than conventional transform domain methods as well as able to handle images of arbitrary size. Current system uses texture as a visual content for feature extraction. First Texture features are obtained by computing the energy, standard deviation and mean on each sub band of the Framelet transform decomposed image .Then a new method as a combination of the Framelet transform-Gray level co-occurrence matrix (GLCM) is applied. The results of the proposed methods are compared with conventional methods. We have done the comparison of results of these two methods for image retrieval. Euclidean distance, Canberra distance, city black distance is used as similarity measure in the proposed CBIR system.

Keywords: Content Based image Retrieval (CBIR); Discrete Wavelet transform (DWT); Framelet Transform; Gray level- co occurrence matrix(GLCM)

S. Sulochana and R.Vidhya, “Texture Based Image Retrieval Using Framelet Transform–Gray Level Co-occurrence Matrix(GLCM)” International Journal of Advanced Research in Artificial Intelligence(IJARAI), 2(2), 2013. http://dx.doi.org/10.14569/IJARAI.2013.020211

@article{Sulochana2013,
title = {Texture Based Image Retrieval Using Framelet Transform–Gray Level Co-occurrence Matrix(GLCM)},
journal = {International Journal of Advanced Research in Artificial Intelligence},
doi = {10.14569/IJARAI.2013.020211},
url = {http://dx.doi.org/10.14569/IJARAI.2013.020211},
year = {2013},
publisher = {The Science and Information Organization},
volume = {2},
number = {2},
author = {S. Sulochana and R.Vidhya}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

IJACSA

Upcoming Conferences

IntelliSys 2025

28-29 August 2025

  • Amsterdam, The Netherlands

Future Technologies Conference 2025

6-7 November 2025

  • Munich, Germany

Healthcare Conference 2026

21-22 May 2026

  • Amsterdam, The Netherlands

Computing Conference 2026

9-10 July 2026

  • London, United Kingdom

IntelliSys 2026

3-4 September 2026

  • Amsterdam, The Netherlands

Computer Vision Conference 2026

15-16 October 2026

  • Berlin, Germany
The Science and Information (SAI) Organization
BACK TO TOP

Computer Science Journal

  • About the Journal
  • Call for Papers
  • Submit Paper
  • Indexing

Our Conferences

  • Computing Conference
  • Intelligent Systems Conference
  • Future Technologies Conference
  • Communication Conference

Help & Support

  • Contact Us
  • About Us
  • Terms and Conditions
  • Privacy Policy

© The Science and Information (SAI) Organization Limited. All rights reserved. Registered in England and Wales. Company Number 8933205. thesai.org