CFP last date
20 May 2024
Call for Paper
June Edition
IJCA solicits high quality original research papers for the upcoming June edition of the journal. The last date of research paper submission is 20 May 2024

Submit your paper
Know more
The week's pick
Responsive image
Enhancing Privacy Preservation: Multi-Attribute Protection with P-Sensitive K-Anonymity

Twinkle Patel Kiran Amin
Random Articles
Reseach Article

A Refinement: Better Classification of Images using LDA in Contrast with SURF and SVM for CBIR System

by Hemjot, Amitabh Sharma
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 117 - Number 16
Year of Publication: 2015
Authors: Hemjot, Amitabh Sharma
10.5120/20642-3349

Hemjot, Amitabh Sharma . A Refinement: Better Classification of Images using LDA in Contrast with SURF and SVM for CBIR System. International Journal of Computer Applications. 117, 16 ( May 2015), 31-33. DOI=10.5120/20642-3349

@article{ 10.5120/20642-3349,
author = { Hemjot, Amitabh Sharma },
title = { A Refinement: Better Classification of Images using LDA in Contrast with SURF and SVM for CBIR System },
journal = { International Journal of Computer Applications },
issue_date = { May 2015 },
volume = { 117 },
number = { 16 },
month = { May },
year = { 2015 },
issn = { 0975-8887 },
pages = { 31-33 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume117/number16/20642-3349/ },
doi = { 10.5120/20642-3349 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:59:35.792652+05:30
%A Hemjot
%A Amitabh Sharma
%T A Refinement: Better Classification of Images using LDA in Contrast with SURF and SVM for CBIR System
%J International Journal of Computer Applications
%@ 0975-8887
%V 117
%N 16
%P 31-33
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Content Based Image Retrieval or CBIR is the image retrieval process which is based on visual features including color, texture and shape. Image databases that are large in size and traditional indexing of images have proven to be less sufficient, more laborious and extremely time consuming which led to its development. Image retrieval and face recognition systems have grown significantly in the area of security systems. Retrieval of images has become an challenging issue in real world applications due to high dimensions of image collection. Therefore it has become a major issue and downfall for Content-Based image Retrieval (CBIR). Furthermore, it results in the inefficiency and degraded classification accuracy. A classifier in combination with the better dimensionality reduction and higher class discrimination can provide higher classification accuracy. This combination must result in a better classification rate. In the field of medical image annotation, research shows that SURF is a very strong tool to be used. Herein, an effort has been formulated to present an efficient algorithm based on SURF which is fast and robust interest point detector, SVM and LDA for further classification.

References
  1. Anna Wojnar, Antonio M. G. pinheiro "Annotation of Medical Images Using The Surf Descriptor"IEEE transactions on medical imaging, vol. 30, no. 3, March 2012, pp130-134
  2. Bob Zhang, B. V. K. Vijaya Kumar "Detecting Diabetes Mellitus and Nonproliferative Diabetic Retinopathy Using Tongue Color, Texture, and Geometry Features" ) IEEE Transactions On Biomedical Engineering, Vol. 61, no. 2, February 2014,pp491-501
  3. David G. Lowe," Object Recognition from Local Scale- Invariant Features", In Proceedings of the International Conference on Computer Vision - Volume 2, ICCV '99, Washington, DC, USA,. 1999
  4. Dong Hui, Han Dian Yuan "Research of Image Matching Algorithm Based on SURF Features" IEEE International Conference on Computer Science and Information Processing (CSIP), 2012
  5. Dr. Fuhui Long, Dr. Hongjiang Zhang and Prof. David Dagan Feng "Fundamentals of Content-Based Image Retrieval"
  6. Hatice Cinar Akakin and Metin N. Gurcan "Content-Based Microscopic Image Retrieval System for Multi-Image Queries" IEEE transactions on information technology in biomedicine, vol. 16, no. 4, July 2012,pp758-769
  7. Herbert Bay, Andreas Ess, Tinne Tuytelaars, and LucVan Gool," Speeded-Up Robust Features (SURF)", Comput. Vis. Image Underst. , 110, June 2008, pp 346–359.
  8. Jasper R. R. Uijlings, ArnoldW. M. Smeulders "Real-Time Visual Concept Classification" IEEE Transactions on Multimedia, vol. 12, no. 7, November 2010, pp 665-681.
  9. Jianlin Zhang, Wensheng Zou "Content-Based Image Retrieval Using Color and Edge Direction Features" ,IEEE 2010
  10. J. S. Taur, G. H. Lee, C. W. Tao "Segmentation of Psoriasis Vulgaris Images Using Multi resolution-Based Orthogonal Subspace Techniques" IEEE Transactions 0n Systems, Man, and Cybernetic part b: cybernetics, vol. 36, no. 2, April 2006,pp 390-402,
  11. Juan C. Caicedoa, Fabio A. Gonzáleza, Eduardo Rome rob "Content-based histopathology image retrieval using a kernel based semantic annotation framework "Journal of Biomedical Informatics, Volume 44, Issue 4, august2011,Pages 519–528.
  12. K. Velmurugan, Lt. Dr. S. SanthoshBaboo "Content-Based Image Retrieval using SURF and Color Moments"
  13. King-Shy Goh, Edward Y. Chang "Using One-Class and Two-Class SVMs for Multiclass Image Annotation "IEEE Transactions On Knowledge And Data Engineering, vol. 17, no. 10, October 2005,pp 1333-1346 Global Journal of Computer Science and Technology Volume 11 Issue 10 Version 1. 0 May 2011
Index Terms

Computer Science
Information Sciences

Keywords

CBIR SURF SVM LDA.

Powered by PhDFocusTM