Notification: Our email services are now fully restored after a brief, temporary outage caused by a denial-of-service (DoS) attack. If you sent an email on Dec 6 and haven't received a response, please resend your email.
CFP last date
20 December 2024
Call for Paper
January Edition
IJCA solicits high quality original research papers for the upcoming January edition of the journal. The last date of research paper submission is 20 December 2024

Submit your paper
Know more
The week's pick
Responsive image
SFLA-Based Line Balancing and Task Optimization in Master-Slave Controlled Hanger Transportation Systems for Garment Production

Duc Hoang Nguyen
Random Articles
Reseach Article

Content Based Image Retrieval using Wavelet based MultiResolution Analysis

by Kalyanasundaram.K., Sanoj.C.S.
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 40 - Number 6
Year of Publication: 2012
Authors: Kalyanasundaram.K., Sanoj.C.S.
10.5120/4959-7216

Kalyanasundaram.K., Sanoj.C.S. . Content Based Image Retrieval using Wavelet based MultiResolution Analysis. International Journal of Computer Applications. 40, 6 ( February 2012), 14-18. DOI=10.5120/4959-7216

@article{ 10.5120/4959-7216,
author = { Kalyanasundaram.K., Sanoj.C.S. },
title = { Content Based Image Retrieval using Wavelet based MultiResolution Analysis },
journal = { International Journal of Computer Applications },
issue_date = { February 2012 },
volume = { 40 },
number = { 6 },
month = { February },
year = { 2012 },
issn = { 0975-8887 },
pages = { 14-18 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume40/number6/4959-7216/ },
doi = { 10.5120/4959-7216 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:27:49.219786+05:30
%A Kalyanasundaram.K.
%A Sanoj.C.S.
%T Content Based Image Retrieval using Wavelet based MultiResolution Analysis
%J International Journal of Computer Applications
%@ 0975-8887
%V 40
%N 6
%P 14-18
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Content Based Image Retrieval (CBIR) is an emerging area of engineering application focusing on algorithms and methods to extract image features from a query image and retrieve similar images from large archives. It has found extensive application in medical imaging for both retrieval and automatic archiving. In this paper it is proposed to extract features using wavelet based multiresolution analysis and measure the classification accuracy of Naive Bayes and K Nearest Neighbor (K-NN) algorithm.

References
  1. S. K. Chang, C. W. Yan, D. C. Dimitroff, and T. Arndt, "An intelligent image database system,"IEEE Trans. on Software Engineering, Vol.14, No.5, pp. 681-688, May 1988.
  2. A. M. Aisen, L. S. Broderick, H. Winer-Muram, C. E. Brodley, A. C. Kak, C. Pavlopoulou, J. Dy, C.-R.Shyu, A. Marchiori, “Automated storage and retrieval of thin-section CT images to assist diagnosis: system description and preliminary assessment”, Radiology 228:265-270, 2003.
  3. K. Rajakumar, K. Rajakumar, “An Integrated Approach for Medical Image Retrieval Using PCA and Energy Efficient Wavelet Transform”, European Journal of Scientific Research ISSN 1450-216X Vol.51 No.3 (2011), pp.340-348.
  4. Avi Kak and Christina Pavlopoulou, “Content-Based Image Retrieval from Large Medical Databases.” Proceedings of the First International Symposium on 3D Data Processing Visualization and Transmission (3DPVT.02). IEEE 2002.
  5. T. Lehmann, M. G¨uld, C. Thies, B. Fischer, K. Spitzer, D. Keysers, H. Ney, M. Kohnen, H. Schubert, and B. Wein. Content-based image retrieval in medical applications.
  6. Soo Beom Park, Jae Won Lee, Sang Kyoon Kim, “Content-based image classification using a neural network.” Pattern Recognition Letter, Vol 25, Issue 3, Feb 2004, Pages 287-300.
  7. Young Deok Chun; Nam Chul Kim; Ick Hoon Jang; , "Content-Based Image Retrieval Using Multiresolution Color and Texture Features," Multimedia, IEEE Transactions on , vol.10, no.6, pp.1073-1084, Oct. 2008.
  8. A. Chebira, Y. Barbotin, C. Jackson, T. Merryman, G. Srinivasa, R. Murphy, and J. Kova?cevi´c, “A multiresolution approach to automated classification of protein subcellular location images,” BMC Bioinformatics 8(210), 2007.
  9. S. Liu, C. F. Babbs, and E. J. Delp, “Multiresolution detection of speculated lesions in digital mammorgrams,” IEEE Trans. Image Process., vol. 10, pp. 874–884, Jun. 2001.
  10. T. Chang and C. -C. J. Kuo, “Texture analysis and classification with tree-structured wavelet transform,” IEEE Trans. Image Process., vol. 2, pp. 429–441, Oct. 1993.
  11. S. Liapis and G. Tziritas, “Color and texture image retrieval using chromaticity histograms and wavelet frames,” IEEE Trans. multimedia, vol. 6, pp. 676–686, Oct. 2004.
  12. Haar, Alfred (1910). "Zur Theorie der orthogonalen Funktionensysteme". Mathematische Annalen 69 (3): 331–371. doi:10.1007/BF01456326.
  13. Traina, A.J.M.; Castanon, C.A.B.; Traina, C., Jr.; , "MultiWaveMed: a system for medical image retrieval through wavelets transformations," Computer-Based Medical Systems, 2003. Proceedings. 16th IEEE Symposium , vol., no., pp. 150- 155, 26-27 June 2003.
  14. Wang JZ. Pathfinder: multiresolution region-based searching of pathology images using IRM. Proc AMIA Symp 2000; 883-887.
  15. Sylvain Contassot-Vivier, Giosue Lo Bosco, Chanh Dao Nguyen. Multiresolution approach for image processing.
Index Terms

Computer Science
Information Sciences

Keywords

Content Based Image Retrieval Multiresolution Haar Transform Naive Bayes k-Nearest Neighbor

Powered by PhDFocusTM