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Reseach Article

Combined Application of Color Histogram and Wavelet Techniques for Content based Image Retrieval

by Asheesh, A. K. Tripathi
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 94 - Number 10
Year of Publication: 2014
Authors: Asheesh, A. K. Tripathi
10.5120/16381-5897

Asheesh, A. K. Tripathi . Combined Application of Color Histogram and Wavelet Techniques for Content based Image Retrieval. International Journal of Computer Applications. 94, 10 ( May 2014), 34-40. DOI=10.5120/16381-5897

@article{ 10.5120/16381-5897,
author = { Asheesh, A. K. Tripathi },
title = { Combined Application of Color Histogram and Wavelet Techniques for Content based Image Retrieval },
journal = { International Journal of Computer Applications },
issue_date = { May 2014 },
volume = { 94 },
number = { 10 },
month = { May },
year = { 2014 },
issn = { 0975-8887 },
pages = { 34-40 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume94/number10/16381-5897/ },
doi = { 10.5120/16381-5897 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:17:18.007775+05:30
%A Asheesh
%A A. K. Tripathi
%T Combined Application of Color Histogram and Wavelet Techniques for Content based Image Retrieval
%J International Journal of Computer Applications
%@ 0975-8887
%V 94
%N 10
%P 34-40
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In this paper, we have proposed a novel method of content based image retrieval using combination of color histogram and wavelet techniques. We have used RGB color space to exploit the color features of image both for color histogram and wavelet decomposition of images. F-norm theory is used to extract features from wavelet transformed image. For histogram technique Euclidean distance is used and for wavelet technique F-norm theory based criteria is used to calculate similarity. We have shown that how individual techniques perform and have given approach to use both techniques in combination. Using recall rate it is shown that results have improved when both techniques are used together. We have also implemented the system in parallel and using speedup parameter it is shown that it has reduced the processing time making it practically useful in real world applications.

References
  1. http://en. wikipedia. org/wiki/Content-based_image_retrieval
  2. Felci Rajam1 and S. Valli; A Survey on Content Based Image Retrieval; Life Science Journal 2013
  3. Rui Y. & Huang T. S. , Chang S. F. "Image retrieval: current techniques, promising directions, and open issues". Journal of Visual Communication and Image Representation, 10, 39-62, 1999.
  4. Mrs. Y. M. Latha, Dr. B. C. Jinaga, V. S. K. Reddy;Content Based Color Image Retrieval via Wavelet Transforms , IJCSNS International Journal of Computer Science and Network Security.
  5. A Study of Color Histogram Based Image Retrieval Rishav Chakravarti, Xiannong Meng ; 2009 Sixth International Conference on Information Technology
  6. D. N. Verma, Vrinda Maru' and Bharti ;An Efficient Approach for Color ImageRetrieval Using Haar Wavelet; International Conference on Methods and Models in Computer Science , 2009
  7. Huihui Huang; Wei Huang; Zhigang Liu; Weirong Chen; Qingquan Qian; "Content-based color image retrieval via lifting scheme" Autonomous Decentralized Systems, 2005. ISADS Proceedings 2005.
  8. Michael Swain and Dana Ballard. Color indexing. International Journal of Computer Vision, 7(1):11{32, 1991.
  9. Markus Stricker and Michael Swain. The capacity of color histogram indexing. In Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, pages 704{708, 1994.
  10. Jain, Anil K. , and Aditya Vailaya. Image Retrieval Using Color And Shape. Great Britain: Elsevier Science Ltd
  11. Wavelets as features for object recognition; Anca Apatean, Alexandrina Rogozan , Simina Emerich, Abdelaziz Bensrjtair
  12. Tang, J. , Z. Chen, A. W. Fu, and D. W. Cheung, "Capabilities of Outlier Detection Schemes in Large Databases, Framework and Methodologies", Knowledge and Information Systems, 11(1): 45-84.
  13. http://en. wikipedia. org/wiki/Speedup
Index Terms

Computer Science
Information Sciences

Keywords

CBIR RGB Histogram Wavelets Haar Wavelet Parallel Threads Recall Rate etc