CFP last date
20 May 2024
Reseach Article

Content-based Image Retrieval using Conflation of Wavelet Transformation and CIECAM02 Color Histogram

by Jeripothula Prudviraj, Rajesh Wadhvani, Manasi Gyanchandani
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 126 - Number 5
Year of Publication: 2015
Authors: Jeripothula Prudviraj, Rajesh Wadhvani, Manasi Gyanchandani
10.5120/ijca2015906052

Jeripothula Prudviraj, Rajesh Wadhvani, Manasi Gyanchandani . Content-based Image Retrieval using Conflation of Wavelet Transformation and CIECAM02 Color Histogram. International Journal of Computer Applications. 126, 5 ( September 2015), 15-20. DOI=10.5120/ijca2015906052

@article{ 10.5120/ijca2015906052,
author = { Jeripothula Prudviraj, Rajesh Wadhvani, Manasi Gyanchandani },
title = { Content-based Image Retrieval using Conflation of Wavelet Transformation and CIECAM02 Color Histogram },
journal = { International Journal of Computer Applications },
issue_date = { September 2015 },
volume = { 126 },
number = { 5 },
month = { September },
year = { 2015 },
issn = { 0975-8887 },
pages = { 15-20 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume126/number5/22548-2015906052/ },
doi = { 10.5120/ijca2015906052 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:16:39.656723+05:30
%A Jeripothula Prudviraj
%A Rajesh Wadhvani
%A Manasi Gyanchandani
%T Content-based Image Retrieval using Conflation of Wavelet Transformation and CIECAM02 Color Histogram
%J International Journal of Computer Applications
%@ 0975-8887
%V 126
%N 5
%P 15-20
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In this paper, a novel image retrieval technique based on the combination of Haar wavelet transformation and CIECAM02 color histogram (CH) have been proposed. In color based image retrieval, color histogram is one of the most repeatedly used image features and it is used at a great extent in content-based image retrieval (CBIR) systems as a significant color feature. The color histogram unchanged by translation and rotation. The local characteristics and texture features of an image are extracted by wavelet transformation. On conflation of wavelet transformation and color histogram new algorithm has been proposed. One may select a query image perceived to be similar to the visualized target image. A set of images similar to the query is then returned from the database. The final experimental results show that the proposed technique gives better performance than the other schemes, in terms of retrieval time.

References
  1. M. Singha, K. Hemachandran, A.Paul, “Content based image retrieval using the combination of the fast wavelet transformation and the color hsitogram”, IET Image Process., 2012, Vol. 6, Iss. 9, pp. 1221–1226.
  2. Smeulders, A.W.M., Worring, M., Santini, S., Gupta, A., Jain, R.: ‘Content based image retrieval at the end of the early years’, IEEE Trans. Pattern Anal. Mach. Intell., 2000, 22, (12), pp. 1349–1380.
  3. Zhenhua Zhang, Wenhui Li, “An improving technique of color histogram in segmentation based image retrieval ”, in 2009 Fifth International Conference on Information Assurance and Security.
  4. Subrahmanyam Murala, R. P. Maheshwari, Member, IEEE, and R. Balasubramanian, Member, IEEE, “Local Tetra Patterns: A New Feature Descriptor for Content-Based Image Retrieval”, in IEEE TRANSACTIONS ON IMAGE PROCESSING, VOL. 21, NO. 5, MAY 2012.
  5. Gerald Schaefer Department of Computer Science Loughborough University Loughborough, U.K., “An Introduction to Content-based Image Retrieval”.
  6. Junwei Han1, Stephen J. McKenna2, “Query-dependent metric learning for adaptive, content-based image browsing and retrieval”,IET Image Process., 2014, Vol. 8, Iss. 10, pp. 610–618.
  7. M. Sarifuddin, Rokia Missaoui, A New Perceptually Uniform Color Space with Associated Color Similarity Measure for ContentBased Image and Video Retrieval”, Universit ´e du Qu´ebec en Outaouais Qu´ebec Canada.
  8. Eleftherios Tiakas, Dimitrios Rafailidis, Anastasios Dimou, and Petros Daras, Member, IEEE, “MSIDX: Multi-Sort Indexing for Efficient Content-Based Image Search and Retrieval”, IEEE TRANSACTIONS ON MULTIMEDIA, VOL. 15, NO. 6, OCTOBER 2013.
  9. Quellec, G., Lamard, M., Cazuguel, G., Cochener, B., Roux, C.: ‘Fast wavelet-based image characterization for highly adaptive image retrieval’, IEEE Trans. Image Process., 2011.
  10. Xuanping Zhang, Liang Cui, Liping Shao , “A Fast Semi-fragile Watermarking Scheme Based on quantizing the Weighted Mean of Integer Haar Wavelet Coefficients, Xi’an Jiaotong University Xi’an, China.
  11. Dr.T.Santhana, 2MS.S.Gomathi, “Representing a image using a Haar-wavelet Transformation for Human Parts Detection”, ICICES2014 - S.A.Engineering College, Chennai, Tamil Nadu, India.
  12. Miss. Priti S. Sanjekar, Prof. Priyadarshan S. Ohabe, “Fingerprint Verification Using Haar Wavelet”, 978-1-4244-6349-7/10/$26.00 @2010 IEEE.
  13. Ming Chen1, Yang Wang2, Xiaoxiang Zou2, Shupeng Wang3, Guangjun Wu3, “A DUPLICATE IMAGE DEDUPLICATION APPROACH VIA HAAR WAVELET TECHNOLOGY”, Proceedings of IEEE CCIS2012.
  14. B.Monisha, M.Ramkumar , M.V.Priya, A.Jenifer Philomina, D.Parthiban, S.Suganya, N.R.Raajan. , “ Design and Implementation of Orthogonal Based Haar Wavelet Division Multiplexing For 3GPP Networks”, 2012 International Conference on Computer Communication and Informatics (ICCCI -2012), Jan. 10 – 12, 2012, Coimbatore, INDIA.
  15. Adnan Abou Nabout, Bernd Tibken, “Object Shape Description Using Haar Wavelet Functions”, University of Wuppertal, Wuppertal, Germany.
  16. Lidija Mandic , Kresimir Delac, Mislav Grgic, “Corresponding Colors: Visual and Predictive Data”, 49th International Symposium ELMAR-2007, 12-14 September 2007, Zadar, Croatia.
  17. R. Missaoui, M. Sarifuddin and J. Vaillancourt, “Similarity measures for efficient content-based image Retrieval”, IEE Proceedings online no. 20045192.
  18. Minsung Kang, Bongjoe Kim, Kar-Ann Toh, and Kwanghoon Sohn, “Surrounding Adaptive Color Image Enhancement based on CIECAM02”, 2008 IEEE International Conference on Systems, Man and Cybernetics (SMC 2008).
  19. Ping He Junsheng Shi* Xiaoqiao Huang Qiong Li, “Investigation on Color Shifts for Different Gamma of Display System in CIECAM02-Based Uniform Color Space”, 2008 International Conference on Computer Science and Software Engineering.
  20. Olivier Tulet, Mohamed-Chaker Larabi and Christine Fernandez-Maloigne, “Image Rendering Based on a Spatial Extension of the CIECAM02”, SIC lab, University of Poitiers.
  21. Hongyong Jin1,Xiuping Zhao2,Hongfang Liu2, “Testing of the Uniformity of Color Appearance Space”, 2009 World Congress on Computer Science and Information Engineering.
  22. Patel Janakkumar Baldevbhai1, R. S. Anand2, “Color Image Segmentation for Medical Images using L*a*b* Color Space”, IOSR Journal of Electronics and Communication Engineering (IOSRJECE) ISSN: 2278-2834 Volume 1, Issue 2 (May-June 2012), PP 24-45.
  23. Mark D. Fairchild, Color Appearance Models: CIECAM02 and Beyond”, IS&T/SID 12th Color Imaging Conference.
  24. Swain, M., Ballard, D.: ‘Color indexing’, Int. J. Comput. Vis., 1991, 7, (1), pp. 11–32.
  25. James Z. Wang Research Group: http://wang.ist.psu.edu/docs/related/, accessed August 2011.
Index Terms

Computer Science
Information Sciences

Keywords

Color Histogram Haar wavelet Transformation Content-based image retrieval (CBIR) Color histogram CIECAM02.