This Article 
   
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
Image Content-Based Retrieval Using Chromaticity Moments
September/October 2003 (vol. 15 no. 5)
pp. 1069-1072
ASCII Text
x 
 
George Paschos, Ivan Radev, Nagarajan Prabakar, "Image Content-Based Retrieval Using Chromaticity Moments," IEEE Transactions on Knowledge and Data Engineering, vol. 15, no. 5, pp. 1069-1072, September/October, 2003.
 
 
BibTex
x
 
@article{ 10.1109/TKDE.2003.1232264,
author = {George Paschos and Ivan Radev and Nagarajan Prabakar},
title = {Image Content-Based Retrieval Using Chromaticity Moments},
journal ={IEEE Transactions on Knowledge and Data Engineering},
volume = {15},
number = {5},
issn = {1041-4347},
year = {2003},
pages = {1069-1072},
doi = {http://doi.ieeecomputersociety.org/10.1109/TKDE.2003.1232264},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - JOUR
JO - IEEE Transactions on Knowledge and Data Engineering
TI - Image Content-Based Retrieval Using Chromaticity Moments
IS - 5
SN - 1041-4347
SP1069
EP1072
EPD - 1069-1072
A1 - George Paschos,
A1 - Ivan Radev,
A1 - Nagarajan Prabakar,
PY - 2003
KW - Image retrieval
KW - color processing
KW - histogram
KW - chromaticity
KW - color spaces.
VL - 15
JA - IEEE Transactions on Knowledge and Data Engineering
ER -
 

Abstract—A number of different approaches have been recently presented for image retrieval using color features. Most of these methods use the color histogram or some variation of it. If the extracted information is to be stored for each image, such methods may require a significant amount of space for storing the histogram, depending on a given image's size and content. In the method proposed in this paper, only a small number of features, called chromaticity moments, are required to capture the spectral content (chrominance) of an image. The proposed method is based on the concept of the chromaticity diagram and extracts a set of two-dimensional moments from it to characterize the shape and distribution of chromaticities of the given image. This representation is compact (only a few chromaticity moments per image are required) and constant (independent of image size and content), while its retrieval effectiveness is comparable to using the full chromaticity histogram.

[1] M.J. Swain and B.H. Ballard, “Color Indexing,” Int'l J. Computer Vision, vol. 7, no. 1, pp. 11-32, 1991.
[2] W. Niblack, R. Barber, W. Equitz, M. Flickner, E. Glasman, D. Petkovic, P. Yanker, and C. Faloutsos, The QBIC Project: Querying Images by Content Using Color, Texture, and Shape IBM Research J., 9203(81511), 1993.
[3] V.E. Ogle, “CHABOT—Retrieval from a Relational Database of Images,” Computer, vol. 28, no. 9, pp. 40-48, Sept. 1995.
[4] A. Pentland, R.W. Picard, and S. Sclaroff, “Photobook: Content-Based Manipulation of Image Databases,” Int'l J. Computer Vision, vol. 18, no. 3, pp. 233-254, 1996.
[5] G. Pass, R. Zabih, and J. Miller, “Comparing Images Using Color Coherence Vectors,” Proc. ACM Multimedia '96, pp. 65-73, 1996.
[6] R.S. Gray, Content-Based Image Retrieval: Color and Edges Technical report #95-252, Dartmouth Univ., Dept. of Computer Science, 1995.
[7] T. Gevers and A.W.M. Smeulders, Content-Based Image Retrieval by Viewpoint-Invariant Color Indexing Image And Vision Computing, vol. 17, no. 7, pp. 475-488, 1999.
[8] M.S. Kankanhalli, B.M. Mehtre, and H.Y. Huang, Color and Spatial Feature for Content-Based Image Retrieval Pattern Recognition Letters, vol. 20, no. 1, pp. 109-118, 1999.
[9] S.K. Choubey and V.V. Raghavan, Generic and Fully Automatic Content-Based Image Retrieval Using Color Pattern Recognition Letters, vol. 18, nos. 11-13, pp. 1233-1240, 1997.
[10] I.K. Park, I.D. Yun, and S.U. Lee, Color Image Retrieval Using Hybrid Graph Representation Image And Vision Computing, vol. 17, no. 7, pp. 465-474, 1999.
[11] B.M. Mehtre, M.S. Kankanhalli, A.D. Narasimhalu, and G.C. Man, “Color Matching for Image Retrieval,” Pattern Recognition Letters, vol. 16, pp. 325-331, 1995.
[12] A. Jain and G. Healey, "A Multiscale Representation Including Opponent Color Features for Texture Recognition," IEEE Trans. Image Processing, vol. 7, no. 1, pp. 124-128, Jan. 1998.
[13] T. Randen and J.H. Husoy, Image Content Search by Color and Texture Properties Proc. Int'l Conf. Image Processing, pp. 580-583, 1997.
[14] F. Ennesser and G. Medioni, “Finding Waldo, or Focus of Attention Using Local Color Information,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 17, no. 8, pp. 805-809, Aug. 1995.
[15] J.R. Smith and S.-F. Chang, Local Color and Texture Extraction and Spatial Query IEEE Proc. Int'l Conf. Image Processing, 1996.
[16] J. Smith and S.-F. Chang, Tools and Techniques for Color Image Retrieval SPIE Proc., vol. 2670, pp. 29-40, 1996.
[17] M. De Marsicoi, L. Cinque, and S. Levialdi, Indexing Pictorial Documents by Their Content: A Survey of Current Techniques Image and Vision Computing, vol. 15, no. 2, pp. 119-141, 1997.
[18] J.R. Smith, Integrated Spatial and Feature Image Systems: Retrieval, Compression and Analysis PhD thesis, Columbia Univ., 1997.
[19] M. Stricker and M. Orengo, Similarity of Color Images Proc. SPIE: Storage and Retrieval for Image and Video Databases III, vol. 2420, pp. 381-392, 1995.
[20] M.K. Mandal, T. Aboulnasr, and S. Panchanathan, “Image Indexing Using Moments and Wavelets,” IEEE Trans. Consumer Electronics, vol. 42, no. 3, pp. 557-565, 1996.
[21] G.W. Wyszecki and S.W. Stiles, Color Science: Concepts and Methods, Quantitative Data and Formulas. John Wiley and Sons, 1982.
[22] http://www-white.media.mit.edu/vismod/imagery/ visiontexturevistex.html, 2003.
[23] Y.H. Gong, G. Proietti, and C. Faloutsos, "Image Indexing and Retrieval Based on Human Perceptual Color Clustering," Proc. Computer Vision and Pattern Recognition, IEEE CS Press, Los Alamitos, Calif., 1998, pp. 578-583.

Index Terms:
Image retrieval, color processing, histogram, chromaticity, color spaces.
Citation:
George Paschos, Ivan Radev, Nagarajan Prabakar, "Image Content-Based Retrieval Using Chromaticity Moments," IEEE Transactions on Knowledge and Data Engineering, vol. 15, no. 5, pp. 1069-1072, Sept.-Oct. 2003, doi:10.1109/TKDE.2003.1232264
Usage of this product signifies your acceptance of the Terms of Use.