Content-based image retrieval via the multiresolution wavelet features of interest
Inhaltsverzeichnis
Referenz
T.-W. Chiang and T.-W. Tsai: Content-based image retrieval via the multiresolution wavelet features of interest. J. Inf. Technol. Appl., vol. 1, no. 3, pp. 205-214, 2006
DOI
Abstract
For the purpose of efficiently and effectively retrieving the desired images from a large image database, the development of a user-friendly image retrieval system is indispensable. In this paper, we propose a contentbased image retrieval method based on the discrete wavelet transform (DWT) that is possessed of the superiority in multiresolution analysis and spatial-frequency localization. Further, to bridge the gap between the retrieving results and the users’ expectation, we developed an interactive user interface such that the users can adjust the weights for each wavelet feature according to their expectations. Then, the system will retrieve the images that are most satisfied to the users’ need from the image database via the selected multiresolution wavelet features of interest. We have performed experiments on a database with 1000 images and the results show the effectiveness of our approach.
Extended Abstract
Bibtex
@article{
author = {T.-W. Chiang and T.-W. Tsai},
title = {Content-based image retrieval via the multiresolution wavelet features of interest},
journal = {J. Inf. Technol. Appl.},
volume = {1},
number = {3},
pages = {205-214},
year = {2006},
doi={},
url={http://jita.csi.chu.edu.tw/Jita_web/publish/vol1_num3/08-20060046-text-sec.pdf http://de.evo-art.org/index.php?title=Content-based_image_retrieval_via_the_multiresolution_wavelet_features_of_interest},
}
Used References
[1] Gudivada, V. and Raghavan, V., 1995, "Content- Based Image Retrieval Systems," IEEE Computers, 28(9), pp. 18-22.
[2] Smeulders, A. W. M., Worring, M., Santini, S., Gupta, A., and Jain, R., 2000, "Content-Based Image Retrieval at the End of the Early Years," IEEE Trans. on Pattern Analysis and Machine Intelligence, 22(12), pp. 1349-1380.
[3] Liang, K.-C. and Kuo, C. C., 1999, "WaveGuide: A Joint Wavelet-Based Image Representation and Description System," IEEE Trans. on Image Processing, 8(11), pp. 1619-1629.
[4] Huang, X.-Y., Zhang, Y.-J., and Hu, D., 2003, "Image Retrieval Based on Weighted Texture Features Using DCT Coefficients of JPEG Images," Proc. 4th Pacific Rim Conf. on Multimedia, Informaiton, Communications and Siginal Processing, pp. 1571-1575.
[5] Huang, Y.-L. and Chang, R.-F., 1999, "Texture Features for DCT-Coded Image Retrieval and Classification," Proc. IEEE Int. Conf. on Acoustics, Speech, and Signal Processing, pp. 3013-3016.
[6] Bae, H.-J. and Jung, S.-H., 1997, "Image Retrieval Using Texture Based on DCT," Proc. of Int. Conf. on Information, Communications and Signal Processing, Singapore, pp. 1065- 1068.
[7] Nadler, M. and Smith, E. P., 1993, Pattern Recognition Engineering, New York: Wesley Interscience.
[8] Dunn, S., 1999, Digital Color. http://davis. wpi.edu/~matt/courses/color/.
[9] Huang, L. and Huang, X., 2001, "Multiresolution Recognition of Offline Handwritten Chinese Characters with Wavelet Transform," Proc. Int. Conf. Document Analysis and Recognition, pp. 631-634.
[10] Mallat, S. G., 1989, "A theory for multiresolution signal decomposition: the wavelet representation," IEEE Trans. on Pattern Analysis and Machine Intelligence, 11(7), pp. 674-693.
[11]Wang, J. Z., 1996, Content Based Image Search Demo Page. http://bergman.stanford.edu/~zwang/ project/imsearch/WBIIS.html.
[12]Wang, J. Z., Li, J., and Wiederhold, G., 2001, "SIMPLIcity: Semantics-Sensitive Integrated Matching for Picture Libraries," IEEE Trans. on Pattern Analysis and Machine Intelligence, 23(9), pp. 947-963.
[13] Huang, P.W. and Dai, S.K., 2004, “Design of a Two-Stage Content-Based Image Retrieval System Using Texture Similarity,” Information Processing and Management, 40(1), pp 81-96.
Links
Full Text
http://jita.csi.chu.edu.tw/Jita_web/publish/vol1_num3/08-20060046-text-sec.pdf
