Authors: Bilal Ahmed1 & Musa M. Ameen2 & Mohammed S. Anwar3
1Information Technology Department, Tishk International University, Erbil, Iraq
2Computer Engineering Department, Tishk International University, Erbil, Iraq
3Computer Engineering Department, Tishk International University, Erbil, Iraq
Abstract: A major research area in computer vision is content-based image retrieval. MPEG-7 sets up a list of descriptions of the structured image content. We examine the weakness and lack of retrieval approaches based on global characteristics in this study by incorporating the commonly used feature descriptors of MPEG-7. In the meantime, to satisfy user requirements for assessing spatial information similarities, an image retrieval approach based on texture region features for MPEG-7 is recommended. Retrieval tests show the validity and efficiency of our approach. This paper also defines our approach to color quantization, extraction, and matching processes of features and so on in depth.
Keywords: MPEG-7, CBIR, Edge Histogram Descriptor
Akgül, C. B., Rubin, D. L., Napel, S., Beaulieu, C. F., Greenspan, H., & Acar, B. (2011). Content-based image retrieval in radiology: current status and future directions. Journal of Digital Imaging, 24(2), 208-222.
Batko, M., Falchi, F., Lucchese, C., Novak, D., Perego, R., Rabitti, F., … & Zezula, P. (2010). Building a web-scale image similarity search system. Multimedia Tools and Applications, 47(3), 599-629.
Chow, T. W., Rahman, M. K. M., & Wu, S. (2006). Content-based image retrieval by using tree-structured features and multi-layer self-organizing map. Pattern Analysis and Applications, 9(1), 1-20.
Cvetković, S. S., & Nikolić, S. V. (2011). Merged MPEG-7 visual descriptors for image classification. In 2011 10th International Conference on Telecommunication in Modern Satellite Cable and Broadcasting Services (TELSIKS) (Vol. 1, pp. 345-348). IEEE.
Eidenberger, H. (2004). Statistical analysis of content-based MPEG-7 descriptors for image retrieval. Multimedia Systems, 10(2), 84-97.
Huang, J., Kumar, S. R., Mitra, M., Zhu, W. J., & Zabih, R. (1997, June). Image indexing using color correlograms. In Proceedings of IEEE computer society conference on Computer Vision and Pattern Recognition (pp. 762-768). IEEE.
Huang, P. W., & Dai, S. K. (2003). Image retrieval by texture similarity. Pattern Recognition, 36(3), 665-679.
Huang, Z. C., Chan, P. P., Ng, W. W., & Yeung, D. S. (2010). Content-based image retrieval using color moment and Gabor texture feature. In 2010 International conference on machine learning and cybernetics (Vol. 2, pp. 719-724). IEEE.
Manjunath, B. S., Ohm, J. R., Vasudevan, V. V., & Yamada, A. (2001). Color and texture descriptors. IEEE Transactions on Circuits and Systems for Video Technology, 11(6), 703-715.
Pass, G., Zabih, R., & Miller, J. (1997). Comparing images using color coherence vectors. In Proceedings of the fourth ACM international conference on Multimedia (pp. 65-73).
Sim, D. G., Kim, H. K., & Park, R. H. (2004). Invariant texture retrieval using modified Zernike moments. Image and Vision Computing, 22(4), 331-342.
Wang, J. Z., Li, J., & Wiederhold, G. (2001). SIMPLIcity: Semantics-sensitive integrated matching for picture libraries. IEEE Transactions on Pattern Analysis and Machine Intelligence, 23(9), 947-963.