Image Retrieval System Based on Density Slicing of Colour Histogram of Images Subareas and Colour Pair Segmentation
Techniques to identify objects within an image and searching for similar objects in the database is not claiming a lot of progress, due to the limitations of the capabilities of the existing techniques and algorithms in image processing and computer vision to perform such task. In this paper, a new technique based on slicing the images to equally sub-areas, then applying the density slicing to the colour histogram of
[1] Aigrain P., Zhang H. J., and Petkovic D., “Content-Based Representation and Retrieval of Visual Media-A State-of-the-Art Review,” Journal of Multimedia Tools and Applications, vol. 3, no. 3, pp. 179-202, 1996.
[2] Chua T. S., Lim S. K., and Pung H. K., “Content- Based Retrieval of Segmented Images,” in Proceedings of ACM Multimedia`94, San Francisco, October 1994.
[3] Eakins J. P., “Automatic Image Content Retrieval: Are We Getting Anywhere?,” in Proceedings of 3rd International Conference on Electronic Library and Visual Information Research (ELVIRA3), De Montfort University, Milton Keynes, pp. 123-135, 1996.
[4] Enser P. G. B., “Pictorial Information Retrieval,” Journal of Documentation, vol. 51, no. 2, pp. 126- 170, 1995.
[5] Gong Y., Zhang H., Chuant H., and Skauuchi M., “An Image Database System with Content Capturing and Fast Image Indexing Abilities,” in Proceedings of IEEE International Conference on Multimedia Computing and Systems, May 1994.
[6] Hafner J., Sawhney H. S., Equitz W., Flickner M., and Niblack W., “Efficient Colour Histogram Indexing for Quadratic Form Distance Function,” IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), vol. 17, no. 7, pp. 729-736, 1995.
[7] Idris F. and Panchanathan S., “Review of Image and Video Indexing Techniques,” Journal of Visual Communication and Image Representation, vol. 8, no. 2, pp. 146-166, 1997.
[8] Nagasaka A. and Tanaka Y., “Automatic Video Indexing and Full Video Search for Object Appearance,” Visual Database Systems II, IFIP, Elsevier Science Publishers B. V., pp. 113-127, October 1992.
[9] Natsev A., Rastogi R., and Shim. K., “WARLUS: A Similarity Retrieval Algorithm for Image atabase,” in Proceedings 1999 ACM SIGMOD International Conference on Management of Data, pp. 395-406, 1999.
[10] Rafael C., Gonzalez, and Richard E. Woods, Digital Image Processing, Addison Wesley, 1992.
[11] Smeulders W. M. A., “Content Based Image Retrieval at the End of the Early Years,” IEEE Transaction on Pattern Analysis and Machine Intelligence, vol. 22, no. 12, December 2000.
[12] Smeulders W. M. A., Worring M., Sanati S., Gupta A., and Jain R., “Content-Based Image Retrieval at the End of the Early Years,” IEEE, vol. 22, no. 12, pp. 1349-1380, 2000.
[13] Umbaugh E. S., Computer Vision and Image Processing, Prentice Hall, 1998. 202 The International Arab Journal of Information Technology, Vol. 1, No. 2, July 2004 Jehad Odeh is a lecturer at the Faculty of Information Science and Technology, Multimedia University, Melaka. He received the BSc degree in mathematical statistics from Yarmouk University, Jordan in 1990 and the MSc degree in computer science from University Putra Malaysia in 1999. From 1999 to 2003, he held a faculty lecturer position at several institutes and universities in Malaysia. His areas of research include computer graphics, image processing and image retrieval. Hjah Fatimah Ahmad is an associate professor and head of the Department of Multimedia, Faculty of Computer Science and Information Technology, University Putra Malaysia. She obtained her PhD from the National University of Malaysia in 1995. Her research interests include information retrieval, multimedia computing, and natural language processing. Mohamed Othman is the head of Department of Communication Technology and Network, University Putra Malaysia. He is also a member of Task Force on Cluster Computing, International Association of Science Technology and Development, Multigrid Network and Malaysian Mathematical Society. He received his PhD from National University of Malaysia. His main research interests on the filed of parallel and distributed algorithms, high-speed networks, and scientific computing. Rozita Johari obtained her BSc in computer science and mathematics from Pittsburg State University, Kansas in 1986, MSc in Computer Science from Illinois Institute of Technology, Chicago in 1987 and completed her PhD at University Putra Malaysia in 2001.