Learning image similarities and categories from content analysis and relevance feedback
MULTIMEDIA '00 Proceedings of the 2000 ACM workshops on Multimedia
Color texture segmentation using feature distributions
Pattern Recognition Letters
Color image segmentation using fuzzy C-means and eigenspace projections
Signal Processing
Journal of Visual Communication and Image Representation
Movie scene segmentation using background information
Pattern Recognition
Content-based image retrieval using associative memories
TELE-INFO'07 Proceedings of the 6th WSEAS Int. Conference on Telecommunications and Informatics
Color-based image retrieval using perceptually modified Hausdorff distance
Journal on Image and Video Processing - Color in Image and Video Processing
An integrated approach to video retrieval
ADC '08 Proceedings of the nineteenth conference on Australasian database - Volume 75
Association-based image retrieval for automatic target recognition
AIKED'08 Proceedings of the 7th WSEAS International Conference on Artificial intelligence, knowledge engineering and data bases
Association-based image retrieval
WSEAS Transactions on Signal Processing
Cubic-splines neural network- based system for image retrieval
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
On the query of video database
MIV'05 Proceedings of the 5th WSEAS international conference on Multimedia, internet & video technologies
String extraction based on statistical analysis method in color space
GREC'05 Proceedings of the 6th international conference on Graphics Recognition: ten Years Review and Future Perspectives
A fast fuzzy c-means algorithm for colour image segmentation
International Journal of Information and Communication Technology
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After performing a thorough comparison of different quantization schemes in the RGB, HSV, YUV, and CIEL*u*v* color spaces, we propose to use color features obtained by hierarchical color clustering based on a pruned octree data structure to achieve efficient and robust image retrieval. With the proposed method, multiple color features, including the dominant color, the number of distinctive colors, and the color histogram, can be naturally integrated into one framework. A selective filtering strategy is also described to speed up the retrieval process. Retrieval examples are given to illustrate the performance of the proposed approach