VisualSEEk: a fully automated content-based image query system
MULTIMEDIA '96 Proceedings of the fourth ACM international conference on Multimedia
Self-organizing maps
MULTIMEDIA '98 Proceedings of the sixth ACM international conference on Multimedia
Comparing images using joint histograms
Multimedia Systems - Special issue on video content based retrieval
Content-Based Image Retrieval at the End of the Early Years
IEEE Transactions on Pattern Analysis and Machine Intelligence
Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
Integration of Image Matching and Classification for Multimedia Navigation
Multimedia Tools and Applications
Comparing Self-Organizing Maps
ICANN 96 Proceedings of the 1996 International Conference on Artificial Neural Networks
Empirical Evaluation of Dissimilarity Measures for Color and Texture
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
A Metric for Distributions with Applications to Image Databases
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Spatial Color Indexing and Applications
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
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The research of content-based image retrieval techniques has been focused on extracting effective low level visual features for indexing and enabling query of individual images by efficient feature matching. In this paper, the content-based approach is extended towards the problem of multimedia collection profiling and comparison. We propose to carry out visual feature clustering using the Kohonen self-organized map algorithm, and then apply distance measures on the generated feature maps to evaluate their similarity. Apart from the conventional Hausdorff distance, other distance measures have been implemented and found to perform better in our case study.