PicSOM—content-based image retrieval with self-organizing maps
Pattern Recognition Letters - Selected papers from the 11th scandinavian conference on image analysis
Self-Organizing Maps
Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
Classify By Representative Or Associations (CBROA): a hybrid approach for image classification
MDM '05 Proceedings of the 6th international workshop on Multimedia data mining: mining integrated media and complex data
An efficiency comparison of two content-based image retrieval systems, GIFT and PicSOM
CIVR'03 Proceedings of the 2nd international conference on Image and video retrieval
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The MPEG-7 standard is emerging as both a general framework for content description and a collection of specific, agreed-upon content descriptors. We have developed a neural, self-organizing technique for content-based image retrieval. In this paper, we apply the visual content descriptors provided by MPEG-7 in our PicSOM system and compare our own image indexing technique with a reference system based on vector quantization. The results of our experiments show that the MPEG-7-defined content descriptors can be used as such in the Pic-SOM system even though Euclidean distance calculation, inherently used in the PicSOM system, is not optimal for all of them. Also, the results indicate that the PicSOM technique is a bit slower than the reference system in starting to find relevant images. However, when the strong relevance feedback mechanism of PicSOM begins to function, its retrieval precision exceeds that of the reference system.