Content based image retrieval using a bootstrapped SOM network

Authors:
Apostolos Georgakis;Haibo Li
Affiliations:
Digital Media Laboratory (DML), Department of Applied Physics and Electronics, Umeå University, Sweden;Digital Media Laboratory (DML), Department of Applied Physics and Electronics, Umeå University, Sweden
Venue:
ISNN'06 Proceedings of the Third international conference on Advnaces in Neural Networks - Volume Part II
Year:
2006

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Abstract

A modification of the well-known PicSOM retrieval system is presented. The algorithm is based on a variant of the self-organizing map algorithm that uses bootstrapping. In bootstrapping the feature space is randomly sampled and a series of subsets are created that are used during the training phase of the SOM algorithm. Afterwards, the resulting SOM networks are merged into one single network which is the final map of the training process. The experimental results have showed that the proposed system yields higher recall-precision rates over the PicSOM architecture.