Content-based image collection summarization and comparison using self-organizing maps
Deng, Da

View/ Open
Cite this item:
Deng, D. (2005). Content-based image collection summarization and comparison using self-organizing maps (Information Science Discussion Papers Series No. 2005/11). University of Otago. Retrieved from http://hdl.handle.net/10523/1038
Permanent link to OUR Archive version:
http://hdl.handle.net/10523/1038
Abstract:
Progresses made on content-based image retrieval has reactivated the research on image analysis and similarity-based approaches have been investigated to assess the similarity between images. In this paper, the content-based approach is extended towards the problem of image collection summarization and comparison. For these purposes we propose to carry out clustering analysis on visual features using self-organizing maps, and then evaluate their similarity using a few dissimilarity measures implemented on the feature maps. The effectiveness of these dissimilarity measures is then examined with an empirical study.
Date:
2005-12
Publisher:
University of Otago
Pages:
20
Series number:
2005/11
Research Type:
Discussion Paper