Content-based image collection summarization and comparison using self-organizing maps
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.
Publisher: University of Otago
Series number: 2005/11
Research Type: Discussion Paper