Deng, Da Content-based image collection summarization and comparison using self-organizing maps. (English) Zbl 1118.68138 Pattern Recognition 40, No. 2, 718-727 (2007). Summary: Progresses made on content-based image retrieval have reactivated the research on image analysis and a number of similarity-based methods have been established 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. MSC: 68T10 Pattern recognition, speech recognition 68U10 Computing methodologies for image processing Keywords:content-based image retrieval; self-organizing maps; dissimilarity Software:VisualSEEk; SOM_PAK; EMD; SOMLib PDF BibTeX XML Cite \textit{D. Deng}, Pattern Recognition 40, No. 2, 718--727 (2007; Zbl 1118.68138) Full Text: DOI Link References: [1] Carson, C.; Thomas, M.; Belongie, S., Blobworld: a system for region-based image indexing and retrieval, (Proceedings of the International Conference on Visual Information Systems (1999)), 509-516 [2] Smith, J.; Chang, S., Visualseek: a fully automated content-based image query system, (Proceedings of ACM Multimedia, vol. 96 (1996)), 87-98 [3] Smeulders, A.; Worring, M.; Santini, S.; Gupta, A.; R., J., Content-based image retrieval at the end of the early years, IEEE Trans. Pattern Anal. Mach. 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