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Content-based image collection summarization and comparison using self-organizing maps. (English) Zbl 1118.68138

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
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