1 January 2001 Multilevel image segmentation and object representation for content-based image retrieval
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Abstract
Due to the increasing demand and offer of the technology, the next generation of the image file formats will be more likely to store and retrieve images based on their semantic conte. Thus, an image should be segmented into 'meaningful' regions, each of which corresponds to an object and/or background. In this study, we propose a scheme for multi- level image segmentation, based on a simple descriptor, called 'the closest color in the same neighborhood'. The proposed scheme generates a stack of images without using any segmentation threshold. The stack of images is hierarchically ordered in a uniformity tree. The uniformity tree is then associated with a semantic tree, which is built by the user for content based representation. The experiments indicate superior results for retrieving images, which consist of few objects and a background.
© (2001) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Pinar Duygulu, Fatos T. Yarman-Vural, "Multilevel image segmentation and object representation for content-based image retrieval", Proc. SPIE 4315, Storage and Retrieval for Media Databases 2001, (1 January 2001); doi: 10.1117/12.410956; https://doi.org/10.1117/12.410956
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