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- W2153591235 abstract "Among representative content-based image retrieval schemes, region-based retrieval has shown promise in retrieving similar images that exhibit considerable local variations. However, since humans are accustomed to relying on object-level concepts rather than low-level regions, robust and accurate object segmentation is an essential step. We propose a new multiple-region level image retrieval algorithm based on region-level image segmentation and its spatial relationship. To capture spatial similarity, we apply Hausdorff distance (HD) to our region-based image retrieval system, FRIP (finding region in the pictures). In contrast to other object or multiple region-based retrieval systems, we update classical HD to retrieve similar regions regardless of their spatial translation, insertion, and deletion. Furthermore, we incorporate relevance feedback to reflect the user's high-level query and subjectivity to the system and to compensate for performance degradation due to imperfect image segmentation. The efficacy of our method is validated using a set of 3000 images from Corel-photo CD." @default.
- W2153591235 created "2016-06-24" @default.
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- W2153591235 date "2003-06-25" @default.
- W2153591235 modified "2023-09-28" @default.
- W2153591235 title "Integrated region-based image retrieval using region's spatial relationships" @default.
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- W2153591235 doi "https://doi.org/10.1109/icpr.2002.1044649" @default.
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