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- W1967539196 abstract "Placed in the context of geographical content-based image retrieval, in this paper we explore the description potential of morphological texture descriptors when combined with the popular bag-of-visual-words paradigm. In particular, we adapt existing global morphological texture descriptors, so that they are computed within local sub-windows and then form a vocabulary of “visual morphological words” through clustering. The resulting image features, are thus visual word histograms and are evaluated using the UC Merced Land Use-Land Cover dataset. Moreover, the local approach under study is compared against alternative global and local descriptors across a variety of settings. Despite being one of the initial attempts at localized morphological content description, the retrieval scores indicate that vocabulary based morphological content description possesses a significant discriminatory potential." @default.
- W1967539196 created "2016-06-24" @default.
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- W1967539196 date "2014-06-01" @default.
- W1967539196 modified "2023-09-23" @default.
- W1967539196 title "Bag of morphological words for content-based geographical retrieval" @default.
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- W1967539196 doi "https://doi.org/10.1109/cbmi.2014.6849837" @default.
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