Bag of morphological words for content-based geographical retrieval
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Date
2014
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IEEE Computer Society
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. © 2014 IEEE.
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an der Universitat Klagenfurt (FTF); Forderverein Technische Fakultat; Industriellen Vereinigung (IV); mediamid
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Source
Proceedings - International Workshop on Content-Based Multimedia Indexing -- 12th International Workshop on Content-Based Multimedia Indexing, CBMI 2014 -- 18 June 2014 through 20 June 2014 -- Klagenfurt -- 106627