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With the exponential growth of storage of digital images, retrieval has become an impending issue. Such large collection of data takes a considerable amount of time in retrieving images apart from picking relevant images with respect to the query. Despite advancements in introducing effective features, the search time still remains larger. In such scenario the search time could be minimized by categorizing...
Scene classification using semantic description has gained much attention towards automatic image retrieval. In many cases, visual appearance of images get affected by environmental conditions such as low lighting and viewing conditions. Such problems in semantic scenes pose difficult challenges during the classification of sceneries. To address this issue, a new outdoor scene classification method...
Scene classification is essential in Content Based Image Retrieval system which processes large amount of data. But this retrieval system failed to produce good classification result due to less relevant visual features used for classification task. In this work, we aim to categorize scenes into indoor versus outdoor using relevant low level features such as color and texture which help to improve...
Scene recognition is of great importance for content based image retrieval systems and image indexing applications to process very large databases. Our motivation is to model the contents of the natural scenes by representing local image using region description. The basic idea of semantic modeling is to describe local image regions into semantic concepts using low level features such as color and...
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