Browsing by Author "Arun, A."

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    A content-based visual information retrieval approach for automated image annotation
    (Springer Verlag service@springer.de, 2018) Senthil, K.; Arun, A.; Kamath S․, S.
    Today’s digital world is filled with a vast multitude of content such as text and multimedia. Various attempts are being made to develop modern and powerful search engines in order to support diverse queries on this large collection of textual and multimedia data. For supporting intelligent search, particularly for multimedia data such as images, additional metadata plays a crucial role in helping a search engine handpick the most relevant information for a query. A common technique that is used to generate pertinent metadata for visual multimedia content is by the process of annotation. Automating the annotation process given the large volume of visual content available on the Web is highly advantageous. In this paper, we propose an automated image annotation system that employs a content-based visual information retrieval technique using certain features of the image. Experimental evaluation and analysis of the proposed work have shown promising results. © Springer Nature Singapore Pte Ltd. 2018.
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    A content-based visual information retrieval approach for automated image annotation
    (2018) Senthil, K.; Arun, A.; Sowmya, Kamath S.
    Today�s digital world is filled with a vast multitude of content such as text and multimedia. Various attempts are being made to develop modern and powerful search engines in order to support diverse queries on this large collection of textual and multimedia data. For supporting intelligent search, particularly for multimedia data such as images, additional metadata plays a crucial role in helping a search engine handpick the most relevant information for a query. A common technique that is used to generate pertinent metadata for visual multimedia content is by the process of annotation. Automating the annotation process given the large volume of visual content available on the Web is highly advantageous. In this paper, we propose an automated image annotation system that employs a content-based visual information retrieval technique using certain features of the image. Experimental evaluation and analysis of the proposed work have shown promising results. � Springer Nature Singapore Pte Ltd. 2018.