Efficient CBIR using Color Histogram Processing

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Details

The need for efficient content-based image retrieval has increased hugely. Efficient and effective retrieval techniques of images are desired because of the explosive growth of digital images. Content based image retrieval (CBIR) is a promising approach because of its automatic indexing retrieval based on their semantic features and visual appearance. In CBIR (Content-Based Image Retrieval), visual features such as shape, color and texture are extracted to characterize images. Each of the features is represented using one or more feature descriptors. During the retrieval, features and descriptors of the query are compared to those of the images in the database in order to rank each indexed image according to its distance to the query The similarity of images depends on the feature representation.However users have difficulties in representing their information needs in queries to content based image retrieval systems.

Autorentext

Neetu Sharma did her graduation and post-graduation from JNKVV, Jabalpur (India). Her major field of research work is crop management especially weed management in cultivated and uncultivated lands. She has published number of research articles in different national and international journals.

Weitere Informationen

  • Allgemeine Informationen
    • GTIN 09783659107832
    • Anzahl Seiten 88
    • Genre Wärme- und Energietechnik
    • Auflage Aufl.
    • Herausgeber LAP Lambert Academic Publishing
    • Größe H220mm x B220mm
    • Jahr 2012
    • EAN 9783659107832
    • Format Kartonierter Einband (Kt)
    • ISBN 978-3-659-10783-2
    • Titel Efficient CBIR using Color Histogram Processing
    • Autor Neetu Sharma , Paresh Rawat
    • Untertitel A Robust CBIR System
    • Sprache Englisch

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