Content Based Image Retrieval: New Approaches of Feature Vector Extraction - Couverture souple

Thepade, Sudeep D.; Kekre, H. B.

 
9783847341253: Content Based Image Retrieval: New Approaches of Feature Vector Extraction
Couverture souple
ISBN 10 : 3847341251 ISBN 13 : 9783847341253
Editeur : LAP LAMBERT Academic Publishing, 2012

Synopsis

Modern image search engines retrieve the images based on their visual contents, commonly referred to as Content Based Image Retrieval (CBIR) systems. Typical CBIR systems can organize and retrieve images from image databases, automatically by extracting some features such as color, texture, shape from images and looking for similar images which have similar feature. One problem of this approach is reliance on visual similarity to judge semantic similarity, which creates problems due to semantic gap between low-level content and high level concepts. Even with the subsistence of this problem, if aggressive attempts are made CBIR can be used for real life applications. For example in spite of the open problems like robust text understanding, Google and Yahoo have become most popular for searching. The work presented here mainly focuses on efficient CBIR methods with help of representation of converting the visual content of images in feature vector using proposed techniques. The proposed CBIR methods using Colour, Transformed Image, Texture and Shape content are proved to be better and faster using test bed of 1000 variable size images spread across 11 image categories.

Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.

Présentation de l'éditeur

Modern image search engines retrieve the images based on their visual contents, commonly referred to as Content Based Image Retrieval (CBIR) systems. Typical CBIR systems can organize and retrieve images from image databases, automatically by extracting some features such as color, texture, shape from images and looking for similar images which have similar feature. One problem of this approach is reliance on visual similarity to judge semantic similarity, which creates problems due to semantic gap between low-level content and high level concepts. Even with the subsistence of this problem, if aggressive attempts are made CBIR can be used for real life applications. For example in spite of the open problems like robust text understanding, Google and Yahoo have become most popular for searching. The work presented here mainly focuses on efficient CBIR methods with help of representation of converting the visual content of images in feature vector using proposed techniques. The proposed CBIR methods using Colour, Transformed Image, Texture and Shape content are proved to be better and faster using test bed of 1000 variable size images spread across 11 image categories.

Biographie de l'auteur

Dr. Sudeep D. Thepade is Ph.D. (Computer Engineering), M.E.(Computer Engineering),B.E.(Computer). He has more than 130 papers in National/International Conferences/Journals to his credit with many accolades and awards. He is member of International Advisory Committee for many International Conferences, Reviewer for many international journal

Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.

Éditeur
LAP LAMBERT Academic Publishing
Date d'édition
2012
Langue
anglais
ISBN 10 
3847341251
ISBN 13 
9783847341253
Reliure
Broché
Nombre de pages
316
Coordonnées du fabricant
non disponible
Personne responsable
KreGa Onlinehandel GmbH
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info@krega-onlinehandel.de

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Brakel
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Allemagne

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Edition présentée

ISBN 10 :  3847310844 ISBN 13 :  9783847310846
Editeur : LAP LAMBERT Academic Publishing, 2012
Couverture souple