Items related to Content Based Image Retrieval (CBIR): A deeper insight
Synopsis
Image processing has become one of the most and fast growing fields. It has occupied an inevitable place in the industry. We also have worked in image processing, but, in a specific area of image retrieval. The purpose of this report is to describe the solution to the problem of designing a Content Based Image Retrieval, CBIR system. It outlines the problem, the proposed solution, the final solution that will be accomplished. Due to the enormous increase in image database sizes, as well as its vast deployment in various applications, the need for CBIR development arose. Firstly, this report outlines a description of the primitive features of an image, texture and color. These features are extracted and used as the basis for a similarity check between images. The report describes the implementation details through which the objective is going to be satisfied, (i.e.) the algorithms used to calculate the similarity between extracted features. The structure of the final software application is also illustrated. In short it would be a nice reading experience.
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About the Author
Shriram K Vasudevan is an M.Tech, M.B.A.,(PhD)with 6 years of experience. He has done his masters in the field of Embedded Systems. He has worked with top MNCs like WIPRO and ARICENT Technologies. His research is being carried out at PRIST University,India. He is currently associated with Amrita University. He has already published 4 books.
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- PublisherLAP LAMBERT Academic Publishing
- Publication date2012
- ISBN 10 3659171727
- ISBN 13 9783659171727
- BindingPaperback
- LanguageEnglish
- Number of pages56
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Content Based Image Retrieval (CBIR)
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LAP LAMBERT Academic Publishing Aug 2012, 2012
ISBN 10: 3659171727
ISBN 13: 9783659171727
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Image processing has become one of the most and fast growing fields. It has occupied an inevitable place in the industry. We also have worked in image processing, but, in a specific area of image retrieval. The purpose of this report is to describe the solution to the problem of designing a Content Based Image Retrieval, CBIR system. It outlines the problem, the proposed solution, the final solution that will be accomplished. Due to the enormous increase in image database sizes, as well as its vast deployment in various applications, the need for CBIR development arose. Firstly, this report outlines a description of the primitive features of an image, texture and color. These features are extracted and used as the basis for a similarity check between images. The report describes the implementation details through which the objective is going to be satisfied, (i.e.) the algorithms used to calculate the similarity between extracted features. The structure of the final software application is also illustrated. In short it would be a nice reading experience. 56 pp. Englisch. Seller Inventory # 9783659171727
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Content Based Image Retrieval (CBIR) : A deeper insight
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LAP LAMBERT Academic Publishing, 2012
ISBN 10: 3659171727
ISBN 13: 9783659171727
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Image processing has become one of the most and fast growing fields. It has occupied an inevitable place in the industry. We also have worked in image processing, but, in a specific area of image retrieval. The purpose of this report is to describe the solution to the problem of designing a Content Based Image Retrieval, CBIR system. It outlines the problem, the proposed solution, the final solution that will be accomplished. Due to the enormous increase in image database sizes, as well as its vast deployment in various applications, the need for CBIR development arose. Firstly, this report outlines a description of the primitive features of an image, texture and color. These features are extracted and used as the basis for a similarity check between images. The report describes the implementation details through which the objective is going to be satisfied, (i.e.) the algorithms used to calculate the similarity between extracted features. The structure of the final software application is also illustrated. In short it would be a nice reading experience. Seller Inventory # 9783659171727
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Content Based Image Retrieval (CBIR)
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Vasudevan Shriram K.Shriram K Vasudevan is an M.Tech, M.B.A.,(PhD)with 6 years of experience. He has done his masters in the field of Embedded Systems. He has worked with top MNCs like WIPRO and ARICENT Technologies. His research is . Seller Inventory # 5136800
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Content Based Image Retrieval (CBIR)
Published by
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ISBN 10: 3659171727
ISBN 13: 9783659171727
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Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
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Taschenbuch. Condition: Neu. Neuware -Image processing has become one of the most and fast growing fields. It has occupied an inevitable place in the industry. We also have worked in image processing, but, in a specific area of image retrieval. The purpose of this report is to describe the solution to the problem of designing a Content Based Image Retrieval, CBIR system. It outlines the problem, the proposed solution, the final solution that will be accomplished. Due to the enormous increase in image database sizes, as well as its vast deployment in various applications, the need for CBIR development arose. Firstly, this report outlines a description of the primitive features of an image, texture and color. These features are extracted and used as the basis for a similarity check between images. The report describes the implementation details through which the objective is going to be satisfied, (i.e.) the algorithms used to calculate the similarity between extracted features. The structure of the final software application is also illustrated. In short it would be a nice reading experience.Books on Demand GmbH, Überseering 33, 22297 Hamburg 56 pp. Englisch. Seller Inventory # 9783659171727
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