Sinossi
This volume addresses the image feature selection issue in developing content-based image retrieval systems. It first discusses the four important issues in developing a complete content-based image retrieval system, and then demonstrates that image feature selection has significant impact on the remaining issues of system design. Next, it presents an in-depth literature survey on typical image features explored by contemporary content-based image retrieval systems for image matching and retrieval purposes. The goal of the survey is to determine the characteristics and the effectiveness of individual features, so as to establish guidelines for future development of content-based image retrieval systems.
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Contenuti
List of Figures. Preface. 1. Introduction. 2. Survey of Contemporary Content-Based Image Retrieval Systems. 3. Indexing Structures for Image Databases. 4. Building an Advanced Region-Based Image Retrieval System (ARBIRS). 5. The Texture Detection Subsystem. 6. The Region-Based Subsystem. 7. The Histogram-Based Subsystem. 8. The Database Query Subsystem. 9. Experimental Evaluations and Discussions. References. Index.
Product Description
Book by Yihong Gong
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Intelligent Image Databases: Towards Advanced Image Retrieval
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Hardcover. Condizione: Très bon. Ancien livre de bibliothèque. Edition 1997. Ammareal reverse jusqu'à 15% du prix net de cet article à des organisations caritatives. ENGLISH DESCRIPTION Book Condition: Used, Very good. Former library book. Edition 1997. Ammareal gives back up to 15% of this item's net price to charity organizations. Codice articolo E-578-739
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Intelligent Image Databases: Towards Advanced Image Retrieval
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Condizione: Sehr gut. Zustand: Sehr gut | Sprache: Englisch | Produktart: Bücher | Intelligent Image Databases: Towards Advanced Image Retrieval addresses the image feature selection issue in developing content-based image retrieval systems. The book first discusses the four important issues in developing a complete content-based image retrieval system, and then demonstrates that image feature selection has significant impact on the remaining issues of system design. Next, it presents an in-depth literature survey on typical image features explored by contemporary content-based image retrieval systems for image matching and retrieval purposes. The goal of the survey is to determine the characteristics and the effectiveness of individual features, so as to establish guidelines for future development of content-based image retrieval systems. Intelligent Image Databases: Towards Advanced Image Retrieval describes the Advanced Region-Based Image Retrieval System (ARBIRS) developed by the authors for color images of real-world scenes. They have selected image regions for building ARBIRS as the literature survey suggests that prominent image regions, along with their associated features, provide a higher probability for achieving a higher level content-based image retrieval system. A major challenge in building a region-based image retrieval system is that prominent regions are rather difficult to capture in an accurate and error-free condition, particularly those in images of real-world scenes. To meet this challenge, the book proposes an integrated approach to tackle the problem via feature capturing, feature indexing, and database query. Through comprehensive system evaluation, it is demonstrated how these systematically integrated efforts work effectively to accomplish advanced image retrieval. Intelligent Image Databases: Towards Advanced Image Retrieval serves as an excellent reference and may be used as a text for advanced courses on the topic. Codice articolo 3036714/202
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Condizione: New. Addresses the image feature selection issue in developing content-based image retrieval systems. This book discusses the four important issues in developing a complete content-based image retrieval system, and then demonstrates that image feature selection has significant impact on the remaining issues of system design. Series: The Springer International Series in Engineering and Computer Science. Num Pages: 134 pages, biography. BIC Classification: UG; UYQ. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly; (UU) Undergraduate. Dimension: 234 x 156 x 11. Weight in Grams: 880. . 1997. Hardback. . . . . Codice articolo V9780792380153
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