Content-Based Image Retrieval (eBook)

The book describes several techniques used to bridge the semantic gap and reflects on recent advancements in content-based image retrieval (CBIR). It presents insights into and the theoretical foundation of various essential concepts related to image searches, together with examples of natural and texture image types. The book discusses key challenges and research topics in the context of image retrieval, and provides descriptions of various image databases used in research studies.

The area of image retrieval, and especially content-based image retrieval (CBIR), is a very exciting one, both for research and for commercial applications. The book explains the low-level features that can be extracted from an image (such as color, texture, shape) and several techniques used to successfully bridge the semantic gap in image retrieval, making it a valuable resource for students and researchers interested in the area of CBIR alike.

Prof. Vipin Tyagi, Fellow IETE, is currently working at the Jaypee University of Engineering and Technology, Guna, India. He is the Vice President of the Computer Society of India (CSI) of Region 3. He is also associated with the CSI Special Interest Group on Cyber Forensics. He was President of the Engineering Sciences Section of the Indian Science Congress Association (ISCA) for the term 2010-11. He has published a number of papers in various prominent journals and advanced research series. He is a recognized expert in the areas Image Processing and Cyber Forensics.

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The book describes several techniques used to bridge the semantic gap and reflects on recent advancements in content-based image retrieval (CBIR). It presents insights into and the theoretical foundation of various essential concepts related to image searches, together with examples of natural and texture image types. The book discusses key challenges and research topics in the context of image retrieval, and provides descriptions of various image databases used in research studies. The area of image retrieval, and especially content-based image retrieval (CBIR), is a very exciting one, both for research and for commercial applications. The book explains the low-level features that can be extracted from an image (such as color, texture, shape) and several techniques used to successfully bridge the semantic gap in image retrieval, making it a valuable resource for students and researchers interested in the area of CBIR alike.