Focusing on bridging the semantic gap, this book explores techniques and recent advancements in content-based image retrieval (CBIR). It delves into essential concepts related to image searches, supported by examples of natural and texture images. Key challenges and research topics in image retrieval are examined, alongside descriptions of various image databases utilized in research studies, offering a comprehensive understanding of the field.
Fundamental concepts of modern digital image processing are thoroughly explored, providing clear explanations and illustrations. The book is designed for students, scientists, and practitioners, enhancing understanding through practical examples and applications. Additionally, it includes ready-to-use implementations in MATLAB®, making it a valuable resource for anyone looking to apply these concepts in real-world scenarios.
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.