Semantical Retrieval of Natural Photographic and Medical Images
From a Domain Perspective
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The growth of image content production and distribution over the world has exploded in recent years. This creates a compelling need for developing innovative tools for managing and retrieving images for many applications, such as web image search engines, medical decision support systems, etc. Until now, content-based image retrieval (CBIR) addresses the problem of finding images by automatically extracting low-level visual features. The main limitation of CBIR is due to the large semantic gap. A successful solution to bridge the semantic gap requires the investigation of techniques from multi...
The growth of image content production and distribution over the world has exploded in recent years. This creates a compelling need for developing innovative tools for managing and retrieving images for many applications, such as web image search engines, medical decision support systems, etc. Until now, content-based image retrieval (CBIR) addresses the problem of finding images by automatically extracting low-level visual features. The main limitation of CBIR is due to the large semantic gap. A successful solution to bridge the semantic gap requires the investigation of techniques from multiple fields. This book is motivated by a multi-disciplinary research effort and focuses on semantic-based image search from a domain perspective with an emphasis on natural photography and biomedical image databases. A prototype image retrieval system is developed to perform exhaustive experimental evaluations and to show the effectiveness of the proposed retrieval approaches in narrow to broad domain applications.
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