Semantical Retrieval of Natural Photographic and Medical Images

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...
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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 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.