Computer mages are being generated at an ever-increasing rate by sources such as defense and civilian satellites, military reconnaissance and sur-I veillance flights, fingerprinting and mug-shot-capturing devices, scientific experiments, biomedical imaging, and home entertainment systems. For example, NASA's Earth Observing System will generate about 1 terabyte of image data per day when fully operational. A content-based image retrieval (CBIR) system is required to effectively and efficiently use information from these image repositories. Such a system helps users (even those unfamiliar with the database) retrieve relevant images based on their contents. Application areas in which CBIR is a principal activity are numerous and diverse: art galleries and museum management, architectural and engineering design, interior design, remote sensing and management of earth resources, geographic information systems, scientific database management, weather forecasting, retailing, fabric and fashion design, trademark and copyright database management, law enforcement and criminal investigation, and picture archiving and communication systems. With the recent interest in multimedia systems, CBIR has attracted the attention of researchers across several disciplines. Previous approaches to content-based retrieval have taken two directions.' In the first, image contents are modeled as a set of attributes extracted manually and managed within the framework of conventional database-management systems. Queries are specified using these attributes. Attribute-based representation of images entails a high level of image abstraction. Generally, the higher the level of abstraction, the lesser is the scope for posing ad hoc queries to the image database. Attribute-based retrieval is advocated and advanced primarily by database researchers. The second approach depends on an integrated feature-extraction/ object-recognition subsystem to overcome the limitations of attribute-based 0018-9162/95/$4.00 0 1995 IEEE
Existing systems for content based image retrieving (CBIR) generally use attributes that are manually or automatically extracted from images and then stored and managed in conventional database systems REF .
Content based image retrieval systems
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IEEE Computer
Computer Science