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An Investigation in Multi-Feature Query Language Based Classification in Image Retrieval: Introduction
Abstract
With rapid development of digital technologies, building an efficient and reliable image retrieval system is always challenging in computing science and related application disciplines. This book part presents an investigation in how “Content-Based Image Retrieval (CBIR)” queries could be designed in order to achieve an extensible language understandable by both humans and machines. The query language used applies concepts from established text search and image retrieval engines. The question of whether such a query language can be sufficiently expressive to formally describe certain real-life concepts is investigated. Sets of images from different classes are used to build “descriptor” queries that are supposed to capture a single concept.
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