Content-Based Image Search and Retrieval Using Relevance Feedback: the MUSE Project
Oge Marques, Fábio M. Costa, Borko Furht · 2000
The field of Content-Based Visual Information Retrieval (CBVIR) has experienced tremendous growth in the recent years and many research groups are currently working on solutions to the problem of finding a desired image or video clip in a huge archive without resorting to metadata. This paper describes the ongoing development of a CBVIR system for image search and retrieval with relevance feedback capabilities. Index Terms Content-based image search and retrieval, Relevance feedback, Multimedia database systems, Digital image processing. 1. Introduction The amount of audiovisual information available in digital format has grown dramatically in the last few years. Gigabytes of new images, audio and video clips are generated and stored everyday, helping to build up a huge, distributed, mostly unstructured repository of multimedia information, much of which can be accessed through the Internet. Digitization, compression, and archival of multimedia information has become popular, i...