Content-based retrieval in multimedia imaging
James Dowe · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1993
Content-based retrieval is founded on neural networks, this technology allows automatic filing of images and a wide range of possible queries of the resulting database. This is in contrast to methods such as entering SQL keys manually for each image as it is filed and later correctly re-entering those keys to retrieve the same image. An SQL-based approach does not take into account information that is hard to describe with text, such as sounds and images. Neural networks can be trained to translate `noisy' or chaotic image data into simpler, more reliable feature sets. By converting the images into the level of abstraction necessary for symbolic processing, standard database indexing methods can then be applied, or used in layers of associative database neural networks directly.