A signal/semantic framework for image retrieval Mohammed Belkhatir, Yves Chiaramella, and Philippe Mulhem   View Paper (PDF)   Return to Poster Session Abstract This poster presents an approach for integrating perceptual signal features (i.e. color and texture) and semantic information within an integrated architecture for image retrieval. It relies on an expressive knowledge representation formalism handling high-level image descriptions and a full-text query framework. It consequently brings the level of image retrieval closer to users' needs by translating low-level signal features to high-level data and coupling it with semantics within index and query structures. BIBTEX #351;ca, RELIEF: combining expressiveness and rapidity into a single system, Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval, p.266-274, August 24-28, 1998, Melbourne, Australia 3   Arnold W. M. Smeulders , Marcel Worring , Simone Santini , Amarnath Gupta , Ramesh Jain, Content-Based Image Retrieval at the End of the Early Years, IEEE Transactions on Pattern Analysis and Machine Intelligence, v.22 n.12, p.1349-1380, December 2000}, ©2006 Association for Computing Machinery