A fuzzy logic based approach to feedback reinforcement in image retrieval
Contributo in Atti di convegno
Data di Pubblicazione:
2009
Citazione:
A fuzzy logic based approach to feedback reinforcement in image retrieval / V. Di Lecce, A. Amato - In: Emerging intelligent computing technology and applications : 5th International Conference on Intelligent Computing, ICIC 2009, Ulsan, South Korea, September 16-19, 2009 : proceedings / [a cura di] D.S. Huang, K.H. Jo, H.H. Lee, H.J. Kang, V. Bevilacqua. - Berlin : Springer, 2009 May 05. - ISBN 9783642040696. - pp. 939-949 (( Intervento presentato al 5. convegno International Conference on Intelligent Computing (ICIC) tenutosi a Ulsan, South Korea nel 2009 [10.1007/978-3-642-04070-2_99].
Abstract:
Nowadays, due to the spread of digital imaging technologies, the design of effective content based image retrieval (CBIR) systems is perceived by the research community as a primary problem. Various techniques such as clustering and relevance feedback were proposed to obtain a certain level of knowledge about a given image database. Often clustering techniques were used to obtain a first level characterization of the image database used to speed up the successive stage of queries. In this work the authors use the knowledge obtained using a fuzzy clustering algorithm to reinforce the user feedback. The system was tested on the Columbia Coil-20 image database and the obtained results seem to be encouraging.
Tipologia IRIS:
03 - Contributo in volume
Keywords:
Fuzzy clustering; Intelligent image retrieval system; Knowledge management; Relevance feedback
Elenco autori:
V. Di Lecce, A. Amato
Link alla scheda completa:
Titolo del libro:
Emerging intelligent computing technology and applications : 5th International Conference on Intelligent Computing, ICIC 2009, Ulsan, South Korea, September 16-19, 2009 : proceedings