Citazione: Vincenzo Di Lecce, Alberto Amato, A Fuzzy Logic Based Approach to Feedback Reinforcement in Image Retrieval, ICIC 2009. Published in Lecture Notes in Computer Science: Emerging Intelligent Computing Technology and Applications, Vol. 5754/2009, pp. 939-947, ISSN 0302-9743, ISBN-10 3-642-04069-1 Springer Berlin Heidelberg NewYork, ISBN-13 978-3-642-04069-6 Springer Berlin Heidelberg NewYork
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.
Keyword: Intelligent image retrieval system, fuzzy clustering, knowledge management, relevance feedback