Adaptive Content-Based Image Retrieval with Relevance Feedback
Slobodan Cabarkapa, Nenad S. Kojic, Vladan Radosavljević, Goran J. Zajic, Branimir D. Reljin · 2005
Retrieval of images, based on similarities between feature vectors of querying image and those from database, is considered. The searching procedure was performed through the two basic steps: an objective one, based on the Euclidean distances and a subjective one based on the user's relevance feedback. Images recognized from user as the best matched to a query are labeled and used for updating the query feature vector through a RBF (radial basis function) neural network. The searching process is repeated from such subjectively refined feature vectors. In practice, several iterative steps are sufficient, as confirmed by intensive simulations.