We present a Bayesian framework for content-based image retrieval which models the distribution of color and texture features within sets of related images. Given a userspecified ...
This paper presents a model for retrieval of images from a large World Wide Web based collection. Rather than considering complex visual recognition algorithms, the model presente...
High retrieval precision in content-based image retrieval can be attained by adopting relevance feedback mechanisms. These mechanisms require that the user judges the quality of t...
Researchers are currently more interested in searching for fragments that are similar to a query, than a total data item that is similar to a query; the search interest is for &qu...
Punpiti Piamsa-nga, Nikitas A. Alexandridis, Sanan...
Concept learning in content-based image retrieval (CBIR) systems is a challenging task. This paper presents an active concept learning approach based on mixture model to deal with...