This paper gives a summary of the content-based Image Retrieval and Content-based Audio Retrieval, which are two parts of the Content-based Retrieval. Content-based Retrieval is the retrieval based on the features of the content. Generally, it is a way to extract features of the media data and find other data with the similar features from the database automatically. Content-based Retrieval can...

in this paper, the performance of 11 different distances for image retrieval and classification, based on color, shape and texture, is evaluated. the precision-recall measure and the correct classification rate of the k-nn classifier are used to evaluate retrieval and classification performances, respectively. the experimental results for a database of 1000 images from 10 different semantic gro...

In this demo proposal, we describe our prototype application, SIERRA, which combines text-based and content-based image retrieval and allows users to link together image content of varying document granularity with related data like annotations. To achieve this, we use the concept of superimposed information (SI), which enables users to (a) deal with information of varying granularity (sub-docu...

content-based image retrieval and text-based image retrieval are two fundamental approaches in the field of image retrieval. the challenges related to each of these approaches, guide the researchers to use combining approaches and semi-automatic retrieval using the user interaction in the retrieval cycle. hence, in this paper, an image retrieval system is introduced that provided two kind of qu...

Zur Beantwortung der Frage, warum Bildersuchen auf Schlüsselwörtern basieren, statt auf den bildimmanenten Informationen, werden Repräsentationsmöglichkeiten für Bildinformationen vorgestellt, die Personen in die Lage versetzen, Anfragen in Form von Bildinformationen statt Schlüsselwörtern zu formulieren. Die Bildinformationen sollen in einer Weise interpretiert werden, die dem subjektiven Empf...