The enlarging audiovisual multimedia content during the last few years has emerged the need of automatic feature extraction and description of this content. With the use of various descriptors, including those defined by the MPEG-7 standard, its low level information is captured. In this diploma thesis MPEG-7 visual descriptors are examined and a descriptor extraction application is developed based on the MPEG-7 eXperimentation Model. This application is evaluated in order to verify its alignment to the XM. This application is then used within a high-level concept detection approach. A region-based technique is applied and a visual thesaurus is constructed to formalize knowledge. Neural-network detectors are trained in order to detect high-level concepts. Moreover, the utility of the well known Latent Semantic Analysis technique is investigated. The dataset of the TRECVID benchmark has been used for testing this techniques. Finally a car exterior/interior classification problem is also tackled. Extensive experimental results are presented for each of the aforementioned problems.