This paper introduces ArtHistorian, a content-based classification and indexing system that represents the visual content of art paintings by a six-dimensional feature set. The introduced feature set is robust to scale changes and can handle variations in lighting conditions. A nonlinear SVM classifier included in the system learns the characteristics of fundamental art movements and painting styles. A hybrid classifier that combines PCA representation of paintings with the SVM classification is also exploited. It is shown that ArtHistorian is capable of classifying art paintings based on painters as well as art movements with an accuracy of greater than 90% and its false alarm ratio is very small. The developed system enables the user to run content-based queries and to retrieve from painting databases created in XML format.

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The last decade witnessed the improvement of strong compression technics over audio-visual data and the development of world wide communications of information. These innovations gave birth to unforeseen requirements like storing these information, indexing and retrieving them for subsequent usages. Standarization of compression of multimedia contents is rapidly accepted as a need for encoding/decoding audio-visual data regardless of machine and environment. However standardization for indexing these materials still remains a puzzle which disables browsing audio-visual data regardless of machine and environment. MPEG-7 standardisation group aims to create the standard syntax to access to multimedia content. This paper puts forward a next step, the extraction of user preferences and matching them with MPEG-7 coded media content for quick and smart browsing.