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.