Numismatics deals with various historical aspects of the phenomenon Money. Fundamental part of a numismatist¿s work is the classification of coins according to standard reference books. Reference numbers make the full description of a given coin type (including accurate dating, the distinction between minting places or any available political background) obtainable for everyone. The classification of ancient coins is a highly complex task that requires years of experience in the entire field of numismatics. Computer Vision explores the theory and technology to obtain and interpret information from images. For the application of ancient coin classification, computer vision techniques like Symbol Recognition and Optical Character Recognition (OCR) are investigated. The aim of the proposed project is to develop a framework for the automatic image-based classification of ancient coins. The framework comprises an image acquisition step, where optimal conditions for the acquisition of coins are examined. Classification is achieved by extracting and matching discriminative features like local image features and coin inscriptions obtained by optical character recognition (OCR) from the images. As the project¿s topic is interdisciplinary, it brings together competencies from the fields of computer vision and numismatics: the Pattern Recognition and Image Processing Group at the Vienna University of Technology and the Department of Coins and Medals at the Museum of Fine Arts, Vienna. The project¿s basic research lies in the field of computer vision but has the goal to produce an application for automatic image-based classification of historical coins in large-scale databases in the long run. Therefore, it establishes a link between basic scientific research and the development of an innovative application in the future.