Digital Support for Archaeology

Abstract

We describe an interdisciplinary approach in which computer scientists develop techniques to support archaeology. In the Reading Images for the Cultural Heritage (RICH) project, a variety of methods have been developed to support archaeologists in the visualization, categorization, and characterization of archaeological objects, such as medieval glass, coins, ceramics, and seeds. The methods are based on image processing and machine learning algorithms that are tailored to the task at hand. We describe the algorithms and illustrate their application on archaeological datasets. The virtues and pitfalls of the interdisciplinary approach to archaeology are discussed.