Abstract
Cuneiform is the ancient writing systemin the world. But, there is no clear interest recognition cuneiform symbol, despite its importance. This research interested in building an algorithm for cuneiform symbol recognition. Firstly, the Sumerian texts were entered through the scanner and make some initial preprocessing operations such as segmentation for the purpose of cutting the text and getting a cuneiform symbol. Then, features were extracted for each symbol by using vertical and horizontal projections, centre of gravity, and connected component. Because of the large number of cuneiform symbols, the similar symbols are clustered by K-means algorithm, then multilayer neural networks are used to classify the symbol within the same cluster. The proposed algorithm gave good results.
