A large corpus of ceramic sherds dating from the High Middle Ages has been extracted in Saran (France). The sherds have an engraved frieze made by the potter with a carved wooden wheel. These relief patterns can be used to date the sherds in order to study the diffusion of ceramic production. The aim of the ARCADIA project was to develop an automatic classification of this archaeological heritage. The sherds were scanned using a three-dimensional (3-D) laser scanner. After projecting the 3-D point cloud onto a depth map, the local variance highlighted the shallow relief patterns. The saliency region focused on the motif was extracted by a density-based spatial clustering of FAST points. An adaptive thresholding was then applied to the depth to obtain a binary pattern close to manual sampling. The five most representative types of motif were classified by training an SVM model with a pyramid histogram of visual words descriptor. Compared with other state-of-the-art methods, the proposed approach succeeded in classifying up to 84% of the binary patterns on a dataset of 377 scanned sherds. The automatic method is extremely time-saving compared to manual stamping.