An important feature of the Minoan culture is the pottery of Kamares style, which documents the Cretan cultural production between the first half of the 2nd millennium BC. This high level painted production, characterized by the combination of several diverse motifs, presents an enormous decorative repertoire. The extraordinary variety of combinations between elementary motifs according to a complex visual syntax makes interesting the automatic identification of the motifs, particularly upon potsherds. A completely automatic pipeline to accomplish this task is still a challenge even for today state-of-the-art Computer Vision and Pattern Recognition. Here we describe a possible approach to this daunting task and report about the promising results obtained. More precisely, starting from the identification of the region of interest in a digital image, motif extraction, and robust contour detection should be performed to obtain a bag of digital shapes. In a second phase each of the extracted shapes has to be classified according to prototypes in a database produced by an expert. The co-occurrence of the different shapes in a specimen will, in turn, be used to help the archaeologists in the cultural and even chronological setting.