In spite of the progress of machine recognition techniques of Latin, Kana, and Chinese characters over the two past decades, the machine recognition of Arabic characters has remained almost untouched. In this correspondence, a structural recognition method of Arabic cursively handwritten words is proposed. In this method, words are first segmented into strokes. Those strokes are then classified using their geometrical and topological properties. Finally, the relative position of the classified strokes are examined, and the strokes are combined in several steps into a string of characters that represents the recognized word. Experimental results on texts handwritten by two persons showed high recognition accuracy.