This paper deals with the detection of freehand forgeries of signatures on bank checks. The detection process makes use of size ratio and slant features derived from Eden's kinematic stroke model for handwriting, which was modified to make it applicable to prewritten material. The features are measured for a real signature by a process involving automatic thresholding, to extract the signature from the background; analysis of projections, to segment the signature into vertical zones; detection of tall letters, to segment it into horizontal zones; and identification of the tall letters with respect to the (assumed known) spelling of the signature. Statistical assumptions are made regarding the expected variation in feature values among different writers and for a single writer. Tests on a small data base led to verification of these assumptions and to successful forgery detection.