A method for the automatic verification of handwritten signatures is described. The method relies on global and local features that summarize aspects of signature shape and dynamics of signature production. We demonstrate that with the addition of our local feature based on stroke direction coding, the performance of signature verification improves significantly. The improvement is comparable with that of more sophisticated algorithms, which require much more computer resources. The current version of the program needs about 150 bytes to store a signature model and has 3% equal error rate. At the 1% false rejection point, the addition of the stroke direction information to the algorithm with only global features reduces the false acceptance rate from 13 to 7.5%. Prior to extraction of stroke direction information, signatures are normalized for position, size, and orientation using their Fourier transform. Such a scheme can also be useful in signature smoothing and compression. © 1996 Society of Photo−Optical Instrumentation Engineers.