In this paper, a number of persons were selected to use their signature as a
database for the work. Six signatures were taken from each person through two
separated period of time using the same pen and paper. The adopted method consists of
three main steps. In the first step, the digital image of the signature transformed into
contours. After that the main contours were extracted and the noise was rejected. These
extracted contours and their dimensions were measured precisely according to their (x)
and (y) axis. Second step is the coding step, where the (Chain Code) method was used
to code the extracted contour from the first step, converted them into vectors in which
they are very easy to deal with. Using length of the vectors were sorted descending by
that can be easily used in comparison process. The third (final) step includes
application of the (Invariant Moments) method with these chain vectors and the
calculated mean of the output for the five signatures taken for each signer and used it
as a reference feature for the signer in the recognition process. The signature
recognition process completed using the (Minimum Distance) method as a classifier to
identify the personal signature.