An Off-Line Signature Recognition Using a Fuzzy Net

Abstract

This paper presents a method of off-line signature recognition using feature strokes and a fuzzy net. For getting feature strokes a pre-processing of signature data is studied. The pre-processing consists of a thinning method and a method of extracting feature strokes from an original signature and corresponding strokes from new signatures. The structure of fuzzy net is a simple perceptron and each unit in the input layer has a fuzzy membership function. From the connection weights of the trained network, it is easy to know which features of input data are important for signature recognition, i.e. the personal characteristics of the signatures are known from the fuzzy net. An experiment is done to show the feasibility of the new method.