Identification and authentification of handwritten signatures with a connectionist approach

TCSF/LER has developed an automatic system to identify or verify off-line handwritten signatures, using a connectionist approach. The authors´ method combines image processing which consists in extracting significant parameters from the signature image and classification by a multilayer perceptron which uses the previous parameters as input. In this paper, the image processing step is described according to the intrinsic features of handwriting. Then, the proposed neural networks are compared with others classifiers including pseudo-inverse, k-nearest-neighbours and k-means and the influence of pre-processing and bad segmentation is measured. On a base of around fifty signers (comprising English, French signatures and paraphes), many experimental results are given for identification and verification purposes