Novel Features for Off-line Signature Verification
AbstractIn this paper a novel feature extraction scheme has been suggested for offline signature verification. The proposed method used geometric center for feature extraction. Euclidean distance model was used for classification. This classifier is well suitable for features extracted and fast in computation. Method proposed in this paper leads to better results than existing offline signature verification methods. Threshold selection is based on statistical parameters like average and standard deviation (sigma).
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