Handwritten Signature Recognition Using Neural Networks

Abstract

This article demonstrates how adaptable neural networks may be used to preprocess handwritten signatures. After interpolating an input signature, a descriptor vector is created to alter the inclination angle. Neurons that are critical for recognition and categorization are preprocessed in a suggested adaptable neural network design. In this study, we present an upgrade to the material-based technique called pseudo coloring. Filling and sharpening color layers on top of the picture is made easier with the addition of edge detection algorithms. For our demonstrations, we use genuine X-ray data from a professional dual energy scanner.