Deep Learning Based Handwritten Signature Recognition
Suresh Pokharel, Subarna Shakya · Figshare · 2021
A handwritten signature commonly practiced route for confirming the authenticity of legal documents. The verification of the signature is critical as it varies every time and may change with age, behavior, and environment. This paper presents a Deep learning model based on the CNN architecture to verify the signature. For experimental purpose, the feature extraction portion of the GoogleNet model has been used to transfer value calculation and the classification layer was retrained using back propagation with the concept of transfer learning. The classification layer of the Deep learning model was retrained with 25 classes of signature image dataset with each class consisting of 85 signatures. After training, the model was evaluated with a testing dataset of 15 signatures from each class. The mean testing precision of the neural network architecture with signature dataset was found to be 95.2 %.