Alexandra Mae C. LayloMark Daryl A. DecilloLouie Andrew F. BooJeffrey S. Sarmiento
Signature is one of the biometric traits that are being used in person authentication and due to its dominant usage; it became one of the top subjects of forgery. In this study, a signature verification using Convolutional Neural Network (CNN) is proposed. With the use of transfer learning, inception-v3 is mainly used for the feature extraction of data samples and for classification of signatures. The proposed method is assessed on dataset of handwritten signatures gathered from 4 people with 100 signatures each. The testing results determine the threshold value which is 96.43%. Factors that affect the accuracy of the result were also identified.
S. V. BondePradeep NarwadeRajendra R. Sawant
Rutik TalekarFarheen ShaikhNavneet KumarKaustub BordeProf. Ankita Kotalwar