The project explores the development of a comprehensive handwritten signature verification system employing a combination of Deep Convolutional Neural Networks (CNNs), Artificial Neural Networks (ANNs), and Standard Machine Learning algorithms. By investigating both static and dynamic verification methods, the system aims to efficiently analyze scanned signatures against a database of stored samples, automating the process of determining authenticity for various applications in banking and business. Through rigorous comparison of the performance among the three methodologies, the project seeks to provide insights into the effectiveness of deep learning techniques in enhancing security and authenticity within document processing workflows.
- Tensorflow
- FastAPI
- ReactJS
- ChartJS
- Numpy, Pandas, OpenCV, Sklearn