A super lightweight image processing algorithm for detection and extraction of overlapped handwritten signatures on scanned documents using OpenCV and scikit-image.

The most powerful and customizable binary pattern scanner

Verify the authenticity of handwritten signatures through digital image processing and neural networks. ✍️

An end-to-end signature verification system to extract, clean and verify signatures in documents. Signatures are detected using YOLOv5. Noise is cleaned using a CycleGAN approach and verified. Keras / Tensorflow / PyTorch

Signature recognition is a behavioural biometric. It can be operated in two different ways: Static: In this mode, users write their signature on paper, digitize it through an optical scanner or a camera, and the biometric system recognizes the signature analyzing its shape. This group is also known as “off-line”. Dynamic: In this mode, users wri…

A package for signature detection

Application to detect the similarity of two signatures.

Signature recognition with Keras,Deep learning

A large-scale offline Chinese handwritten signature dataset

Tanda Tangan Digital (Android)

Signature Recognition with Siamese Network and CycleGAN

OpenCV Signature Detector

A python page to recognize the signature using CV2 library and back propagation algorithm

A web application for signature detection.

Signature recognition using template matching and correlation

Signature recognition is a behavioural biometric. It can be operated in two different ways: Static: In this mode, users write their signature on paper, digitize it through an optical scanner or a camera, and the biometric system recognizes the signature analyzing its shape. This group is also known as “off-line”. Dynamic: In this mode, users wri…

Machine Learning model made by me and my colleagues for Signature and Facial Recognition which is helpful in Finance Sector considering the need of Security.

A deep learning-based system for signature classification using CNN, HOG, and SIFT. This project segments signature images, applies feature extraction, and trains models to recognize individual signatures. Performance is evaluated using precision, recall, F1-score, and accuracy.

Research-Based Digital Signature Authentication: An Alternative to Password-Based Authentication with Integration Capabilities