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signature-recognition
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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 write their signature in a digitizing tablet, which acquires the signature in real time. Another possibility is the acquisition by means of stylus-operated PDAs. Some systems also operate on smart-phones or tablets with a capacitive screen, where users can sign using a finger or an appropriate pen. Dynamic recognition is also known as “on-line”. Dynamic information usually consists of the following information:
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.
Research-Based Digital Signature Authentication: An Alternative to Password-Based Authentication with Integration Capabilities
Signaturn is a Python application that groups and organizes scanned documents with signatures