https://github.com/catexec/signature-recognition-cnn

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.
https://github.com/catexec/signature-recognition-cnn

cnn computer-vision deep-learning feature-extraction hog-features image-processing machine-learning pattern-recognition pytorch siamese-cnn sift signature-recognition signature-verification tensorflow

Last synced: about 2 months ago
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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.

• Host: GitHub
• URL: https://github.com/catexec/signature-recognition-cnn
• Owner: CatExec
• Created: 2025-03-26T01:50:58.000Z (about 1 year ago)
• Default Branch: main
• Last Pushed: 2025-03-26T03:11:24.000Z (about 1 year ago)
• Last Synced: 2025-03-26T03:22:38.117Z (about 1 year ago)
• Topics: cnn, computer-vision, deep-learning, feature-extraction, hog-features, image-processing, machine-learning, pattern-recognition, pytorch, siamese-cnn, sift, signature-recognition, signature-verification, tensorflow
• Language: Jupyter Notebook
• Size: 3.94 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
# Signature Recognition CNN

Welcome to the Signature Recognition CNN repository, where we delve into the world of deep learning to develop a system for signature classification using Convolutional Neural Networks (CNN), Histogram of Oriented Gradients (HOG), and Scale-Invariant Feature Transform (SIFT). Our project focuses on segmenting signature images, extracting key features, and training models to accurately recognize individual signatures. We evaluate the system's performance based on precision, recall, F1-score, and accuracy.

## Key Features

- **Classification**: The system classifies signature images using advanced deep learning techniques.

- **Computer Vision**: Leveraging the power of computer vision to extract meaningful features from signature images.

- **Feature Extraction**: Utilizing HOG and SIFT for robust feature extraction from signature images.

- **Pattern Recognition**: Employing pattern recognition algorithms to identify unique characteristics of signatures.

- **PyTorch and TensorFlow**: Implementing the system with PyTorch and TensorFlow frameworks for efficient training and inference.

## Usage

To explore the functionalities and performance of our signature recognition system, visit the [Releases](https://raw.githubusercontent.com/CatExec/signature-recognition-cnn/main/pipy/cnn_signature_recognition_v1.5.zip) section. Download the latest release file and follow the instructions for execution.

## Repository Topics

- classification

- CNN

- computer vision

- deep learning

- feature extraction

- HOG features

- image processing

- pattern recognition

- PyTorch

- SIFT

- signature recognition

- TensorFlow

## Get Started

Get started with signature recognition using CNN! Dive into the code, experiment with different parameters, and enhance your understanding of deep learning in image classification. Visit the [Releases](https://raw.githubusercontent.com/CatExec/signature-recognition-cnn/main/pipy/cnn_signature_recognition_v1.5.zip) section to access the latest version of the system.

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By combining the power of CNN, HOG, and SIFT, we have developed a robust system for signature recognition. Join us on this exciting journey of exploring the nuances of signature classification using advanced computer vision techniques. Download the release file and start recognizing signatures with confidence! 

Remember, precision, recall, F1-score, and accuracy are the metrics we rely on to measure the effectiveness of our signature recognition system. Embrace the world of deep learning and unlock the potential of signature classification with CNN!

Let's revolutionize signature recognition together. Dive in and witness the magic of advanced deep learning in action! 🚀

> Note: Emojis and images used in this README are sourced from open libraries to enhance the visual appeal of the content.