Introduction

Fingerprint Glitch is a Python application designed for fingerprint analysis and matching against a database. It utilizes image processing techniques and machine learning to identify and match fingerprints.

Python Versions

Fingerprint Glitch is compatible with Python 3.x.

Code Style

We follow PEP 8 style guidelines for writing Python code to ensure consistency and readability.

Documentation

This document serves as the official documentation for the Fingerprint Glitch project. It provides information on installation, usage, and project structure.

Release Date

The initial release of Fingerprint Glitch was on [INSERT RELEASE DATE].

GitHub Stars

Fingerprint Glitch has garnered [INSERT NUMBER OF STARS] stars on GitHub.

GitHub Forks

The project has been forked [INSERT NUMBER OF FORKS] times on GitHub.

Features

• Fingerprint Image Preprocessing: Preprocesses fingerprint images to enhance their quality and prepare them for feature extraction.
• Feature Extraction: Extracts relevant features from fingerprint images using advanced image processing techniques.
• Machine Learning Model Training: Trains a machine learning model for fingerprint matching using the extracted features.
• Fingerprint Matching: Matches fingerprint images with a database of template images to identify potential matches.
• Matching Performance Evaluation: Provides tools to evaluate the performance of fingerprint matching, including accuracy, precision, and recall.

Requirements

To use Fingerprint Glitch, you need the following requirements:

• Python 3.x
• OpenCV
• NumPy
• scikit-learn (if using machine learning)
• Database of Fingerprint Images (provide details or a link if available)

File Structure

The project directory structure is as follows:

fingerprint-glitch/
│
├── fingerprint/
│   ├── template1.jpg
│   ├── template2.jpg
│   ├── ... (more template fingerprint images)
│
├── img0026.jpg (your target fingerprint image)
│
├── main.py
│
├── README.md
    

fingerprint-glitch/: The root directory of the project.