Fingerprint Glitch

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

## Features - Fingerprint image preprocessing. - Feature extraction from fingerprint images. - Training a machine learning model for fingerprint matching. - Matching fingerprint images with a database. - Evaluation of matching performance.

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

fingerprint-glitch/

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

fingerprint-glitch/is the root directory of your project.
fingerprint/ is a subdirectory where you store your template fingerprint images. You can add as many template images as needed.
img0026.jpg is the target fingerprint image you want to compare with the templates.
main.py is your Python script containing the fingerprint matching code. README.md is the Markdown file where you provide instructions and documentation for users.

Getting Started

To get started with Fingerprint Glitch, follow these steps:

1. Clone this repository:

   git clone https://github.com/code-glitchers/fingerprint-glitch.git`

2.cd fingerprint-glitch

3. Place your target fingerprint image (e.g., img0026.jpg) in the main.py file.

4. Organize your template fingerprint images in a folder (e.g., fingerprint/) within the project directory.

5. Run the code: python main.py

6. The code will iterate through the template fingerprint images in the specified folder, compare each template with the target image, and print the match score for each template.

Customization

You can customize the code further by modifying the following functions in the main.py file:

• preprocess_fingerprint(): This function applies preprocessing steps to the fingerprint images. You can modify this function to add your own preprocessing steps.
• match_fingerprint(): This function compares two fingerprint images and returns the match score. You can modify this function to use a different matching algorithm.

Feel free to explore and adapt the code to suit your specific fingerprint matching requirements.

Happy fingerprint matching!

Usage

To use Fingerprint Glitch, you will need to:

1. Prepare a database of fingerprint images and labels.
2. Run the preprocessing and feature extraction scripts.
3. Train the matching model (if using machine learning).
4. Use the analyzer to match new fingerprint images.
5. Evaluate the system's performance.

For more detailed instructions, please see the documentation.

Contributing

Contributions to Fingerprint Glitch are welcome! To contribute to this project, follow these steps:

1. Fork the repository on GitHub.
2. Clone your forked repository to your local machine.
3. Create a new branch for your changes.
4. Make your changes and commit them.
5. Push your changes to your fork.
6. Create a pull request on GitHub.

Contact

If you have any questions or feedback, please contact the project maintainers:

• 0x_hayden
• Email: [email protected]

Credits

This project is maintained by:

Contributors and Developers

Support

If you find this project helpful, consider buying us a coffee:

License

Fingerprint Glitch is licensed under the MIT License. See the LICENSE file for details.

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