caseol / python-fingerprint-recognition

Fingerprint recognition with OpenCV

Python Fingerprint Recognition

Fingerprint recognition with SKimage and OpenCV

Requirements:

• NumPy
• SKimage
• OpenCV2

Works by extracting minutiae points using harris corner detection.

Uses SIFT (ORB) go get formal descriptors around the keypoints with brute-force hamming distance and then analyzes the returned matches using thresholds.

Usage:

1. Place 2 fingerprint images that you want to compare inside the database folder
2. Pass the names of the images as arguments in the console

Dockerfile

If you don't want to install the libraries, or want a easier way to test the application you can follow the commands:

docker build -t <name_of_your_choice> .

docker run -it <name_of_your_choice> <fingerprint_1> <fingerprint_2>

If you don't have Docker Engine installed, you can get the instructions to install it here: Install Docker

NOTE: the fingerprints must be in the /database folder

Credits

Special thanks to https://github.com/Utkarsh-Deshmukh/Fingerprint-Enhancement-Python for providing a library used to enhance the fingerprint picture.