Skip to content

Latest commit

 

History

History
49 lines (25 loc) · 1018 Bytes

README.md

File metadata and controls

49 lines (25 loc) · 1018 Bytes
Raw

Fingerprint-Minutiae-Extraction

Summary

This project was forked from fingerprint_recognition

How to run

Install requirements

pip install -r requirements.txt

Run fingerprint-minutiae-extraction code

python main.py

Stages of the Fingerprint-Minutiae-Extraction Algorithm

The performance of minutiae extraction algorithms and other fingerprint recognition techniques relies heavily on the quality of the fingerprint images, and thus, pre-processing is a very important step.

The stages of pre-processing are as follows:

  • Grayscale Transformation

  • Image Normalization

  • Segmentation

  • Directional Map

  • Frequency Map

  • Gabor's Filtering

  • Skeletonization

  • Minutiae Detection

  • Singularity Detection

Dataset

Dataset used for this project can be found here.

Results

The output images contain result of each pre-processing step.

results