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PyFnPrint

Simple fingerprint recognition library written in Python3. The library implements various fingerprint preprocessing and recognition methods along with evaluation and database splitting utilities

Structure

fplib

  • The library sources containing the following modules:
    • image.py - a wrapper for a fingerprint image with a filename like "${id}_${number}.${ext}" and lazy file reading
    • preprocess.py - preprocessing module containing various image quality enhancing functions and functions for extraction of ridge characteristics
    • binarize.py - binarization module wrapping various opencv calls
    • filter.py - filtering module supporting custom kernels and gabor filtering
    • minutae.py - minutae points extraction and preprocessing module supporting core point detection
    • feature.py - feature extraction and comparison module
    • plot.py - plotting module for various stages of preprocessing

db/PNG

  • Database containing 128 high quality fingerprint images 8 for each user
  • More challenging are databases used by the FVC competition

dbsplit.py

  • Command line tool for splitting any amount of fingerprint images into a single filesystem database with train/test structure. Generates test.csv file which can be used for remote evaluation of predictions

evaluation.py

  • Command line tool for evaluating predictions

example.py

  • Example program that uses fplib sources to create a fingerprint identification model
Original image Skeletonized
Original image Segmented
Ridge orientations Minutae

Prerequisites:

  • Python3 interpreter
  • Dependencies: numpy, opencv2, skimage, matplotlib, pandas, seaborn