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

• 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

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

• 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

• Command line tool for evaluating predictions

• Example program that uses fplib sources to create a fingerprint identification model

Original image	Skeletonized
Original image	Segmented
Ridge orientations	Minutae

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