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Source code of a paper entitled "Face Recognition Using Local Binary Pattern and Nearest Neighbour Classification"

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Face Recognition with LBP and NN

This repository contains the source code of the experiments done in the paper entitled "Face Recognition Using Local Binary Pattern and Nearest Neighbour Classification" . This work will be presented at the 2018 International Symposium on Advanced Intelligent Informatics (SAIN 2018) on August 29-30, 2018 in Yogyakarta, Indonesia.

Structure of the source code

  • db folder Contains three datasets used in this experiment, i.e. JAFFE, AT&T, and Yale
  • localbinarypatterns.py The implementation of LBP using scikit-learn module
  • knn.py The implementaion of the system using k-NN (k Nearest Neighbour)
  • rnn.py The implementation of the system using RNN (Radius Nearest Neighbour)
  • akurasi.py Analyse the system accuracy (recognition rate) in terms of their parameters (number of neighbour points P, the radius P, and the chosen k value of the k-NN)
  • plotting.py Plot the histogram of the feature vector from the LBP output
  • results folder Contains experiments results for both k-NN and RNN, saved in csv files

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Source code of a paper entitled "Face Recognition Using Local Binary Pattern and Nearest Neighbour Classification"

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