ON ONE APPROACH TO RECOGNIZING FUZZY IMAGES OF FACES BASED ON AN ENSEMBLE

Abstract

This article implements and analyzes face recognition algorithms based on fuzzy image representations using several major classifiers, including decision tree, random forest, and kNN. The main focus is on the extraction of informative features for the correct recognition and classification of the human face. The algorithms under study recognize a person by their eyes if their face is covered with something. According to the results of the research, the accuracy of the kNN, random forest and decision tree algorithms is 95.5%, 96.1% and 92.3%, respectively. In order to improve the results, the ensemble learning method was implemented, which allows to combine several classification results using a metaclassifier. As a result of the ensembling, the accuracy was 96.8\%, exceeding the accuracy of each algorithm.