Evaluation of Supervised Machine Learning Classification Algorithms for Fingerprint Recognition
Andrés Rojas, Gordana Jovanović Doleček · 2021
This paper presents the application of the Classification Learner MATLAB tool from the Statistics and Machine Learning Toolbox for the classification process in a fingerprint recognition system based on the set B from the public databases FVC2000, FVC2002, and FVC2004. The general results indicate that this system can achieve high accuracy values for several sub-databases using multiple supervised machine learning algorithms including decision trees, discriminant analysis, support vector machines, logistic regression, nearest neighbors, naive Bayes, and ensemble classifiers. The highest accuracy value of 98.8% corresponding to the DB3-2000 subset was obtained using the ensemble subspace discriminant classifier.