Intelligent Classifier of Banknotes: an approach to Principal Component Analysis and Artificial Neural Networks

Abstract

This paper proposes a method to assist visually impaired people to identify banknotes of Brazilian Real (BRL). The method uses the combination of the technique of Principal Component Analysis (PCA) and artificial neural networks (ANN). The PCA is used in pre-processing the images to reduce the dimensionality of the data. The coefficients obtained with the PCA is used as input to a classifier based on artificial neural network Multilayer Perceptron (MLP). In several experiments, the success rate was 100%. The results obtained with the method were satisfactory. The proposed method has shown promise. It is hoped in the future to recommend its use in helping blind people.

Publication
In Proceedings of 9th Brazilian Workshop on Computer Vision (WVC)

Text in Portuguese, with English title and abstract.

Allan Kardec
Allan Kardec
Master’s Student

Fabrizzio Soares is bla bla bla.

Fabrizzio Soares
Fabrizzio Soares
Associate Professor and CS Chair

Fabrizzio Soares is a professor of Computer Science, Information Systems and Software Engineering at INF/UFG. His research interests include Computer Vision, Human Computer Interaction, Machine Learning and Programming topics. He is the leader of the Pixellab group, which develops solutions for accesibilty, Precision Agriculture, and Interactive Systems.

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