Facial Recognition with Mobile Application and Artificial Neural Network

This work presents the implementation of a facial recognition system with mobile application for the identification of people/faces. For this, haar-like object detection techniques, filters of luminosity, contrast and grayscale are used. In order to abstract the characteristics, the discrete cosine transform (DCT) and the Laplacian filter were used. In the classification stage it was used the Multi-Layer Perceptron Neural Network (MLP) and Self-Organizing Map (SOM). The interaction flow between the application steps and the classifier has been linked to a web services set. The results reached an accuracy of up to 97%, reaching the objectives proposed for the work.