Identical Twins Facial Recognition System Using Cloud

Abstract

Facial recognition algorithm should be able to work even when the similar looking people are found i.e. also in the extreme case of identical looking twins. An experimental data set which contains 40 images of 20 pairs of twins collected randomly from the internet. The training is done with the selected images of the twins using different training algorithms and inbuilt functions available. The extracted features are stored over the Amazon public cloud. As a part of testing phase random images from the dataset trained are selected and upon running it over the system we get the features of those images which then will be compared by extracting the features already stored in Amazon cloud. The stored values and the current image features are compared and result will be displayed on the GUI. Identical twin’s facial recognition system uses the machine learning, image processing algorithms and deep learning algorithms. Regardless of the conditions of the images acquired, distinguishing identical twins is significantly harder than distinguishing faces that are not identical twins for all the algorithms.