Differentiating Monozygotic Twins By Facial Features
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Abstract
Biometrics is a technology which is applied to authenticate an individual by considering their corporeal or comportment characteristics. This expertise technology is mainly used for people who are under scrutiny. There are various types of biometrics traits which can be utilized to recognize an individual and the results shows 100% accuracy. But, in case of Monozygotic twins or identical twins categorizing them is a complex task as they resemble each other in all aspects as they form from a single zygote. Studies shows that even the DNA which is considered to be a unique biometric of every person are similar in case of identical twins. There are various physical biometrics which can be compared such as face, finger print, facial marks, iris, retina, facial features to identify a person. In this paper, the proposed study shows on how to distinguish twins who resemble each other by means of their facial features using the combination of RNN (Recurrent Neural Network) classification and CNN (Convolutional Neural Network) for filters.
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