Human Behaviour Modelling & Analysis Using Artificial Neural Network

This is a survey and classification based on behavioural biometrics which is based on skills, style, preference, knowledge or strategy used by people while accomplishing different everyday tasks such as driving an automobile, talking on the phone, handwriting analysis, face analysis, visual action recoginition, keystroke dynamics, using a computer. In this research, using combination of graphical approach based on signature and digit of character of application form using multi-structure algorithms and artificial neural networks (ANN). We examine current research in the field and analyse the types of features used to describe different types of behaviour by using signature in handwriting analysis .The following feature used in this paper are: orientation, letter spacing, thickness, streaks . Various techniques used for comparing accuracy rates for verification of users using different approaches such as Markov model, Sigma Lognormal model Keywords— Artificial Neural Networks ,Markov Model , Sigma Lognormal Model , Behavioural Biometrics