Course Content

The aim is to recognize person identity based on brain activity, measured by EEG signals. Recently, classification from EEG data has attracted much attention with the rapid development of machine learning algorithms, and various real-world applications of brain–computer interface for normal people. Until now, researchers had little understanding of the details of relationship between different emotional states and various EEG features. With the help of EEG-based human identification, the computer can have a look inside user’s head to observe user's mental state. We systematically perform feature extraction, feature selection, feature smoothing and pattern classification methods in the process. The best features extracted are specified in detail and their effectiveness is proven by classification results. Human identification based on Face recognition is one of the latest technology being studied area in biometric as it has wide area of applications. But Face detection is one of the challenging problems in Image processing. The basic aim of face detection is determine if there is any face in an image & then locate position of a face in an image. Evidently face detection is the first step towards creating an automated system which may involve other face processing. The deep learning neural network needs to be created & trained with training set of faces & non-faces. All results are implemented in MATLAB 2013 environment. Database is collected for different persons from online EEG data base which is meant for research.