Traitors and missing person detection with face matching

Face detection and identification system is the highest processing artificial intelligence domain. Many applications got developed based on face detection. In our proposed system an identification of the criminal and missing person over multiple faces has been enhanced. This application will be more helpful to the police men where they will be easily catching the terrorist, criminal, missing person etc. Here the face detection is enhanced using HAAR cascade feature extraction algorithm which completely extracts the feature points and decides the face values. The extraction of the points tends in the matching with server database which is already trained. For the training purpose machine learning training and testing phase are proposed. Neural Network analysis will be more accurate compared to other existing solution. So Recurrent Neural Network (RNN) algorithm classifies the trained features and test features. The principle goal is to generate a system which will be more useful to the police surrounding without watching and noticing people. So CCTV camera based monitoring helps in the face detection and recognition of the criminals and missing person with an alert system. Thus the alert system generates the complete identification of the person according to the camera area. The system will decrease the crime rates and reduce the work of police with security in the environment.