CRIMINAL FACE DETECTION USING 2D IMAGE

CRIMINAL FACE DETECTION USING 2D IMAGE

Prof Neelam Jadhav, Sawai Komal Kadunath, Muluk Sayali Siddheshwar, Kharche Rutuja Bhanudas, Kondalkar Sakshi Kiran

ABSTRACT

A criminal record contains both personal information about a person and an image of that person. To identify a criminal, we need personal information about that person, which an eyewitness can supply. Fingerprints, eyes, and DNA are all methods for identifying someone. One of the uses is face recognition. The face is our primary focus of attention in social interactions, and it plays a vital role in communicating identity and emotion. Although it is impossible to discern intelligence or character from a person's face, humans have an exceptional ability to remember and distinguish faces.  An automatic facial recognition system for criminal records was proposed using the well-known Principal Component Analysis technique. This technology will be able to detect and distinguish faces automatically. If there is no thumbprint on the scene, law enforcement will have an easier time locating or identifying the suspect. The goal of this project is to examine several techniques to face detection and recognition in order to create a full solution for image-based face detection and recognition that is more accurate, has a better response rate, and may be utilized as a first step in video surveillance. The proposed solution is based on testing results from multiple face-rich datasets in terms of subjects, position, emotions, and light.

Keywords: CIS, CNN, Deep learning, criminals, Criminal face detection