CRIME DETECTION SYSTEM USING FACE RECOGNITION

Abstract

Real-time crime detection application using face recognition. Identication of criminal is done through thumbprint identication. However, this type of identication is constrained as most of criminal nowadays getting cleverer not to leave their thumbprint on the scene. With the advent of security technology, cameras especially CCTV have been installed in many public and private areas to provide surveillance activities. The footage of the CCTV can be used to identify suspects on scene. In this paper, an automated facial recognition system for criminal database was proposed. This system will be able to detect face and recognize face automatically. The results show that about 98% of input photo can be matched with the template data. Face recognition is one of the most challenging topics in computer vision today. It has applications ranging from security and surveillance to entertainment websites. Face recognition software are useful in banks, airports, and other institutions for screening customers. Human face is a dynamic object having high degree of variability in its appearance which makes face recognition a difcult problem in computer vision. In this eld, accuracy and speed of identication is a main issue. It is a particular form of biometric technology that describes the automatic face identication of computing systems by looking at the face. As a result, a robust system with good generalisation capability can be built by adopting cutting-edge techniques from learning, computer vision, and pattern recognition. Earlier methods treated face recognition as a standard pattern recognition problem; later methods focused more on the representation aspect after realising its uniqueness using domain knowledge; and more recent methods have been concerned with both representation and recognition. This system consists of four phases- database creation, face detection, face recognition, attendance updation. The goal of this paper is to evaluate face detection and recognition techniques and provide a complete solution for image based face detection and recognition with higher accuracy, better response rate and an initial step for video surveillance.