Eigen face Detection and Criminal Identification System Using Artificial Neural Network

Abstract

Identifying and authenticating a criminal is a time-consuming and challenging task. According to a survey by the National Crime Archives, 80% of repeat offenders commit the same crimes over and over again. Criminals are becoming smarter than leaving any biological evidence or fingerprints at crime scenes. A face is a complex Multidimensional scene modeling and face recognition creating a computational model is difficult. Face image coding and of an information theory approach to coding the paper basically provides a face recognition algorithm. The face is a unique and important feature of the structure of the human body that identifies a person. This facial recognition can be used to identify criminals from a pic ture or video frame by cameras mounted in many areas. As a result, it can be used to trace the identity of a criminal. Face recognition uses biometrics to map a person's facial features statistically and save the information as a face print. Every face is given a distinctive shape, which It compares to other photos in the collection. If a match is found with the input face, In formation related to the corresponding image will be shown. This strategy will lessen crime and safeguard public safety. For the test batch, nearly all recognition scores were calculated taking feature extraction into account. The model's overall Cron bach's Alpha rating is 0.616, which denotes a 61% reliability level.