Traffic Violation Detection using Principal Component Analysis and Viola Jones Algorithms

Abstract

This paper describes an application to detect traffic rule violation using principal component analysis algorithm(PCA).The proposed system will detect crowded bikes using PCA and Viola Johnson algorithms. The viola-Jones computation is seen as convincing in order to check and focus the face features. The face acknowledgment is strategy of perceiving region of face from a picture of one or different individuals together. The perceived face is removed in the proposed using the viola-Jones estimation. This application uses camera to recognize the amount of faces in the edge which identifies with number of people going in a bike. As indicated by the organization controls only two adults or two adults and one adolescent are permitted to go in a bike. We use Violo Johnes and PCA Algorithm to perceive the appearances to choose the amount of faces in the edge. Consequently the endeavor derives that through this structure we execute OCR to check the number plate to recognize the bike liberating with numerous people. This is a customized system to keep up a vital good ways from the accident by driving past the limited part on bike. At the point when our system perceives the over-trouble vehicle, the number plate of the vehicles is discovered using OCR.