Masked Face Detection using the Viola Jones Algorithm: A Progressive Approach for less Time Consumption

Abstract

The use of CCTV surveillance is today’s need inpublic and private sector for ensuring security against terrorismand robbery. Regular expressions are used to signify enormoussets of motion attributes captured in video. The video vigilanceis popular system without using human interference to captureimportant scenes. The motive of the work is to introduce automaticrevelation of masked objects in real time with a surveillancecamera. The main aim is to detect masked person automaticallyin less time period. In this paper,the researcher proposes a systemthat consists methods which uses four variant steps that are thesteps of calculating distance range of person from the camera,eye or vision line detection and face part detection such asmouth detection and face detection. Performance of proposedalgorithm is carried out on various real time inputs. Experimentalevaluation shows that proposed algorithm exceeds better in termsof time consumption. This unique approach for the problemhas created a method transparent and easier in complexity sothat the real time implementation can be made beneficial andworkable. Analysis of the algorithms fulfillment on the test videotrack gives appropriate judgments for additional improvementsin the masked face detection performance. Finally, based on theresearch, the axioms were useful for the work which can beusually accessible from available algorithms.