Automated Invigilation System for Detection of Suspicious Activities during Examination

Cheating and abnormal activities like- whispering, impersonation or hand contact are widely involved in offline examination around the globe, this hinders the integrity and morality of fair conduction of examination. Video Surveillance systems embeds image and video processing algorithms to monitor, analyse and process various activities and even detection of crime, suspicious activities. The purpose of this research is to design a robust video surveillance system model to monitor and analyse activities during examination, this will allow the academic institutes to detect and identity unfair or suspicious activities during examination. This system model will use automated video as feed to monitor students activities during examination in real-time. We have discussed about various video analytics or video processing and image processing methods and tools involved in surveillance model. We throughout the paper have walk through about the various processes- pre-processing, segmentation, classification, feature extraction and its related video processing algorithm in sequential manner. The proposed model is effective, efficient and requires relatively less processing power.