Detection Of Unauthorized Human in Surveillance Video

Abstract: Uniqueness or individuality of an individual face is the representation of one's identity. In this project, the face of an individual is utilized for the automatic detection of unauthorized human entities in surveillance videos. Ensuring security and monitoring unauthorized access are paramount in various environments such as public spaces, private properties, and restricted areas. Traditional surveillance methods often rely on manual monitoring, which is time-consuming and prone to errors. To address these challenges, this project proposes a novel approach based on image processing techniques. Face detection and recognition algorithms are employed to identify individuals captured in surveillance footage. The system maintains a database of authorized personnel, and when a face is detected, it is compared against the database to determine if the individual is authorized or unauthorized. By automating the process of detecting unauthorized human entities, this project aims to enhance security measures and mitigate risks associated with unauthorized access. The system offers real-time monitoring capabilities, reducing the need for manual intervention and enabling timely response to security breaches. Overall, the proposed solution provides an efficient and effective means of safeguarding various environments against unauthorized intrusions.

Keywords: Face recognition, Surveillance, Unauthorized human detection, Image processing, Real-time alerting, Security systems, Machine learning, Facial feature extraction