Face Detection and Recognition Using  HOG and OpenCV for Intelligent  Surveillance Systems

Author(s)	Mr. Utkarsh, Shivam Kumar, Sandeep Gaur, Tanu Pandey, Mr. Rup Kamal
Country	India
Abstract	This project presents an intelligent surveillance system that performs face detection and recognition using Histogram of Oriented Gradients (HOG) and OpenCV. The system first processes video or image input to identify human faces by extracting gradient-based features through the HOG method, which is effective in capturing facial structure and shape. Once faces are detected, the system applies a recognition technique to match them with a pre-trained dataset of known individuals. The proposed approach is designed to work in real-time, making it suitable for security applications such as monitoring restricted areas, attendance systems, and access control. By combining the efficiency of HOG with the flexibility of OpenCV, the system achieves reliable performance under varying lighting and environmental conditions. This project demonstrates a cost-effective and scalable solution for modern surveillance needs.
Field	Engineering
Published In	Volume 7, Issue 2, March-April 2026
Published On	2026-04-30

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