Copyright © 2025 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

@article{176443,
        author = {Vedant Umesh Patil and Sanju Narayan and Arindam Ghosh},
        title = {A Lightweight Face Recognition System Using Haar Cascade for Real-Time Applications},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {11},
        pages = {7127-7130},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=176443},
        abstract = {Facial recognition plays a vital role in contemporary access control, attendance systems, and surveillance technologies. However, many advanced recognition systems rely heavily on computationally intensive models, making them unsuitable for deployment in low-resource environments. This paper proposes a lightweight and efficient face recognition framework using Haar Cascade classifiers, optimised for real-time performance without the need for GPU acceleration or deep learning architectures. The system employs OpenCV’s pre-trained haarcascade_ frontalface_default.xml for rapid face detection, focusing on frontal face recognition under standard lighting conditions. For identification, a simple yet effective machine learning technique compares captured facial data to a set of registered entries, enabling reliable verification with minimal computational overhead. Experimental validation demonstrates that the framework performs well in recognising users quickly and accurately, making it ideal for scenarios such as classroom attendance, basic voting systems, and entry-level security solutions. Its ease of use, low hardware requirements, and adaptability make it a strong candidate for practical applications where resource efficiency is critical.},
        keywords = {Face Recognition, Haar Cascade, Computer Vision, Image Processing, Real-Time Detection, OpenCV},
        month = {April},
        }