A Lightweight Face Recognition System Using Haar Cascade for Real-Time Applications

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Vedant Umesh Patil; Sanju Narayan; Arindam Ghosh

A Lightweight Face Recognition System Using Haar Cascade for Real-Time Applications

Authors: Vedant Umesh Patil, Sanju Narayan, Arindam Ghosh

Unique Paper ID: 176443
Volume: 11
Issue: 11
PageNo: 7127-7130

Keywords: Face Recognition Haar Cascade Computer Vision Image Processing Real-Time Detection OpenCV

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.

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Cite This Article

ISSN: 2349-6002
Volume: 11
Issue: 11
PageNo: 7127-7130

A Lightweight Face Recognition System Using Haar Cascade for Real-Time Applications

Available:https://ijirt.org/article?manuscript=176443

Impact Factor
8.01 (Year 2024)

UGC Approved
Journal no 47859

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