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Real Time Face Recognition using Raspberry Pi

by Sanchit Dass, Mohammed Sadrulhuda Quadri, Navaz Pasha, Nishant Nayan, Jyothi S Nayak
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 176 - Number 33
Year of Publication: 2020
Authors: Sanchit Dass, Mohammed Sadrulhuda Quadri, Navaz Pasha, Nishant Nayan, Jyothi S Nayak
10.5120/ijca2020920387

Sanchit Dass, Mohammed Sadrulhuda Quadri, Navaz Pasha, Nishant Nayan, Jyothi S Nayak . Real Time Face Recognition using Raspberry Pi. International Journal of Computer Applications. 176, 33 ( Jun 2020), 1-4. DOI=10.5120/ijca2020920387

@article{ 10.5120/ijca2020920387,
author = { Sanchit Dass, Mohammed Sadrulhuda Quadri, Navaz Pasha, Nishant Nayan, Jyothi S Nayak },
title = { Real Time Face Recognition using Raspberry Pi },
journal = { International Journal of Computer Applications },
issue_date = { Jun 2020 },
volume = { 176 },
number = { 33 },
month = { Jun },
year = { 2020 },
issn = { 0975-8887 },
pages = { 1-4 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume176/number33/31413-2020920387/ },
doi = { 10.5120/ijca2020920387 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:44:06.321914+05:30
%A Sanchit Dass
%A Mohammed Sadrulhuda Quadri
%A Navaz Pasha
%A Nishant Nayan
%A Jyothi S Nayak
%T Real Time Face Recognition using Raspberry Pi
%J International Journal of Computer Applications
%@ 0975-8887
%V 176
%N 33
%P 1-4
%D 2020
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Face recognition is a fast growing and challenging area in the field of computer vision and real time applications. A lot of techniques and algorithms are available with varying degrees of accuracy and speed. Face recognition has a lot of applications in the field of advertising, healthcare, security, accessibility, and even payments. Hence, there is a need for low cost, reliable and accurate face recognition systems in todays world [3]. The aim is to implement a face recognition system using a Raspberry Pi device. This system is part of an assistive device created by us for visually impaired people. The setup consists of a Raspberry Pi 3 Model B device with a camera module attached to it. The Raspberry Pi has a 1.2 GHz 64-bit CPU along with 1 GB RAM and the camera module has a resolution of 5 MP.

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Index Terms

Computer Science
Information Sciences

Keywords

Face Recognition Raspberry Pi Computer Vision LBPH Haar Cascade Real Time

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