G. Jenifa, N. Yuvaraj and K.R. SriPreethaa, Department of Artificial Intelligence and Data Science, KPR Institute of Engineering and Technology, Coimbatore, India.
Online First : 30 December 2020
Publisher Name : IJAICT India Publications, India.
Print ISBN : 978-81-950008-0-7
Online ISBN : 978-81-950008-1-4
Page :229-231
Abstract
Home security system plays a predominant role in the modern era. The purpose of the security systems is to protect the members of the family from intruders. The main idea behind this system is to provide security for residential areas. In today’s world securing our home takes a major role in the society. Surveillance from home to huge industries, plays a significant role in the fulfilment of our security. There are many machine learning algorithms for home security system but Haar-cascade classifier algorithm gives a better result when compared with other machine learning algorithm This system implements a face recognition and face detection using Haar-cascade classifier algorithm, OpenCV libraries are used for training and testing of the face detection process. In future, face recognition will be everywhere in the world. Face recognition is creating a magic in every field with its advanced technology. Visitor/Intruder monitoring system using Machine Learning is used to monitor the person and find whether the person is a known or unknown person from the captured picture. Here LBPH (Local Binary Pattern Histogram) Face Recognizer is used. After capturing the image, it is compared with the available dataset then their respective name and picture is sent to the specified email to alert the owner.
Keywords
LBPH, OpenCV, Face recognition.
Cite this article
G. Jenifa, N. Yuvaraj and K.R. SriPreethaa, “Visitor/Intruder Monitoring System using Haar-cascade Classifier Algorithm”, Innovations in Information and Communication Technology, pp. 229-231, December 2020.
Copyright
© 2020 G. Jenifa, N. Yuvaraj and K.R. SriPreethaa. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
