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dc.contributor.advisorRahman, Md. Khalilur
dc.contributor.authorSakib, Sadman
dc.contributor.authorWadud, M. M. Abdul
dc.contributor.authorArnob, Fakid Tazbid
dc.date.accessioned2021-06-07T13:42:14Z
dc.date.available2021-06-07T13:42:14Z
dc.date.copyright2019
dc.date.issued2019-12
dc.identifier.otherID: 13121041
dc.identifier.otherID: 13221041
dc.identifier.otherID: 13321013
dc.identifier.urihttp://hdl.handle.net/10361/14495
dc.descriptionThis thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Electrical and Electronic Engineering, 2019.en_US
dc.descriptionCataloged from PDF version of thesis.
dc.descriptionIncludes bibliographical references (page 31).
dc.description.abstractWith the help of recent technological advancement the world is moving towards an era of advance security systems. For every single purpose or system the main concern is safety. As software based security system creates a good vibe in the security industry because of its robustness so people are more interested to use it in different places like office or even at home. For ensuring an efficient security system and a solid surveillance camera vision has been used vastly nowadays. In this research an image processing based low cost home security system has been approached for home safety and surveillance. Different image processing algorithms based on python, deep learning, Convolutional Neural Networks has been used for better output. Algorithm based on Haar Cascade Classifiers using open CV gives the desired results for low cost components. An IOT based mobile application which is also a part of the total system helps the user to ensure a notification based surveillance system when the user is away from home. Different experimental analysis based on different data sets justify the efficiency as well as sustainability of the total system for real life scenario.en_US
dc.description.statementofresponsibilitySadman Sakib
dc.description.statementofresponsibilityM. M. Abdul Wadud
dc.description.statementofresponsibilityFakid Tazbid Arnob
dc.format.extent31 Pages
dc.language.isoen_USen_US
dc.publisherBrac Universityen_US
dc.rightsBrac University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission.
dc.subjectFace Recognitionen_US
dc.subjectHome Security Systemen_US
dc.titleFace recognition based home security systemen_US
dc.typeThesisen_US
dc.contributor.departmentDepartment of Electrical and Electronic Engineering, Brac University
dc.description.degreeB. Electrical and Electronic Engineering


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