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dc.contributor.advisorUddin, Dr. Jia
dc.contributor.authorKhan, Mahjabeen
dc.date.accessioned2017-01-19T06:30:50Z
dc.date.available2017-01-19T06:30:50Z
dc.date.copyright2016
dc.date.issued11/14/2016
dc.identifier.otherID 14101272
dc.identifier.urihttp://hdl.handle.net/10361/7623
dc.descriptionCataloged from PDF version of thesis report.
dc.descriptionIncludes bibliographical references (page 33-35).
dc.descriptionThis thesis report is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2016.en_US
dc.description.abstractSecurity nowadays is a very important issue so Smart Security System based on Frontal Face Detection Method and Android Mobile was conceived with the idea that it will offer protection. This system consists two parts where the first is the Bluetooth connectivity via Andriod phone to an electric door lock forwarded by face detection system via camera. It is done by OpenCv in Python using Local Binary Patterns Histograms (LBPH) Recognizer algorithm. The Bluetooth is connected with an app on the Android phone. The app will seek password that is saved in the system. If there is a match in the password, the process move forwards towards face detection program. The recognizer is trained earlier with the images stored in the database. As a face appears in front of the camera, the system compares it with those photos in the database. LBPH works by characterizing the local patterns in each location in the image and thus it analyzes the image. The system will decide whether to restrict or allow any person depending on the comparison result. Experimental results show that the proposed method exhibited 100% accuracy for a tested data set.en_US
dc.description.statementofresponsibilityMahjabeen Khan
dc.format.extent35 pages
dc.language.isoenen_US
dc.publisherBRAC Universityen_US
dc.rightsBRAC University thesis 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.subjectSmart security systemen_US
dc.subjectFrontal face detection methoden_US
dc.subjectAndroid mobileen_US
dc.titleSmart security system based on frontal face detection method and android mobileen_US
dc.typeThesisen_US
dc.contributor.departmentDepartment of Computer Science and Engineering, BRAC University
dc.description.degreeB. Computer Science and Engineering


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