dc.contributor.advisor | Uddin, Dr. Jia | |
dc.contributor.author | Khan, Mahjabeen | |
dc.date.accessioned | 2017-01-19T06:30:50Z | |
dc.date.available | 2017-01-19T06:30:50Z | |
dc.date.copyright | 2016 | |
dc.date.issued | 11/14/2016 | |
dc.identifier.other | ID 14101272 | |
dc.identifier.uri | http://hdl.handle.net/10361/7623 | |
dc.description | Cataloged from PDF version of thesis report. | |
dc.description | Includes bibliographical references (page 33-35). | |
dc.description | This 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.abstract | Security 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.statementofresponsibility | Mahjabeen Khan | |
dc.format.extent | 35 pages | |
dc.language.iso | en | en_US |
dc.publisher | BRAC University | en_US |
dc.rights | BRAC 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.subject | Smart security system | en_US |
dc.subject | Frontal face detection method | en_US |
dc.subject | Android mobile | en_US |
dc.title | Smart security system based on frontal face detection method and android mobile | en_US |
dc.type | Thesis | en_US |
dc.contributor.department | Department of Computer Science and Engineering, BRAC University | |
dc.description.degree | B. Computer Science and Engineering | |