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      Prevention of unauthorized door access using face recognition built with Haar Cascade Classifier and Histogram of Oriented Gradients

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            Abstract

            With the emergence of Internet of Things (IoT) along with its development of advanced authentication, both security and remote monitoring have become imperative as well as essential, and the need for smarter security systems has only been growing. The traditional system needs an individual to use a key or an identification (ID) card or a password to access the security doors. However, they have many limitations such as keys can be forged, recreation of ID cards and passwords can be stolen. To overcome, the existing system issues, a novel approach is proposed with the design and development of face authenticated web-based smart door lock control system using facial recognition and remotely monitoring the door. In this proposed system OpenCVs self-trained Haar Cascade Classifier along with Histogram of Gradient is used for face Recognition. Door will be unlocked when users face is recognised else will remain closed. In case an unauthorised person is found, the time of intrusion and the intruders image will be captured and sent to a separate server on discord, so that the user or the admin can view them at their convenience. The main usage of this system is to assist users for improvement of the door security of sensitive locations by using face recognition and is also designed by considering the physically challenged persons also.

            Content

            Author and article information

            Journal
            ScienceOpen Preprints
            ScienceOpen
            20 May 2020
            Affiliations
            [1 ] GITAM, Bengaluru
            [2 ] Assistant Professor, GITAM, Bengaluru
            [3 ] Associate Professor, GITAM, Bengaluru
            Article
            10.14293/S2199-1006.1.SOR-.PPPVL0J.v1
            eadab3a6-58de-4fbb-89ac-cd064041aaf0

            This work has been published open access under Creative Commons Attribution License CC BY 4.0 , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Conditions, terms of use and publishing policy can be found at www.scienceopen.com .


            The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.
            Computer vision & Pattern recognition,Image processing,Artificial intelligence,Computer engineering - Hardware,Electrical engineering,Human-computer-interaction
            Facial Recognition,Discord,Webhooks,IoT,Internet of Things,Home Security,OpenCV,Raspberry Pi,Histogram of Oriented Gradients,Haar Cascade Classifier

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