Face Recognition Door Unlock System
Vijayalakshmi. M1, Krishna Vamsi Thulluri2, Charan Sai Kanchana3

1Vijayalakshmi.M, Assistant Professor, SRM Institute Of Science And Technology, Chennai, Tamil Nadu, India. 

2Krishna Vamsi Thulluri, B.Tech Department of CSE 4th Year, SRM Institute Of Science And Technology, Chennai, Tamil Nadu, India.

3Charan Sai Kanchana, B.Tech Department of CSE 4th Year, SRM Institute Of Science And Technology, Chennai, Tamil Nadu, India.

Manuscript received on 15 September 2019 | Revised Manuscript received on 23 September 2019 | Manuscript Published on 11 October 2019 | PP: 1133-1139 | Volume-8 Issue-11S September 2019 | Retrieval Number: K113309811S19/2019©BEIESP | DOI: 10.35940/ijitee.K1133.09811S19

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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Face recognition system is widely used for human identification particularly for security functions. The project deals with the look and implementation of secure automatic door unlockby using Raspberry Pi. Web camera for capturing the images from the video frame is operated and controlled by raspberry pi using Open CVPython library to train and store human faces for recognition. In this project we are using Raspberry Pi as face recognition module to capture human images and it will compare with stored data base images. If it matches with authorized user then system allows to supply power to electromagnetic lock to create magnetic field for unlocking the door. The need for facial recognition system that is fast and accurate is continuously increasing which can detect intruders and restricts all unauthorized users from highly secured areas and aids in minimizing human error. Face recognition is one of the most Secured System than the biometric pattern recognition technique which is used in a large spectrum of applications.The time and accuracy factor is considered about the major problem which specifies the performance of automatic face recognition in real time environments. Various solutions have been proposed using multicore systems. By considering present challenge, this provides the complete architectural design and proposes an analysis for a real time face recognition. Thus, the image extracted and allowed to match with the database pictures. If the images are matched, the door unlocks mechanically. the planning of the face recognition system exploitation Raspberry pi will create the smaller, lighter and with lower power consumption, therefore it’s a lot of convenient than the PC-based face recognition system. Principle element analysis LBPH (Local Binary Pattern Histogram) algorithmic program is employed for the face recognition and detection method. Then acknowledgement are send through Zigbee module from transmitter to receiver. If image isn’t detected in database then it’ll ask for manual four digit pin for unlocking the door.The developed theme is affordable, fast, and extremely reliable and provides enough flexibility to suits any environment of various systems. Problem Statement:In theworld of emerging technology, security became an essential component in day to day life. Information theft, lack of security and violation of privacy etc. are the essential components which are needed to be protected. Using smart secure systems for door lock and unlocking became popular nowadays. This is system is being adapted by many countries and first grade countries such as USA, Japan etc., already makes use of this system. This system provides either a facial recognition security feature or a keypad is provided to enter the passcode which unlocks the door. Although, it provides security to the doors, it also has somelimitations and drawbacks: Firstly, if the system mainly uses a facial recognition module, there might be a slight chance that sometimes the face may not be detected and hence the door cannot be unlocked. Secondly, if the system uses a keypad to enter the passcode to unlock the door, there might be a chance that the key maybe be recorded or can be observed by others without users consent. Hence, a two-step verification is developed which makes use of facial recognition as first step and passcode as its following step. But the same issues pertain in the newly developed system. Thus, a new model which rectifies all the above issues is developed.

Keywords: Face recognition; Local Binary Histograms; keypad password; electromagnetic lock.
Scope of the Article: Optical Phase Lock Loop