Abstract
In this paper, the design and development of a home security system has been detailed which uses facial recognition to conform the identity of the visitor and taking various security measures when an unauthorized personnel tries accessing the door. It demonstrates the implementation of one of the most popular algorithm for face recognition i.e. principal component analysis for the purpose of security door access. Since PCA converts the images into a lower dimension without losing on the important features, a huge set of training data can be taken. If the face is recognized as known then the door will open otherwise it will be categorized as unknown and the microcontroller (Arduino Uno) will command the buzzer to start ringing.
Highlights
With the advancement in the areas of personal identification in access control and technologies such as biometric identification seem to be gaining more popularity over the use of cards, pattern or password
In this paper we have proposed a system which comprises of dimensional reduction of the images, facial recognition, classification and a door access security system [4]
We can see from the set of images below that as we go further down, there is an increase in the variance or noise in the images, rather than considering all the Eigen faces an optimal number of them is chosen
Summary
With the advancement in the areas of personal identification in access control and technologies such as biometric identification seem to be gaining more popularity over the use of cards, pattern or password Such system requires the individual to touch the hardware for identification which is not the case in face recognition systems and has an added advantage making it a much quicker and efficient process [1]. When the person has been classified as known the servo motor would rotate a certain angle signifying access to the door where as if the person is categorized as unknown, the system takes security measures such as raining the alarm with the blinking of the red led [7] In this system, PCA and face classification has been implemented with the help of MATLAB installed on PC.
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