Security and Safety With Facial Recognition Feature for Next Generation Automobiles
Nalini Nagendran1, Ashwini Kolhe2

1Nalini Nagendran, VIT, Vellore (Tamil Nadu), India.
2Ashwini Kolhe, VIT, Vellore (Tamil Nadu), India.
Manuscript received on 13 December 2018 | Revised Manuscript received on 24 December 2018 | Manuscript Published on 09 January 2019 | PP: 289-294 | Volume-7 Issue-4S November 2018 | Retrieval Number: E2016017519/19©BEIESP
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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: This is the era of automated cars or self-driving cars. All car vendors are trying to come up with different advancements in the cars (Like Automatic car parking, Automatic Lane changing, automatic braking systems, android auto, car connect, Vehicle to external environment technology etc). In the automation industry, TESLA, Google and Audi are the most competent leader among each other as well as for other automation business also. Modern vehicles are all equipped with different technologies like navigation system, driver assistant mode, weather mode, Bluetooth, and other safety features which brings broader impact to quality of human’s life, environmental sustainability. This paper explains how the proposed feature, unlocks the semiautonomous cars or autonomous cars safely and provides the safety to the entry level cars. The acknowledged pictures are put away in the picture database amid confront acknowledgment by utilizing Support Vector Machine (SVM) classifier. Information from confront pictures through picture pressure utilizing the two-dimensional discrete cosine change transformation (2D-DCT). A self-arranging map (SOM) utilizing an unsupervised learning method is utilized to order DCT-based element vectors into gatherings to distinguish if the picture is “available” or “not available” in the picture database. The face is detected by the event that the framework perceives faces, only the authentic users are able to start the ignition of the car and untheorized users are not allow to start the ignition.
Keywords: Face Detection, Controller, Autonomous Vehicles, Safety, New Feature, Driverless Cars, SVM.
Scope of the Article: Pattern Recognition