Advanced Driver Assistance System using Image Processing Techniques
S.V.Jansi Rani1, R.Priyadharsini2, R.Kavya3
1NS.V.Jansi Rani*, Associate Professor, Department of CSE, SSN College of Engineering Chennai, India.
2R.Kavya, Software Engineer, Paypal Chennai, India
3R. Priyadharsini, Software Engineer, Paypal Chennai, India
Manuscript received on November 16, 2019. | Revised Manuscript received on 23 November, 2019. | Manuscript published on December 10, 2019. | PP: 3377-3382 | Volume-9 Issue-2, December 2019. | Retrieval Number: A5201119119/2019©BEIESP | DOI: 10.35940/ijitee.A5201.129219
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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: Driverless car technology is being extensively researched in both academia and industry. But it will take a while until they are sustainable in the present conditions and commercially viable. Until then driving will be done by humans and has room for error like all other humane activities. The driver analysis system tries to gauge the ability of a driver and soundness of their skill. The proposed Advanced Driver Assistance System (ADAS) authenticates a driver by recognizing their face, leaving no room for misuse by unauthorized personnel as well as prevents theft. It keeps track of the driver’s activity by continuously monitoring the driver and detects drowsiness of the driver. When the trip ends, the system produces a summary of the trip with the details.
Keywords: Haar Classifier, HOG, SVM, Computer Vision
Scope of the Article: Image Processing and Pattern Recognition