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ISSN 2063-5346
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CAR IDENTIFICATION FOR BRAKE LIGHT DETECTION USING HAAR CASCADE APPROACH

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Dr. Shailesh V. Kulkarni, Dr. Pravin G. Gawande, Dr. Rajendra S. Talware, Dr. K. J. Raut, Dr. Anup W. Ingle, Vishal B. Ambhore
» doi: 10.31838/ecb/2023.12.s3.364

Abstract

Lighting system in a car is comprising of lighting and signaling components. These are installed inside the vehicle, on the front and at the rare side of the vehicles. Precisely, lighting systems are used for providing illumination inside the vehicle for passengers and at the front of the vehicle for road visibility to the driver. Along with this purpose, the light is also used for indicating the projected activity of the vehicle through signaling. With the passage of time, revolutionary modifications are done in automobile industries. Autonomous vehicles are the recent outcome of such revolutionary changes. There are diverse components which are to be developed in order to bring the autonomous vehicle to the level of human driven vehicles. Out of this numerous building blocks, brake light detection of the forward vehicle is one of the challenging jogs, which can be explored for collision avoidance, maintaining safe distance and forward vehicle activity detection. In the proposed research work, brake light detection of the forward car is projected. The research work is divided in to car identification and brake light detection. In this research paper, car detection using HAAR transformation is explored. The implementation is carried out using Deep Learning Approach and configured using Python language.

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