Image Processing In Automotive Safety

Image Processing  In  Automotive Safety

ABSTRACT

Dozens of processors control every performance aspect of today’s automobiles, and not a single feature of the “vehicle experience” remains untouched by technology. Whether its climate control, engine control, or entertainment, there has been constant evolution of capabilities in manufacturer offerings over the last decade.
 Since Electronics is making its road in the automotive sectors. With hand in advance electronics technologies automotive sector if fully lightened. Several processors and sensors are continuing their services in automation, control and in safety without alteration of basics. Here this paper focuses light on video in automobile in areas like airbag deployment. Collision avoidance. With Image processing technique lane departure is explained with example  
Information processing capabilities of imaging processing presently lack the robustness and rich complexity found in biological systems. Endowing artificial systems with the ability to adapt to changing conditions requires algorithms that can rapidly learn from examples. We demonstrate the application of one such learning algorithm on an inexpensive process constructed to perform critical tasks in automotive industry sensor. The image processor learns to track a particular object by discovering the salient visual and auditory cues unique to that object. The system uses a convolution neural network to combine color, luminance, motion, and auditory information. The weights of the networks are adjusted using feedback from a teacher to reflect the reliability of the various input channels in the surrounding environment.

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