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Robust Image Processing for an Omnidirectional Camera-based Smart Car Door by Christian Scharfenberger; Samarajiit Chakraborty; Georg Färber is a Computer Science article available to read on EtoBox.

What is Robust Image Processing for an Omnidirectional Camera-based Smart Car Door about?

Over the last decade, there has been an increasing emphasis on driver-assistance systems for the automotive domain. In this article, we report our work on designing a camera-based surveillance system embedded in a “smart” car door. Such a camera is used to monitor the ambient environment outside the car, for instance, the presence of obstacles such as approaching cars or cyclists who might collide with the car door if opened—and automatically control the car door operations. This is an enhancement to the currently available side-view mirrors that the driver/passenger checks before opening the car door. The focus of this article is on fast and robust image processing algorithms specifically targeting such a smart car door system. The requirement is to quickly detect traffic objects of interest from grayscale images captured by omnidirectional cameras. While known algorithms for object extraction from the image processing literature rely on color information and are sensitive to shadows and illumination changes, our proposed algorithms are highly robust, can operate on grayscale images (color images are not available in our setup), and output results in real time. We present a number

Who reads Robust Image Processing for an Omnidirectional Camera-based Smart Car Door?

Author

Christian Scharfenberger; Samarajiit Chakraborty; Georg Färber

Publisher

ACM

Published

2012

Language

EN

Field

Computer Science (Physical Sciences)