Real-time automated road, lane and car detection for autonomous driving

Birdal, Tolga and Erçil, Aytül (2007) Real-time automated road, lane and car detection for autonomous driving. In: DSPincars 2007, Istanbul

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In this paper, we discuss a vision based system for autonomous guidance of vehicles. An autonomous intelligent vehicle has to perform a number of functionalities. Segmentation of the road, determining the boundaries to drive in and recognizing the vehicles and obstacles around are the main tasks for vision guided vehicle navigation. In this article we propose a set of algorithms which lead to the solution of road and vehicle segmentation using data from a color camera. The algorithms described here combine gray value difference and texture analysis techniques to segment the road from the image, several geometric transformations and contour processing algorithms are used to segment lanes, and moving cars are extracted with the help of background modeling and estimation. The techniques developed have been tested in real road images and the results are presented.
Item Type: Papers in Conference Proceedings
Subjects: T Technology > T Technology (General)
T Technology > TA Engineering (General). Civil engineering (General)
Divisions: Faculty of Engineering and Natural Sciences
Depositing User: Aytül Erçil
Date Deposited: 30 Oct 2007 22:49
Last Modified: 26 Apr 2022 08:43

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