Hough transformation based approach for road border detection in infrared images

• Main Authors: Fardi, B., Wanielik, G.
• Format: Conference Proceeding
• Language: English
• Subjects: Applied sciences; Cameras; Convergence; Data mining; Exact sciences and technology; Ground, air and sea transportation, marine construction; Image edge detection; Image processing; Image resolution; Infrared detectors; Infrared imaging; Kernel; Road transportation and traffic; Road vehicles
• DOI: 10.1109/IVS.2004.1336443

This paper describes a real-time image processing algorithm for road border detection in infrared images. The basic idea is to couple the road border lines through the parallelism between them in the vehicle coordinate system. The parallelism of the two lines is translated in their convergence in the image plane due to the perspective projection. In this plane the two lines meet at a point on the horizon line. The new idea is to use this common point on the horizon line to find the road border in the Hough domain. The input data for the Hough transformation is created by a set of local regularized edge detectors and an adaptive thresholding of the image. Since the image mostly shows low contrast, the edge extraction can hardly be realized by edge detectors with a small kernel. The image, therefore, is subsampled using the Gaussian pyramid technique and the preprocessing takes place in an optimal resolution level that is experimentally determined. The developed algorithm has been implemented on an experimental vehicle equipped with an infrared camera and was successfully tested in different situations.