基于Hough变换的红外图像道路边界检测方法

B. Fardi, G. Wanielik
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引用次数: 38

摘要

本文介绍了一种用于红外图像中道路边界检测的实时图像处理算法。其基本思想是通过车辆坐标系中道路边线之间的平行度来耦合道路边线。由于透视投影,两条线的平行度在图像平面上的收敛中被转换。在这个平面上,两条直线在地平线上的一点相交。新的想法是利用地平线上的这个共同点来找到霍夫域中的道路边界。霍夫变换的输入数据由一组局部正则化边缘检测器和图像的自适应阈值产生。由于图像大多对比度较低,小核的边缘检测器很难实现边缘提取。因此,使用高斯金字塔技术对图像进行次采样,并在实验确定的最佳分辨率水平下进行预处理。所开发的算法已在一辆装有红外摄像机的实验车上实现,并在不同情况下进行了成功的测试。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Hough transformation based approach for road border detection in infrared images
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.
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