本文提出了一种新的跨国家的障碍

检测技术为基础的立体视觉系统。

原始图像的预处理的高斯

过滤器和对比度限制的自适应直方图

均衡（ CLAHE ）方法来削弱作用 噪音，光线和对比度。哈里斯的角落位于与子像素精确。

-Cross-country intelligent vehicles always work in

complicated environments with varying illuminations.

The paper presents a new cross-country obstacle

detection technology based on stereo vision system.

The original images are preprocessed by Gaussian

filter and contrast-limited adaptive histogram

equalization (CLAHE) method to weaken the effect of

noise, light and contrast. Harris corners are located

with sub-pixel accurate. To guarantee the overall

system real-time performance, feature-based matching

techniques are studied and fundamental matrix is

calculated based on random sample consensus

(RANSAC). Also restrains are studied to eliminate

pseudo matching pairs. Then data interpolation is

introduced to build elevation maps. Edge extraction

and morphological processing are concerned to

accomplish obstacle detection. Experiment results for

different conditions are presented in support of the

obstacle detection technology.