To obtain real-time terrain information in front of the cross-country intelligent vehicle and effectively detect the possible obstacles, an environment detection method on the basis of stereo vision sensor was presented. Firstly, local image enhancement technology was proposed to weaken the influence of varying illumination and guarantee that the corner features could be extracted with uniform distribution. Secondly, edge features were extracted to avoid miss-detection of obstacles. Thirdly, stereo matching flow based on multi-feature extraction was presented. Fundamental matrix was calculated based on Random Sample Consensus (RANSAC) method. Corner-based matching scheme and edge-based matching scheme were implemented independently to avoid disturbance. Continuity constraint was studied to eliminate pseudo matching. Finally, different cross-country scenes with varying illuminations were collected to test the robust performance of the method.