Real-time and robust road recognition is a key technology in intelligent vehicle research, and plays an important role in vehicle autonomous navigation.
实时、可靠的道路识别是智能车辆研究的一个关键技术，在车辆自主导航中起着重要的作用。
In this paper, a new technique to the problem of road recognition in TM images is presented.
提出了一种新的TM图像中道路目标的识别方法。
Experiments show that the algorithm is both effective and quick, can meet the requirement of road recognition.
实验表明，算法在识别效果和运行速度上都比较理想，能够满足道路识别要求。
A new road recognition algorithm based on local statistical features and principal component analysis is introduced to improve its robustness and adaptiveness.
为了提高道路识别算法的鲁棒性和自适应性，提出了基于局部统计特征和主元分析的道路识别算法。
Parabola detection is a fundamental problem in road recognition application.
抛物线侦测在道路辨识应用中是个十分重要的议题。
Finally, compared with the conventional method of threshold segmentation, the result of the treatment of actual field pictures shows that this algorithm is more effective for the road recognition.
与传统的阈值分割算法的对比处理试验表明，此识别算法可以明显地改善路径识别效果。
Finally, compared with the conventional method of threshold segmentation, the result of the treatment of actual field pictures shows that this algorithm is more effective for the road recognition.
与传统的阈值分割算法的对比处理试验表明，此识别算法可以明显地改善路径识别效果。
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