从建筑物图像中提取直线是视觉导航、特征识别和遥感影像处理等很多应用中的关键步骤。针对复杂建筑物图像，提出了一种基于边缘方向图的直线特征提取算法。该算法在Canny边缘的基础上，提出边缘方向编码策略，能过检测9×9局部窗口内的直线，将边缘拆分成直线、曲线和点的组合，生成了一种新的直线检测辅助图像——边缘方向图，并通过分析边缘方向图中连续线边缘的方向分布，结合直线误差判别准则和稀疏直线拟合识别直线。实验结果表明：该算法的直线检测性能优于Hough变换和相位编组等经典方法，对建筑物图像的直线检测准确率高，误判率、漏检率低，算法稳健性强。

Detecting lines in a digital image is a crucial step in many applications, such as visual navigation, feature recognition and remote sensing image processing, In this paper, an algorithm which is based on edge orientation image is proposed for extracting straight lines from comples building image. Firstly, edges are detected based on Canny detector. Secondly, an edge direction coding strategy is proposed by detecting the local line in 9×9 window. Thirdly, edges are split into a series of straight lines, curves and points, and a new secondary image — the edge orientation image is generated. Finally, the straight lines are extracted from the edge orientation image by analyzing the direction distribution, and using the straightness errors evaluation strategy and the sparse line fitting algorithm. Experiment results show that the proposed algorithm is better than hough transform and phase grouping algorithm. It can detect lines correctly in complex building images with high accuracy rate, low false and low missing rate and good robustness.