针对传统Hough变换用于直线检测存在的问题进行了细致的分析和归纳总结，在此基础上，提出一种结合边缘编组的Hough变换直线提取算法。该算法首先采用基于8邻域的边缘跟踪算法对Canny算子检测得到的边缘点进行编组；然后对每一个边缘组分别进行Hough变换，单独确定Hough变换原点和参数的取值范围。Hough变换过程中，采用迭代的“投票”方式，每次确定单一峰值点并删除对应像素。实验证明，该算法原理简单，能有效解决传统Hough变换存在的精度不高、计算复杂等问题。同时该算法具有较强的鲁棒性，可以有效处理不同类型的影像数据，适用于并行处理。

This paper analyzes and discusses the main problems of line detection and extraction by traditional Hough transform in detail. Thus, it proposes an algorithm of straight line extraction by Hough transform combining edge grouping. This algorithm first adopts an edge tracking based on eight-neighborhood to group the detected edge points by Canny operator. It then separately performs the Hough transform to each edge group obtained by grouping, and individually determines the origin of the Hough transform and the range of parameter. This algorithm uses the iterative vote scheme to determine the single peak and the corresponding points to be deleted. The experimental results prove that the proposed algorithm is simple in principle and can effectively solve problems in the traditional Hough transform, such as low precision and complex computation. The proposed algorithm has robustness, can process different content images, and is suitable for parallel processing.