基于改进随机Hough变换的直线检测算法

Line Detection Algorithm Based on Improved Random Hough Transformation

针对标准Hough变换在直线检测中存在的问题,提出了一种基于改进随机Hough变换的直线检测算法。利用8邻域搜索对边缘图像像素点进行了聚类分组;提出了像素点梯度方向差分概念,求出每一个边缘分组中相邻像素点的梯度方向差分,从而进行直线预检测,排除不含直线特征的边缘组;基于随机抽样一致性算法,提出了一种带有直线参数模型预检验的改进随机Hough变换算法。研究结果表明,该算法有效解决了标准Hough变换中的问题,改善了直线检测过程中的误检情况,具有检测速度快、检测精度高的优点。

Aiming at the existing problems in the line detection for standard Hough transform, a line detection algorithm based on improved random Hough transform is proposed. The pixels of edge images are clustered and grouped by 8-neighborhood search. The concept of the pixel gradient direction difference is proposed, and the gradient direction difference between adjacent pixel is calculated in each edge group, thus the line pre-detection is carried out to exclude the edge groups without line features. Based on the theory of the random sample consensus algorithm, the improved random Hough transformation algorithm with a linear parameter pre-test model is proposed. The research results show that the proposed algorithm effectively solves the problem in standard Hough transform and improves the error detection rate in the process of line detection. The proposed algorithm has the advantages of fast detection and high detection accuracy.