利用梯度信息快速提取直线边缘特征

立足于视觉检测系统的实时性需要,提出一种利用梯度信息的快速直线边缘提取方法。该方法首先利用梯度信息和两点确定一条直线进行线段基元的快速定位和扫描;然后对扫描得到的线段基元进行基于几何距离最小化的最佳直线拟合;最后使用端点投影距离的方法对线段基元进行共线性检测,连接共线的线段基元并对连接结果重新进行最佳直线拟合,得到最终的直线边缘特征。实验结果表明:该方法进行直线边缘特征提取的速度比目前文献中最快的Hough变换改进算法提高了1倍左右,适应能力强,可以满足视觉检测系统对直线边缘特征提取的实时性和精度要求。

Fast line edge feature extraction using image gradients

In order to meet the real-time requirements of vision detection systems, an efficient line edge extraction method using image gradient is proposed. First, by using gradient information of the image and the property that two points define a line, line segments in the image are quickly located and scanned. Then, the scanned line segments are fitted through a method minimizing the geometric distances. Finally, a collinearity judging approach based on the projection distances of line segment endpoints is applied to all the line segments, after which the collinear line segments are linked together and refitted to obtain the final line edge features. Experimental results indicate that the time consumed by the proposed method is only about a half of the fastest improved Hough transform method . Furthermore, with the given parameters, the method is highly adaptable to different images. It can satisfy the real-time and precision requirements of the line edge feature extraction processes in various vision detection systems.