边缘轮廓上基于CPDA的图像角点检测

Image corner detection of CPDA-based on edge contour

针对现有的基于弦到点距离累积(CPDA)的角点检测方法无法准确、快速地检测相邻角点等问题,提出了一种基于CPDA的角点检测算法。首先,对不同的曲率阈值、角度阈值和弦长进行对比实验,选择1个可以准确检测相邻角点的弦长;其次,利用Canny边缘检测器检测边缘,再将弦长用于曲率估计,得到曲线上各像素点的曲率,利用曲率阈值判断是否为候选角点。最后,利用角度阈值将误检点去除,得到最终角点。实验结果表明,与CPDA和其他3种经典检测器相比,提出的检测器具有良好的角点定位性能。对于Checkerboard图来说,本算法检测器检测到的正确角点数为49,与标准检测情况具有相似的检测性能。对于Lab图来说,提出的检测器具有最佳的角点定位性能,其定位误差仅为1.477。与FAST、GCM和CPDA检测器相比,该检测器在漏检点数、误检点数和检测速度方面也获得了最佳性能。

Coupled with slow detection speed,the existing corner detection methods based on chord-to-point distance accumulation(CPDA)can not accurately detect adjacent corners,a fast and accurate CPDA based corner detection algorithm was proposed.Firstly,comparative experiments were carried out to investigate the curvature threshold,angle threshold and chord length,and a chord was selected to accurately detect the chord length of adjacent corners.Secondly,the edge was detected by Canny edge detector,and then the chord length was used for curvature estimation to get the curvature of each pixel on the curve,and the curvature threshold was used to determine whether it is a candidate corner.Finally,the error detection point was removed by the angle threshold,and the final corner point was obtained.The experimental results show that the proposed detector has good corner location performance compared with CPDA and other three classical detectors.For the Checkerboard diagram,the number of correct corners detected by the detector of this algorithm is 49,which is similar to that of the standard detection.For the Lab diagram,the proposed detector has the best corner location performance,and its location error is only 1.477.Compared with FAST,GCM and CPDA detectors,this detector also achieves the best performance in terms of missed detection points,error detection points and detection speed.