利用多尺度弦角尖锐度累积的自适应角点检测算子

为提高角点检测算法的定位精度和对噪声的鲁棒性,提出了基于多尺度弦角尖锐度累积的自适应角点检测算子。首先,利用Canny算法快速提取图像边缘轮廓;然后,划分轮廓支撑域并将其作为尺度,分别计算3个尺度下的弦角尖锐度均值,并将其累积作为角点响应函数;最后,根据每条轮廓各自的自适应阈值标记角点。实验结果表明,与现有的角点检测算法相比,该算法提高了噪声图像和模糊图像上角点的定位精度和抗噪声能力,并具有自适应性。

An Adaptive Threshold Corner Detector Based on Multi-scale Chord-Angle Sharpness Accumulation

We propose a new adaptive corner detector based on multi-scale chord-angle sharpness accu-mulation, which can reduce location error and detects fine accuracy on noisy images. Firstly, we use the canny detector to detect edges at low computational cost. Secondly, we devise support regions of the contour into three sections as scales and computes the chord-angel sharpness respectively, then accumulate the three scale sharpness as corner response function. Finally, we use an dynamic adaptive corner threshold to label corners. The results on fine and low quality images show that the proposed algorithm performs better than the other three algorithms in terms of both detection accuracy and location error.