一种改进的亚像素角点提取算法

针对Harris角点检测过程中存在定位粗糙、检测精度不高以及检测效率慢等原因,该文在Harris算法的基础上,结合Harris算子和Forstner算子提出一种改进的亚像素角点提取算法。该算法采用一种逐层检测策略,首先利用Harris算法进行角点粗略定位,首先对角点做一个初始选择,利用图像领域灰度相似度得到大部分角点的粗定位值,大大降低了算法的运算量,然后通过计算自相关矩阵的两个特征值,利用特征值和阈值比较筛选得到全部角点的粗定位值,避免了CRF（corner reference function角点响应函数）的计算,最后利用Forstner算子对粗定位后的角点进行亚像素级精确定位。实验证明,该算法不仅保证Harris算法的灵活性和Forstner算子的亚像素级精度,而且速度快,并且抗噪声性能较强。

An Improved Subpixel Corner Extraction Algorithm

In view of the rough positioning、inaccurate detecting and the slow efficiency in the Harris corner detection,According to this,an improved Harris algorithm is presented in this paper, on the basis of the combining with Harris algorithm and Forstner operator. The algorithm adopts a layered detection strategy, firstly using Harris algorithm for corner rough localization, considering the slow detecting, before calculating the CRF we made an initial choice to avoid large amount of multiplication, after geting the coarse position of angular point, we then calculate Forstner operator for accurate positioning. Experiments show that the algorithm not only guarantees the flexibility of Harris algorithm and the subpixel accuracy of Forstner operator,but also improve the speed and have strong anti-noise performance. The algorithm overcomes the problem on the detection speed and precision in the Harris algorithm.