Harris角点检测的优化算法

针对Harris角点检测算法中提取出较多的伪角点和计算量大的问题，提出了一种基于Harris角点检测的改进算法. 为抑制Harris角点检测中的伪角点数目并且提高算法的效率，首先加入预筛选得到候选角点，在计算水平和垂直方向梯度时，对于梯度较小的像素点进行预处理，在进行非极大值抑制时采用自适应阈值，提高算法自适应性，最后利用USAN对角点进行进一步选择. 实验结果表明，改进的Harris角点检测算法不仅提高了检测精度和效率，而且对噪声具有一定的鲁棒性.

Improved Algorithm Based on Harris Corner Detection

According to the problems of extracting more false corners and large computation problems in harris corner detection, this paper proposes an improved algorithm based on harris corner detection. In order to reduce the number of false corners and improve the algorithm efficiency, a pre-selection strategy is embedded to pick out potential corners before the normal routine. When calculate the horizontal and vertical gradients, the pixels with smaller horizontal and vertical gradients are pre-processed. In order to improve the auto-adaptive of algorithm, an auto-adaptive threshold is adopted, finally using USAN to make further selection. The result shows that the improved algorithm not only can improve the precision and efficiency of corner detection, but also is robust to noise to some extent.