基于Zernike矩亚像素边缘检测的快速算法

摘要

为了克服传统的Zernike法在边缘检测过程中,由于人工手动选取阈值而带来的低效率、高误判等不足,将原算法与Otsu法相结合,提出了一种边缘检测的快速算法.利用传统的Zernike法计算出图像的阶跃灰度矩阵,再将该矩阵作为计算对象,用Otsu法直接得到最优的阶跃灰度阈值进行边缘判别,并考虑了由于边缘模型带来的误差,在保证检测效果的同时缩短了检测时间.实验结果表明,改进的算法能够更有效地完成边缘检测,补偿后的亚像素定位更准确.%The traditional Zemilce orthogonal moment operators can detect the edge with subpixel-level, but the algorithm still requires manual tuning on selecting threshold, not only inefficient, but also leads to the wrong detection of the edge. In order to overcome this weakness, this article combined original algorithm with Otsu adaptive threshold algorithm and proposed a new fast algorithm for edge detection. Firstly,it calculated the step grayscale matrix of the image by the traditional Zernike method, then treated the matrix as a calculate object, directly obtained the optimal step gray threshold by Otsu method and determined the edge. This algorithm also calculated the error caused by edge model. The detection time is significantly shortened while ensuring the detection accuracy. Experimental results show that the improved algorithm can detect the image edge more effectively and the subpixel-level location is more accurate after compensating.