摘要
亚像素边缘检测技术是采用图像处理软件算法来提高检测精度的有效途径,文中对矩法、拟合法和插值法等常用的亚像素边缘检测算法的原理、优点和不足进行了分析,提出了Sigmoid函数拟合的亚像素边缘定位算法.该算法采用Sigmoid函数拟合边缘模型,利用图像边缘灰度信息对模型进行非线性最小二乘拟合,求得边缘的亚像素位置.理论分析和实验结果表明,基于Sigmoid函数拟合的亚像素边缘定位算法的定位精度为0.045像素,但检测的速度比灰度矩提高了一个数量级,比空间矩、Zern ike矩和插值法提高了两个数量级.此算法能较好地满足影像测量的稳定可靠、高精度及强实时性要求.
Sub-pixel edge detection is an effective way to improve the accuracy of edge detection using image processing algorithms. In this paper, the principles, advantages and shortcomings of such existing sub-pixel edge detection algorithms as the moment method, the fitting and the interpolation methods are analyzed, and a novel sub- pixel edge location algorithm is proposed based on the Sigmoid function fitting. This algorithm employs the Sigmoid function to obtain an edge model and uses the image edge gray data to perform a nonlinear least-square fitting for the edge model. Thus, the sub-pixel location of image edge is obtained. Theoretical analyses and experimental results demonstrate that the precision of the proposed algorithm based on Sigmoid function fitting achieves 0. 045 pixel, and the detection rate increases by one order of magnitude as compared with that of the gray moment method, and by two orders of magnitude as compared with those of the spatial moment, the Zemike moment and the interpolation methods. Thus, it well satisfies the requirements for strong stability, high precision and strong real-time performance in image measurement.
出处
《华南理工大学学报(自然科学版)》
EI
CAS
CSCD
北大核心
2009年第10期39-43,共5页
Journal of South China University of Technology(Natural Science Edition)
基金
中国博士后科学基金资助项目(20070420784)
广东省博士启动基金项目(841064101000594)
广东省工业攻关项目(2008B01040004)