基于非线性扩散滤波的边缘检测和图像测量

提出了一种基于自适应非线性扩散方程滤波的边缘检测方法, 以提高图像测量的精度。首先对原始图像实施一种非线性扩散处理,即沿着等照度线(边缘)的梯度方向实施反向扩散以锐化边缘, 而相反地沿切线方向实施正向扩散以去除噪声和锯齿伪像; 然后应用经典的微分算子来检测边缘。实验结果表明,相对于经典的边缘检测算子, 本算法得到了尖锐而平滑的单像素宽的图像边缘,较好地定位了边缘, 相对误差为0.03。当图像边缘模糊和存在附加噪声时, 测量结果将会受到很大影响。本方法较好地定位了边缘像素, 对于微小尺寸测量显示出它的优越性.

Edge detection for image measurement based on nonlinear diffusion filtering

Image measurement technique is a new developing method in the non-contact measurement and instrument fields.In this paper, an adaptive nonlinear flow equation process is presented to improve the measurement precision.First,an inverse diffusion is performed to sharpen edges along the normal directions to the isophote lines(edges),while a normal diffusion is done to remove noise and artifacts("jaggies") along the tangent directions.Then,classical differential operator is employed to detect image edges.With a better edge location,experimental results show that sharper and smoother edges with one pixel are abtained in a relative error of 0.03.The method also shows its advantages in the minuteness measurement for a better edge location.In the case of blurry edges and additional noise in the image,the measurement results would be worse.