一种尺度自适应Canny边缘检测方法

作为最优边缘检测算子,Canny算子在线性滤波及选取阈值方面具有一定的局限性.在其基础上,采用尺度可变的自适应高斯滤波器进行滤波,通过计算滤波器各滤波窗口内像素点灰度值的均值,以及该均值与当前像素点灰度值的差值,确定滤波窗口的平滑度,并将其作为高斯函数尺度的大小,在滤除噪声的同时确保了边缘信号不被平滑掉;同时采用基于简单统计法及梯度阚值法的双阈值分割方法检测经过非极大值抑制的梯度幅值图像的边缘.实验结果表明,该方法能够有效滤除噪声,且假边缘及丢失边缘的数量都比Canny边缘检测的少.

Scale Adaptive Canny Edge Detection Method

As the optimal operator of edge detection,classical Canny operator has the limits in linear filtering and threshold choosing.On the basis of it,an adaptive Gaussian filter with scale adjustable was adopted in filtering.By computing the average of all intensity values in current filter window and the difference between the average and the intensity value of the current pixel,the smooth degree of current filter window was obtained.And then,by regarding the smooth degree as the scale size of Gaussian function,the noises of images could be filtered while the edges couldn’t be smoothed.At the same time,an adaptive double-threshold selection method was used based on the grads threshold method and simple statistic method to detect edges of Non-Maxima Suppressed grads image.Experiments prove that the method can filter noise effectively;also the distilled fake edges and lost edges are fewer than those of classical Canny operator.