基于梯度二阶导数的Canny阈值自适应选取算法

摘要

Image edges contain abundant information , which is crucial for many systems , such as target detec-tion and image segmentation .Traditional Canny can only be used for gray images , which cannot effectively use col-or information in multicolor images .In addition, the method needs to set the high and low threshold , which cannot extract edges adaptively , and can cause other problems such as amplification of background edges .An adaptive edge detection algorithm was presented based on Canny in multicolor images .Firstly, this algorithm adaptively se-lects parameters of the Gaussian filter by first-order statistical properties of the histogram of images , which effective-ly removes the noise and reduces the influence of unreasonable parameter setting on edge detection .Secondly , the threshold selection method based on the two derivative of image gradient is adopted to adaptively select the appropri -ate threshold according to characteristics of images .Experimental results show that the proposed algorithm can im-prove defects of traditional Canny operator , and can extract edge information from multicolor images effectively .%图像边缘含有丰富的图像信息,对于很多视觉系统至关重要,比如目标检测与图像分割等.传统的Canny算子仅能用于灰度图像,无法有效利用彩色图像中的颜色信息;此外,该方法需要人为设定高低阈值,不能自适应提取图像边缘,进而造成背景边缘放大等问题.提出了一种基于Canny的自适应彩色图像边缘检测算法;该算法首先通过图像一阶直方图的统计特性,自适应地选取高斯滤波器的参数σ,有效去除了噪声;同时改善了σ参数设置不合理对边缘检测的影响.其次采用了基于图像梯度二阶导数的阈值选取的方法,即根据图像特性自适应选取合适的阈值.实验结果表明:算法能很好地改善传统Canny算子的缺陷,对于彩色图像的边缘信息提取能达到很好的效果.