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1、OpenCV Canny 源码解析 1986年，John F.Canny 完善了边缘检测理论，Canny算法以此命名。 Canny 算法的步骤： 1. 使用滤波器卷积降噪 2. 使用Sobel导数计算梯度幅值和方向 3. 非极大值抑制 + 滞后阈值 在正式处理前，用高斯滤平滑波器对图像做滤波降噪的操作，避免噪声点的干扰，但在OpenCV的canny源码中，没有进行高斯滤波，需要使用者自行滤波；有些资料将非极大值抑制和滞后阈值视为两个步骤也是可行的，但是在源码中非极大值抑制 和滞后阈值是同时进行的。canny源码的位置：opencvsourcesmodulesimgprocsrccanny.cp
2、p参考了网上许多资料，有不足之处请指正，谢谢。cpp view plain copy 在CODE上查看代码片派生到我的代码片/*M/ / / IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. / / By downloading, copying, installing or using the software you agree to this license. / If you do not agree to this license, do not download, install, / copy or
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7、, / indirect, incidental, special, exemplary, or consequential damages / (including, but not limited to, procurement of substitute goods or services; / loss of use, data, or profits; or business interruption) however caused / and on any theory of liability, whether in contract, strict liability, / o
8、r tort (including negligence or otherwise) arising in any way out of / the use of this software, even if advised of the possibility of such damage. / /M*/ #include precomp.hpp /* #if defined (HAVE_IPP) & (IPP_VERSION_MAJOR = 7) #define USE_IPP_CANNY 1 #else #undef USE_IPP_CANNY #endif */ #ifdef USE_
9、IPP_CANNY namespace cv static bool ippCanny(const Mat& _src, Mat& _dst, float low, float high) int size = 0, size1 = 0; IppiSize roi = _src.cols, _src.rows ; ippiFilterSobelNegVertGetBufferSize_8u16s_C1R(roi, ippMskSize3x3, &size); ippiFilterSobelHorizGetBufferSize_8u16s_C1R(roi, ippMskSize3x3, &siz
10、e1); size = std:max(size, size1); ippiCannyGetSize(roi, &size1); size = std:max(size, size1); AutoBuffer buf(size + 64); uchar* buffer = alignPtr(uchar*)buf, 32); Mat _dx(_src.rows, _src.cols, CV_16S); if( ippiFilterSobelNegVertBorder_8u16s_C1R(_src.data, (int)_src.step, _dx.ptr(), (int)_dx.step, ro
11、i, ippMskSize3x3, ippBorderRepl, 0, buffer) 0 ) return false; Mat _dy(_src.rows, _src.cols, CV_16S); if( ippiFilterSobelHorizBorder_8u16s_C1R(_src.data, (int)_src.step, _dy.ptr(), (int)_dy.step, roi, ippMskSize3x3, ippBorderRepl, 0, buffer) 0 ) return false; if( ippiCanny_16s8u_C1R(_dx.ptr(), (int)_
12、dx.step, _dy.ptr(), (int)_dy.step, _dst.data, (int)_dst.step, roi, low, high, buffer) 0 ) return false; return true; #endif void cv:Canny( InputArray _src, OutputArray _dst, double low_thresh, double high_thresh, int aperture_size, bool L2gradient ) Mat src = _src.getMat(); /输入图像，必须为单通道灰度图 CV_Assert
13、( src.depth() = CV_8U ); / 8位无符号 _dst.create(src.size(), CV_8U); /根据src的大小构造目标矩阵dst Mat dst = _dst.getMat(); /输出图像，为单通道黑白图 / low_thresh 表示低阈值， high_thresh表示高阈值 / aperture_size 表示算子大小，默认为3 / L2gradient计算梯度幅值的标识，默认为false / 如果L2gradient为false 并且 apeture_size的值为-1（-1的二进制标识为：1111 1111） / L2gradient为false 则计算sobel导数时，用G = |Gx|+|Gy| / L2gradient为true 则计算sobel导数时，用G = Math.sqrt(Gx)2 + (Gy)2) 根号下 开平方 if (!L2gradient & (aperture_size & CV_CANNY_L2_GR
