opencv从入门到精通（2）--简单图像变换

1.图像滤波

这里有到两个函数cvCreateImage和 cvSmooth( image, out, CV_GAUSSIAN, 5,5,0,0 )。

cvCreateImage(cvGetSize(image),IPL_DEPTH_8U,3)用于创建

指定大小的图像，第一个参数是尺寸，第二个参数是数据类型，

第三个参数是通道数。cvSmooth( image, out, CV_GAUSSIAN, 5,5,0,0 )

用于图像滤波，第一个参数是输入图像；第二个参数是输出图像；

第三个参数是平滑方法；5,5表示5*5邻域；

第六个参数是高斯参数的 Gaussian sigma (标准差)。

#include <stdio.h>#include <fstream>#include<iostream> #include <opencv2/core/core.hpp> #include <opencv2/highgui/highgui.hpp> #include "cv.h" using namespace cv;using namespace std;int main( ){IplImage* image = cvLoadImage( "a1.ppm" );//输入图像cvNamedWindow( "Example4-in", CV_WINDOW_AUTOSIZE );//创建显示输入图像的窗口cvNamedWindow( "Example4-out", CV_WINDOW_AUTOSIZE );//创建显示输出图像的窗口cvShowImage( "Example4-in", image );//显示输入图像IplImage* out = cvCreateImage(cvGetSize(image),IPL_DEPTH_8U,3);//创建和image大小相同的图像// 平滑cvSmooth( image, out, CV_GAUSSIAN, 5,5,0,0 );cvSmooth( out, out, CV_GAUSSIAN, 5, 5,0,0);cvShowImage( "Example4-out", out );cvReleaseImage( &out );cvWaitKey( 0 ); cvDestroyWindow("Example4-in" );cvDestroyWindow("Example4-out" );cvReleaseImage( &image );}

封装函数

1.图像缩放

cvPyrDown( in, out )使用Gaussian金字塔分解对输入图像向下采样。第一个参数是输入图像，第二个参数是输出图像，长宽为输入图像的一半。

#include <stdio.h>#include <fstream>#include<iostream> #include <opencv2/core/core.hpp> #include <opencv2/highgui/highgui.hpp> #include "cv.h" using namespace cv;using namespace std;IplImage* doPyrDown(IplImage* in,int filter = IPL_GAUSSIAN_5x5){assert( in->width%2 == 0 && in->height%2 == 0 );//长宽不为偶数退出IplImage* out= cvCreateImage(cvSize( in->width/2, in->height/2 ),in->depth,in->nChannels);cvPyrDown( in, out );return( out );};int main( ){IplImage* img = cvLoadImage( "ch12_birdseye.jpg" );IplImage* img2 = cvCreateImage( cvSize( img->width/2,img->height/2 ), img->depth, img->nChannels);cvNamedWindow("Example1", CV_WINDOW_AUTOSIZE );cvNamedWindow("Example2", CV_WINDOW_AUTOSIZE );cvShowImage("Example1", img );img2 = doPyrDown( img );cvShowImage("Example2", img2 );cvWaitKey(0);cvReleaseImage( &img );cvReleaseImage( &img2 );cvDestroyWindow("Example1");cvDestroyWindow("Example2");}

边缘检测

cvCvtColor(img_rgb, img_gry ,CV_BGR2GRAY)函数可以实现颜色空间的转换，第一个参数是输入图像，第二个参数是输出图像，第三个参数是转换形式——CV_BGR2GRAY表示转换为灰度图，输入需要是单通道图片；CV_BGR2HSV将图片从RGB空间转换为HSV空间，需要将rgb值归一化到0-1之间。

函数 void cvCanny( const CvArr* image,CvArr* edges,double threshold1,double threshold2, int aperture_size=3 )采用 Canny 算法发现输入图像的边缘而且在输出图像中标识这些边缘。输入是灰度图，threshold1和threshold2 当中的小阈值用来控制边缘连接，大的阈值用来控制强边缘的初始分割， aperture_size是算子内核大小。

#include <stdio.h>#include <fstream>#include<iostream> #include <opencv2/core/core.hpp> #include <opencv2/highgui/highgui.hpp> #include "cv.h" using namespace cv;using namespace std;IplImage* doCanny(IplImage* in,double lowThresh,double highThresh,double aperture){if (in->nChannels != 1)return(0); IplImage* out = cvCreateImage( cvGetSize( in ),in->depth,1);cvCanny( in, out, lowThresh, highThresh, aperture );return( out );};int main( ){IplImage* img_rgb = cvLoadImage( "left01.jpg" );IplImage* img_gry = cvCreateImage( cvSize( img_rgb->width,img_rgb->height ), img_rgb->depth, 1);cvCvtColor(img_rgb, img_gry ,CV_BGR2GRAY);cvNamedWindow("Example Gray", CV_WINDOW_AUTOSIZE );cvNamedWindow("Example Canny", CV_WINDOW_AUTOSIZE );cvShowImage("Example Gray", img_gry );IplImage* img_cny = doCanny( img_gry, 10, 100, 3 );cvShowImage("Example Canny", img_cny );cvWaitKey(0);cvReleaseImage( &img_rgb);cvReleaseImage( &img_gry);cvReleaseImage( &img_cny);cvDestroyWindow("Example Gray");cvDestroyWindow("Example Canny");}

3.嵌套使用

有了之前封装的函数，就可以很方便的对图像做一系列的变换，比如缩小两次在进行边缘检测，代码为：

#include <stdio.h>#include <fstream>#include<iostream> #include <opencv2/core/core.hpp> #include <opencv2/highgui/highgui.hpp> #include "cv.h" using namespace cv;using namespace std;IplImage* doCanny(IplImage* in,double lowThresh,double highThresh,double aperture){IplImage* out = cvCreateImage( cvGetSize( in ),in->depth, //IPL_DEPTH_8U, 1);cvCanny( in, out, lowThresh, highThresh, aperture );return( out );};IplImage* doPyrDown(IplImage* in,int filter = IPL_GAUSSIAN_5x5){// Best to make sure input image is divisible by two.//assert( in->width%2 == 0 && in->height%2 == 0 );IplImage* out = cvCreateImage( cvSize( in->width/2, in->height/2 ),in->depth,in->nChannels);cvPyrDown( in, out );return( out );};int main( ){cvNamedWindow("Example Gray", CV_WINDOW_AUTOSIZE );cvNamedWindow("Example Pyr", CV_WINDOW_AUTOSIZE );cvNamedWindow("Example Canny", CV_WINDOW_AUTOSIZE );IplImage* img_rgb = cvLoadImage("ch12_birdseye.jpg");IplImage* out;out = cvCreateImage( cvSize( img_rgb->width,img_rgb->height ), img_rgb->depth, 1);cvCvtColor(img_rgb, out ,CV_BGR2GRAY);cvShowImage("Example Gray", out );out = doPyrDown( out );out = doPyrDown( out );cvShowImage("Example Pyr", out );out = doCanny( out, 10, 100, 3 );cvShowImage("Example Canny", out );cvWaitKey(0);cvReleaseImage( &out);cvDestroyWindow("Example Gray");cvDestroyWindow("Example Pyr");cvDestroyWindow("Example Canny");}

对视频的每一幅图像进行变换

#include <stdio.h>#include <fstream>#include<iostream> #include <opencv2/core/core.hpp> #include <opencv2/highgui/highgui.hpp> #include "cv.h" using namespace cv;using namespace std;int main( ) {cvNamedWindow( "Example2_10", CV_WINDOW_AUTOSIZE );cvNamedWindow( "Log_Polar", CV_WINDOW_AUTOSIZE );CvCapture* capture = cvCreateFileCapture("a2.mp4" );if (!capture){return -1;}IplImage* bgr_frame;double fps = cvGetCaptureProperty (capture, CV_CAP_PROP_FPS);//获取帧率printf("fps=%d\n",(int)fps);CvSize size = cvSize((int)cvGetCaptureProperty( capture, CV_CAP_PROP_FRAME_WIDTH),(int)cvGetCaptureProperty( capture, CV_CAP_PROP_FRAME_HEIGHT));printf("frame (w, h) = (%d, %d)\n",size.width,size.height);CvVideoWriter* writer = cvCreateVideoWriter( "D:\Documents\Visual Studio \Projects\load and display an image\load and display an image\a3.mp4",CV_FOURCC('D','X','5','0'), fps,size);IplImage* logpolar_frame = cvCreateImage(size,IPL_DEPTH_8U,3);IplImage* gray_frame = cvCreateImage(size,IPL_DEPTH_8U,1);while( (bgr_frame=cvQueryFrame(capture)) != NULL ) {cvShowImage( "Example2_10", bgr_frame );cvConvertImage( //We never make use of this gray imagebgr_frame,gray_frame,CV_RGB2GRAY);cvLogPolar( bgr_frame, logpolar_frame, //This is just a fun conversion the mimic's the human visual systemcvPoint2D32f(bgr_frame->width/2,bgr_frame->height/2), 40, CV_INTER_LINEAR+CV_WARP_FILL_OUTLIERS );cvShowImage( "Log_Polar", logpolar_frame );//Sigh, on linux, depending on your ffmpeg, this often won't work ...cvWriteToAVI( writer, logpolar_frame );char c = cvWaitKey(10);if( c == 27 ) break;}cvReleaseVideoWriter( &writer );cvReleaseImage( &gray_frame );cvReleaseImage( &logpolar_frame );cvReleaseCapture( &capture );return 0;}