今日依旧偷懒，只看了几页纸照着书做了两个例程。思路依旧简单：
（一）显示结果图像代码写在主函数中：（如2.）
（a）在主函数中创建IplImage格式变量，利用cvLoadImage加载图像
（b）在主函数中调用所写的图像处理函数
功能函数注意选择需要传递的参数。
功能函数中一般先确保该函数需要满足的条件（某些操作或者待用的OpenCV函数需要图像满足一定条件，如Canny
算子需要灰度图才行），然后定义IplImage格式的输出变量，调用OpenCV函数执行功能（一般为xxx（in，
out））
（c）在主函数中cvNamedWindow创建窗口，cvShowImage显示图像，cvWaitKey( 0 )按键等待，cvReleaseImage
释放资源，cvDestroyWindow销毁窗口
（二）显示结果图像代码写在功能函数中：（如1.）
（a）在主函数中创建IplImage格式变量，利用cvLoadImage加载图像
（b）在主函数中调用所写的图像处理函数
（c）在功能函数中cvNamedWindow创建窗口，cvShowImage显示图像，cvWaitKey( 0 )按键等待，cvReleaseImage
释放资源，cvDestroyWindow销毁窗口
两种方法没有本质区别，博主倾向方法（一）
1.图像高斯平滑
#include "highgui.h"
#include "cv.h"void example2_4( IplImage* image )
{ // Create some windows to show the input// and output images in.//cvNamedWindow( "Example4-in" ,0);cvNamedWindow( "Example4-out",0 );// Create a window to show our input image//cvShowImage( "Example4-in", image );// Create an image to hold the smoothed output//IplImage* out = cvCreateImage(cvGetSize(image),IPL_DEPTH_8U,);// Do the smoothing//cvSmooth( image, out, CV_GAUSSIAN, 3, 3 );// Show the smoothed image in the output window//cvShowImage( "Example4-out", out );// Be tidy//cvReleaseImage( &out );// Wait for the user to hit a key, then clean up the windows//cvWaitKey( 0 );cvDestroyWindow( "Example4-in" );cvDestroyWindow( "Example4-out" );}void main(){ IplImage* img = cvLoadImage( "1.jpg", CV_LOAD_IMAGE_COLOR);example2_4( img );}2.Canny平滑与图像缩小
#include "highgui.h"
#include "cv.h"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 );}; IplImage* doCanny(IplImage* in,double lowThresh,double highThresh,int aperture) { if(in->nChannels != 1) return(0); //Canny only handles gray scale imagesIplImage* out = cvCreateImage(cvGetSize( in ) ,IPL_DEPTH_8U,1);
cvCanny( in, out, lowThresh, highThresh, aperture );
return( out );};void main()
{ cvNamedWindow( "in" ,0);cvNamedWindow( "img1" ,0);cvNamedWindow( "img2" ,0);cvNamedWindow( "img3" ,0);IplImage* in = cvLoadImage( "1.jpg", CV_LOAD_IMAGE_COLOR);IplImage* img1 = doPyrDown( in, IPL_GAUSSIAN_5x5 );IplImage* img2 = doPyrDown( img1, IPL_GAUSSIAN_5x5 );IplImage* img3 = doCanny( img2, 10, 100, 3 );cvShowImage( "in", in );cvShowImage( "img1", img1 );cvShowImage( "img2", img2 );cvShowImage( "img3", img3 );cvWaitKey( 0 );cvReleaseImage( &img1 );cvReleaseImage( &img2 );cvReleaseImage( &img3 );cvDestroyWindow( "in" );cvDestroyWindow( "img1" );cvDestroyWindow( "img2" );cvDestroyWindow( "img3" );}