例5-1......例5-4 图像处理

//// 例 5-1 cvPyrSegmentation()#include "stdafx.h"#include <cv.h>#include <highgui.h>void f(IplImage* src,IplImage* dst){CvMemStorage* storage=cvCreateMemStorage(0);CvSeq* comp=NULL;cvPyrSegmentation(src,dst,storage,&comp,4,200,50);int n_comp=comp->total;printf("comp->total:%d/n",comp->total);for (int i=0;i<n_comp;i++){CvConnectedComp* cc=(CvConnectedComp*) cvGetSeqElem(comp,i);//...........printf("/n/ncc->area:%f/n",cc->area);//从运行结果里看，cc->area是越来越缩小的//printf("cc->contour->total: %f/n",cc->contour->total);//不能输出，程序出现错误，未知原因printf(" cc->rect.height: %f/n",cc->rect.height);printf(" cc->rect.width: %f/n", cc->rect.width);printf(" cc->rect.x: %f/n",cc->rect.x);printf(" cc->rect.y: %f/n",cc->rect.y);printf("cc->value.val: %f/n",cc->value.val);}cvReleaseMemStorage(&storage);}int main(int argc,char** argv){IplImage* src=cvLoadImage(argv[1],1);IplImage* dst=cvLoadImage(argv[2],1);f(src,dst);cvReleaseImage(&src);cvReleaseImage(&dst);return 0;}//例 5-2 cvThreshold()函数的用法#include "stdafx.h"#include <cv.h>#include <highgui.h>void sum_rgb(IplImage* src,IplImage* dst){//逐步跟踪图像//cvNamedWindow("跟踪器",1);//Allocate individual image planes分配独立的图像平面IplImage* r=cvCreateImage(cvGetSize(src),IPL_DEPTH_8U,1);IplImage* g=cvCreateImage(cvGetSize(src),IPL_DEPTH_8U,1);IplImage* b=cvCreateImage(cvGetSize(src),IPL_DEPTH_8U,1);// cvShowImage("r",r);//生成的是三个灰色的图像，截图保存为1// cvShowImage("g",g);// cvShowImage("b",b);//split image onto the color planes截断cvSplit(src,r,g,b,NULL);// cvShowImage("r",r);//很黑// cvShowImage("g",g);//亮度比r好点// cvShowImage("b",b);//很黑的部分变白了，好像是截断了//temporary storageIplImage* s=cvCreateImage(cvGetSize(src),IPL_DEPTH_8U,1);cvShowImage("s",s);//和之前创建的r,g,b一样，灰色的//add equally weighted rgb valuescvAddWeighted(r,1/3,g,1/3,0,s);// cvShowImage("r",r);// cvShowImage("g",g);// cvShowImage("b",b);//和截断之前的效果一样，没看出来变化//cvShowImage("s",s);//s是黑压压一片cvAddWeighted(s,2/3,b,1/3,0,s);// cvShowImage("r",r);// cvShowImage("g",g);// cvShowImage("b",b);//truncate values above 100 截断cvThreshold(s,dst,100,100,CV_THRESH_TRUNC);// cvShowImage("r",r);// cvShowImage("g",g);// cvShowImage("b",b);cvReleaseImage(&r);cvReleaseImage(&g);cvReleaseImage(&b);cvReleaseImage(&s);//cvDestroyWindow("跟踪器");}int main(int argc,char** argv){cvNamedWindow(argv[1],1);IplImage* src=cvLoadImage(argv[1]);IplImage* dst=cvCreateImage(cvGetSize(src),src->depth,1);sum_rgb(src,dst);cvShowImage(argv[1],dst);//灰乎乎一片，还不如在中间跟踪查看呢while (1){//if ((cvWaitKey(10)&0x7f)==27)//这样做，按了esc只是关闭了能看见的画面，不能返回到dos下，应该是还有东西在运行if(cvWaitKey(10)==27){break;}}cvDestroyWindow(argv[1]);cvReleaseImage(&src);cvReleaseImage(&dst);}//例5-3 另一种组合不同通道，并域值化图像的方法#include "stdafx.h"#include <cv.h>#include <highgui.h>void sum_rgb(IplImage* src,IplImage* dst){IplImage* s=cvCreateImage(cvGetSize(src),IPL_DEPTH_32F,1);IplImage* r=cvCreateImage(cvGetSize(src),IPL_DEPTH_8U,1);IplImage* g=cvCreateImage(cvGetSize(src),IPL_DEPTH_8U,1);IplImage* b=cvCreateImage(cvGetSize(src),IPL_DEPTH_8U,1);cvZero(s);//cvShowImage("cvZero(s)",s);//黑压压一片cvAcc(b,s);// cvShowImage("cvAcc(b,s)的s",s);//白的// cvShowImage("cvAcc(b,s)的b",b);//灰的cvAcc(g,s);// cvShowImage("cvAcc(g,s)的s",s);//白的// cvShowImage("cvAcc(g,s)的g",g);//灰的cvAcc(r,s);// cvShowImage("cvAcc(r,s)的s",s);//白的// cvShowImage("cvAcc(r,s)的r",r);//灰的cvThreshold(s,s,100,100,CV_THRESH_TRUNC);//cvShowImage("cvThreshold(s,s,100,100,CV_THRESH_TRUNC)之后的s",s);//白的cvConvertScale(s,dst,1,0);// cvShowImage("cvConvertScale(s,dst,1,0)之后的s",s);//白的// cvShowImage("cvConvertScale(s,dst,1,0)之后的dst",dst);//灰的cvReleaseImage(&s);cvReleaseImage(&r);cvReleaseImage(&g);cvReleaseImage(&b);}int main(int argc,char** argv){cvNamedWindow("lala",1);IplImage* src=cvLoadImage(argv[1],1);IplImage* dst=cvCreateImage(cvGetSize(src),src->depth,1);sum_rgb(src,dst);cvShowImage("src原图像",src);cvShowImage("dst目标图像",dst);//没有观察到结果while (1){if(cvWaitKey(10)==27){break;}}cvReleaseImage(&src);cvReleaseImage(&dst);cvDestroyWindow("lala");return 0;}//例5-4 单一阈值和自适应阈值#include "stdafx.h"#include <highgui.h>#include <cv.h>IplImage* Igray=0,*It=0,*Iat;int main(int argc,char** argv){if (argc!=7){return -1;}double threshold=(double)atof(argv[1]);int threshold_type=atoi(argv[2])?CV_THRESH_BINARY:CV_THRESH_BINARY_INV;int adaptive_method=atoi(argv[3])?CV_ADAPTIVE_THRESH_MEAN_C:CV_ADAPTIVE_THRESH_GAUSSIAN_C;int block_size=atoi(argv[4]);double offset=(double)atof(argv[5]);if ((Igray=cvLoadImage(argv[6],CV_LOAD_IMAGE_GRAYSCALE))==0){return -1;}It=cvCreateImage(cvSize(Igray->width,Igray->height),IPL_DEPTH_8U,1);Iat=cvCreateImage(cvSize(Igray->width,Igray->height),IPL_DEPTH_8U,1);cvThreshold(Igray,It,threshold,255,threshold_type);cvAdaptiveThreshold(Igray,Iat,255,adaptive_method,threshold_type,block_size,offset);cvNamedWindow("raw",1);cvNamedWindow("Threshold",1);cvNamedWindow("Adaptive Threshold",1);cvShowImage("Raw",Igray);cvShowImage("Threshold",It);cvShowImage("Adaptive Threshold ",Iat);cvWaitKey(0);cvReleaseImage(&Iat);cvReleaseImage(&Igray);cvReleaseImage(&It);cvDestroyWindow("Raw");cvDestroyWindow("Threshold");cvDestroyWindow("Adaptive Threshold");return 0;}