图像分割简单处理

//学习OPENCV第5章,简单图像处理#include<stdio.h>#include<cv.h>#include<highgui.h>#include<stdio.h>#include <opencv2/legacy/legacy.hpp>void f(IplImage* src, IplImage* dst,int layer);void sum_rgb(IplImage* src,IplImage* dst);void sum_rgb1(IplImage* src,IplImage* dst); int main(int argc, char** argv){//-------------------------------------------------------------------//图像金字塔分割IplImage* src = cvLoadImage("D:\\AI_Proj\\OPENCV\\cameraman.tif");if(!src) { printf("Couldn't seem to Open image, sorry\n"); return -1;}//分别按照金字塔2/4/6层分割IplImage* dst2l = cvCreateImage(cvGetSize(src),src->depth,src->nChannels);IplImage* dst4 = cvCreateImage(cvGetSize(src),src->depth,src->nChannels);IplImage* dst6 = cvCreateImage(cvGetSize(src),src->depth,src->nChannels);f(src,dst2l,2);f(src,dst4,4);f(src,dst6,6);cvNamedWindow("PyrSegmentation2",1);cvNamedWindow("PyrSegmentation4",1);cvNamedWindow("PyrSegmentation6",1);cvShowImage("PyrSegmentation2",dst2l);cvShowImage("PyrSegmentation4",dst4);cvShowImage("PyrSegmentation6",dst6);while(1) { if(cvWaitKey(100) == 27) break; }cvDestroyWindow("PyrSegmentation2");cvDestroyWindow("PyrSegmentation4");cvDestroyWindow("PyrSegmentation6");cvReleaseImage(&src);cvReleaseImage(&dst2l);cvReleaseImage(&dst4);cvReleaseImage(&dst6);cvWaitKey();//-------------------------------------------------------------------//rgb分离:加权加法得到目的图像IplImage* src1 = cvLoadImage("D:\\AI_Proj\\OPENCV\\dog.jpg");IplImage* dst1 = cvCreateImage(cvGetSize(src1),src1->depth,1);sum_rgb(src1,dst1);cvNamedWindow("split_rgb",1);cvShowImage("split_rgb",dst1);while(1) { if((cvWaitKey(10)&0x7f) == 27) break; }cvDestroyWindow("split_rgb");cvReleaseImage(&src1);cvReleaseImage(&dst1);cvWaitKey();//-------------------------------------------------------------------//rgb分离:通过累加cvAcc得到目的图像IplImage* src2 = cvLoadImage("D:\\AI_Proj\\OPENCV\\dog.jpg");IplImage* dst2 = cvCreateImage(cvGetSize(src2),src2->depth,1);sum_rgb1(src2,dst2);cvNamedWindow("cvAcc_rgb",1);cvShowImage("cvAcc_rgb",dst2);while(1) { if((cvWaitKey(10)&0x7f) == 27) break; }cvDestroyWindow("cvAcc_rgb");cvReleaseImage(&src2);cvReleaseImage(&dst2);cvWaitKey();//-------------------------------------------------------------------//自适应分割:增加可配性IplImage* Igray;IplImage* It;IplImage* Iat;if(!(Igray = cvLoadImage("D:\\AI_Proj\\OPENCV\\dog.jpg",CV_LOAD_IMAGE_GRAYSCALE)))return -1;    double threshold = 100;//(double)atof(argv[1]);    int threshold_type = CV_THRESH_BINARY;//atoi(argv[2]) ? CV_THRESH_BINARY : CV_THRESH_BINARY_INV;    int adaptive_method = CV_ADAPTIVE_THRESH_MEAN_C;//atoi(argv[3]) ? CV_ADAPTIVE_THRESH_MEAN_C : CV_ADAPTIVE_THRESH_GAUSSIAN_C;    int block_size = 3;//atoi(argv[4]);    double offset = 0;//(double)atof(argv[5]);    //Create the grayscale output images    It = cvCreateImage(cvSize(Igray->width,Igray->height),IPL_DEPTH_8U,1);    Iat = cvCreateImage(cvSize(Igray->width,Igray->height),IPL_DEPTH_8U,1);    //Threshold    cvThreshold(Igray,It,threshold,255,threshold_type);//根据block_size内像素，二值化//P159:只能处理8位图像，或浮点图像，源图像与目的图像不能一致。    cvAdaptiveThreshold(Igray,Iat,255,adaptive_method,threshold_type,block_size,offset);    //PUT UP 2 WINDOWS    cvNamedWindow("Raw",1);    cvNamedWindow("Threshold",1);    cvNamedWindow("Adaptive_Threshold",1);    //Show the results    cvShowImage("Raw",Igray);    cvShowImage("Threshold",It);    cvShowImage("Adaptive_Threshold",Iat);    cvWaitKey(0);    //Clean up    cvReleaseImage(&Igray);    cvReleaseImage(&It);    cvReleaseImage(&Iat);cvDestroyWindow("Raw");cvDestroyWindow("Threshold");cvDestroyWindow("Adaptive_Threshold");return(0);}//图像金字塔实现分割void f(IplImage* src,IplImage* dst,int layer) {//为结构体CvMemStorage分配空间,返回指向该空间的指针CvMemStorage* storage = cvCreateMemStorage(0);//动态结构序列CvSeq是所有OpenCv动态数据结构的基础;有两种类型的序列:稠密序列,稀疏序列CvSeq* comp = NULL;//用金字塔实现图像分割P153//http://blog.csdn.net/cartoonface/article/details/5998543//参数：源/目的图像;存储连通部件的序列结果;分割部件的输出序列指针;//最大层数layer;阈值200,50cvPyrSegmentation(src,dst,storage,&comp,layer,200,50);int n_comp = comp->total;//对序列进行索引,或进行其他操作for(int i=0;i<n_comp;i++) {//cvGetSeqElem返回索引指定元素的指针//comp是要检测的序列,而i是元素在序列中的索引CvConnectedComp* cc = (CvConnectedComp*) cvGetSeqElem(comp,i);// do_something_with( cc );}cvReleaseMemStorage(&storage);}void sum_rgb(IplImage* src,IplImage* dst) {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);//Temporary storage.IplImage* s = cvCreateImage(cvGetSize(src),IPL_DEPTH_8U,1);//Split image onto the color planes.图像通道分离cvSplit(src,r,g,b,NULL);//Add equally weighted rgb values.//s=r*1/3+g*1/3//s=s*2/3+b*1/3//通常不对8位数组进行加法运算,可能溢出。//通过加权加法对3通道进行运算,高于100进行截断cvAddWeighted(r,1./3.,g,1./3.,0.0,s);cvAddWeighted(s,2./3.,b,1./3.,0.0,s);//对value大于100的像素进行截断为255，不足100的保留原值cvThreshold(s,dst,100,255,CV_THRESH_TRUNC);cvNamedWindow("split_r",CV_WINDOW_AUTOSIZE);cvNamedWindow("split_g",CV_WINDOW_AUTOSIZE);cvNamedWindow("split_b",CV_WINDOW_AUTOSIZE);cvNamedWindow("s",CV_WINDOW_AUTOSIZE);cvShowImage("split_r",r);cvShowImage("split_g",g);cvShowImage("split_b",b);cvShowImage("s",s);cvWaitKey();cvReleaseImage(&r);cvReleaseImage(&g);   cvReleaseImage(&b);   cvReleaseImage(&s);cvDestroyWindow("split_r");cvDestroyWindow("split_g");cvDestroyWindow("split_b");cvDestroyWindow("s");}void sum_rgb1(IplImage* src,IplImage* dst) {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);IplImage* s = cvCreateImage(cvGetSize(src),IPL_DEPTH_32F,1);cvSplit(src,r,g,b,NULL);//图像累加cvZero(s);cvAcc(b,s);cvAcc(g,s);cvAcc(r,s);cvThreshold(s,s,100,255,CV_THRESH_TRUNC );//使用线性变换转换数组//源/目的图像;缩放因子;添加的值cvConvertScale(s,dst,1,0); cvReleaseImage(&r);cvReleaseImage(&g);   cvReleaseImage(&b);   cvReleaseImage(&s);}

示例效果：

金字塔层数越多分割越模糊