opencv根据面积提取轮廓

Opencv 提取轮廓(去掉面积小于某个值的轮廓) #include #include “cv.h“ #include “cxcore.h“ #include “highgui.h“ #include using namespace std; #pragma comment(lib,“cv.lib“) #pragma comment(lib,“cxcore.lib“) #pragma comment(lib,“highgui.lib“) struct Position int x,y; ; double per256;/ 保存灰度概率 IplImage *FindCountours(IplImage* src,IplImage *pContourImg); int ImageStretchByHistogram(IplImage *src,IplImage *dst); IplImage* Hist_Equalization(IplImage *srcimg); void proBorder(IplImage *src); / 边界的处理 void GetBackImage(IplImage* src,IplImage* src_back); void Threshold(IplImage *src); int GetThreshold(double *const prob); void Getprobability(IplImage *src); double Eccentricity(IplImage *src); void main() /IplImage * src = cvLoadImage(“C:image19A634.jpg“,-1);/灰度图的方式载入 IplImage * src = cvLoadImage(“C:image19A857.jpg“,-1); IplImage * dst = cvCreateImage(cvGetSize(src),IPL_DEPTH_8U,3); IplImage *src_back = cvCreateImage(cvGetSize(src),IPL_DEPTH_8U,src-nChannels); GetBackImage(src,src_back); dst = FindCountours(src_back,dst); cvNamedWindow(“test“,CV_WINDOW_AUTOSIZE); cvShowImage(“test“,dst); cvWaitKey(0); cvReleaseImage( cvReleaseImage( void GetBackImage(IplImage* src,IplImage* src_back) /cvCvtColor(src,src,CV_RGB2GRAY);/灰度化 IplImage *tmp = cvCreateImage(cvGetSize(src),IPL_DEPTH_8U,3); / 创建结构元素 IplConvKernel *element = cvCreateStructuringElementEx( 2, 2, 0, 0, CV_SHAPE_ELLIPSE,0); /用该结构对源图象进行数学形态学的开操作后，估计背景亮度 cvErode(src,tmp,element,9); /使用任意结构元素腐蚀图像 cvDilate(tmp,src_back, element,9); /使用任意结构元素膨胀图像 IplImage *FindCountours(IplImage* src,IplImage *pContourImg) CvMemStorage *storage = cvCreateMemStorage(0); /提取轮廓需要的储存容量 0为默认 64KB CvSeq * pcontour = 0; /提取轮廓的序列指针 IplImage *temp = cvCreateImage(cvGetSize(src),src-depth,1); /cvSmooth(src,temp,CV_GAUSSIAN,3,1,0); cvSmooth(src,src,CV_GAUSSIAN,3,1,0);/平滑处理 cvCvtColor(src,temp,CV_RGB2GRAY);/灰度化 Getprobability(temp); printf(“最好的阈值:%dn“,GetThreshold(per); /Threshold(temp); proBorder(temp); cvThreshold(temp,temp,GetThreshold(per),255,CV_THRESH_BINARY_INV); int contoursNum = 0; / 轮廓数量 /int mode = CV_RETR_LIST; int mode = CV_RETR_EXTERNAL;/ 提取最外层轮廓 contoursNum = cvFindContours(temp,storage, / contoursNum = cvFindContours(temp,storage, /二值图, 得到轮廓存储,轮廓指针序列,header_size,提取模式,逼近方法 CvScalar externalColor;/ 保存颜色值 CvScalar holeColor; /-画轮廓-/ for (; pcontour != 0; pcontour=pcontour - h_next) /holeColor=CV_RGB(rand() /externalColor=CV_RGB(rand() CvRect r = (CvContour *)pcontour)-rect; if(r.height * r.width width; int height = src-height; int i,j; for(i = 0; i = 0; i-) for(j = 0; j = 0; i-) for(j = 0 ; j s_dis) printf(“偏心率:%fn“,l_dis*1.0/s_dis); else tmp_dis = l_dis; l_dis = s_dis; s_dis = tmp_dis; printf(“偏心率:%fn“,l_dis*1.0/s_dis); return 0; void Getprobability(IplImage *src) memset(per,0,sizeof(per); int width = src-width; int height = src-height; for(int i = 0; i height; int width = src-width; int N = 100; for(i = 0; i imageDataindex = (char)255; int NN = 150; int sw = width * (height - NN);/ 左下角 三角形 int t = 1; for(i = sw; i imageDataindex = (char)255; int se = (height - NN - 1) * width; / 右下角 t = 0; for(i = se; i imageDataindex = (char)255; int ne = width - NN; / 右上角 三角形剪切 t = 0; for(i = ne; i imageDataindex = (char)255; void Threshold(IplImage *src) int width = src-width; int height = src-height; float minpixel = cvGet2D(src,0,0).val0; float maxpixel = cvGet2D(src,0,0).val0; CvScalar s; for(int i = 0; i maxpixel) maxpixel = s.val0; if(s.val0 minpixel) minpixel = s.val0; float firstgrey = (maxpixel + minpixel) / 2; printf(“%fn“,firstgrey); float lastgrey; float sum1 = 0,sum2 = 0; int num1 = 0,num2 = 0; int result = 0; while(1) result +; for(i = 0; i height; i+) for(int j = 0; j width; j+) s = cvGet2D(src,i,j); if(s.val0 firstgrey) sum1 += s.val0; num1+; if(s.val0 firstgrey) sum2 += s.val0; num2+; lastgrey = (sum