/* CvBox2D skin_rect; CvMemStorage* storage = cvCreateMemStorage(0); CvSeq* contour = 0; CvMemStorage* storage2 = cvCreateMemStorage(0); CvSeq* contour2 = 0; cvFindContours( fore, storage, &contour, sizeof(CvContour),CV_RETR_LIST, CV_CHAIN_APPROX_NONE, cvPoint(0,0)); CvSeq* contour_max=0; for( ; contour != 0; contour = contour->h_next ) { int tmparea=abs(cvContourArea(contour,CV_WHOLE_SEQ));//轮廓区域的面积 if (tmparea<14)//大量数据得到-----------同时整个区域的样本数量为0 样本可以分到杂质 { cvSeqRemove(contour,0); continue; } num_connect++; double tmpcount=cvArcLength(contour,CV_WHOLE_SEQ,-1); skin_rect = cvMinAreaRect2(contour, 0);//最小外界矩形 float tmpbox=(float)skin_rect.size.height/skin_rect.size.width;//长宽比 //h_axis=skin_rect.size.height; //w_axis=skin_rect.size.width; if(tmparea > maxarea) { maxarea = tmparea;//最大面积连通区域 contour_max=cvCloneSeq(contour); } if(tmpcount > count) { count = tmpcount;//最大轮廓的像素数 } if(tmpbox > axisratio) { axisratio = tmpbox;//最大长短轴的比值 } } if (contour_max!=0) { CvScalar color = CV_RGB( rand()&255, 0, 0 ); cvDrawContours(dst, contour_max, color, color, -1, -1, 8); ConcavityRepair(dst,3);//对fore图像进行修补 cvFindContours( dst, storage2, &contour2, sizeof(CvContour),CV_RETR_LIST, CV_CHAIN_APPROX_NONE, cvPoint(0,0));
cvDrawContours(src, contour2, color, color, -1, 1, 8);/* /************************************************************************/ /* 图像轮廓的HU矩 */ /************************************************************************//* CvMoments m; CvHuMoments hu; //cvMoments(cvGetSubRect(fore,&mat,rct),&m,0); cvMoments(contour2,&m,0); cvGetHuMoments(&m,&hu); huju[0]=(float)fabs(log10(fabs(hu.hu1))); huju[1]=(float)fabs(log10(fabs(hu.hu2))); huju[2]=(float)fabs(log10(fabs(hu.hu3))); huju[3]=(float)fabs(log10(fabs(hu.hu4))); huju[4]=(float)fabs(log10(fabs(hu.hu5))); huju[5]=(float)fabs(log10(fabs(hu.hu6))); huju[6]=(float)fabs(log10(fabs(hu.hu7)));*/ /************************************************************************/ /* 图像重心及半径分布 */ /************************************************************************/ /* double m00,x,y; double r_long=0; double r_short=100; int num_long,num_short;//长、短轴对应的弧度 float dist_sum=0;//距离和 m00=cvGetSpatialMoment(&m,0,0); x=cvGetSpatialMoment(&m,1,0)/m00; //重心坐标 y=cvGetSpatialMoment(&m,0,1)/m00; int contour_max_count=contour2->total; //this is number point in contour CvPoint* pointarray; float* dist_center=new float[contour_max_count]; pointarray=(CvPoint*)malloc(contour_max_count*sizeof(CvPoint)); cvCvtSeqToArray(contour2,pointarray,CV_WHOLE_SEQ); //查找最长和最短轴 for (i=0;i<contour_max_count;i++) { dist_center[i]=sqrt(((float)pointarray[i].x-x)*((float)pointarray[i].x-x)+((float)pointarray[i].y-y)*((float)pointarray[i].y-y)); //fprintf(stream,"%f ",dist_center[i]); dist_sum+=dist_center[i]; if (r_long<dist_center[i]) { r_long=dist_center[i]; num_long=i; } if (r_short>dist_center[i]) { r_short=dist_center[i]; num_short=i; } } axisratio=r_long/r_short;//计算长短轴的比值 axis_angle=(float)abs(num_long-num_short)/contour_max_count;//计算长短轴对应的角度 dist_avar=dist_sum/contour_max_count;//均值 float vari_temp=0; for (i=0;i<contour_max_count;i++) { vari_temp+=(dist_center[i]-dist_vari)*(dist_center[i]-dist_vari); } dist_vari=sqrt(vari_temp/contour_max_count); free(pointarray); delete[] dist_center;*/ /************************************************************************/ /* 细胞核灰度均值、方差、图像熵 */ /*注意：找轮廓的时候已经删除了一部分小面积的区域，这部分是否参与计算 */ /************************************************************************//* int sum_gray=0;//灰度和 int sum_pix=0;//像素和 float ffreq[256]={0}; for (i=0;i<dst->height;i++) { for (int j=0;j<dst->width;j++) { if (((uchar*)(dst->imageData+i*dst->widthStep))[j]==255) { sum_pix++; int temp=((uchar*)(src->imageData+i*src->widthStep))[j]; sum_gray+=temp; ffreq[temp]++; } } } for (i=0;i<256;i++) { ffreq[i]/=(float)sum_pix; } // 计算图像熵 for (i = 0; i < 256; i ++) { // 判断概率是否大于0 if (ffreq[i] > 0) { // 计算图像熵 shan_maxcontour -= ffreq[i] * log(ffreq[i]) / log(2.0); } } averagegray=(double)sum_gray/sum_pix;//均值 int grey_s=0; for (i=0;i<dst->height;i++) { for (int j=0;j<dst->width;j++) { if (((uchar*)(dst->imageData+i*dst->widthStep))[j]==255) { grey_s+=(((uchar*)(src->imageData+i*src->widthStep))[j]-averagegray)*(((uchar*)(src->imageData+i*src->widthStep))[j]-averagegray); } } } variance_gray=sqrt(grey_s/(sum_pix+eps)); //方差
} else { return 0; }
CString aa(Path); aa+="-1.jpg";//保存图像为新的路径，但不影响原先的bmp图像 cvSaveImage(aa,src); cvReleaseMemStorage(&storage2); cvReleaseMemStorage(&storage);*/
