特征提取代码
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颜色提取 颜色直方图提取： Code: #include
#include #include using namespace std; int main( int argc, char** argv ) { IplImage * src= cvLoadImage("E:\\Download\\test1.jpg",1); IplImage* hsv = cvCreateImage( cvGetSize(src), 8, 3 ); IplImage* h_plane = cvCreateImage( cvGetSize(src), 8, 1 ); IplImage* s_plane = cvCreateImage( cvGetSize(src), 8, 1 ); IplImage* v_plane = cvCreateImage( cvGetSize(src), 8, 1 ); IplImage* planes[] = { h_plane, s_plane }; /** H 分量划分为16个等级，S分量划分为8个等级*/ int h_bins = 16, s_bins = 8; int hist_size[] = {h_bins, s_bins}; /** H 分量的变化范围*/ float h_ranges[] = { 0, 180 }; /** S 分量的变化范围*/ float s_ranges[] = { 0, 255 }; float* ranges[] = { h_ranges, s_ranges }; /** 输入图像转换到HSV颜色空间*/ cvCvtColor( src, hsv, CV_BGR2HSV ); cvCvtPixToPlane( hsv, h_plane, s_plane, v_plane, 0 ); /** 创建直方图，二维, 每个维度上均分*/ CvHistogram * hist = cvCreateHist( 2, hist_size, CV_HIST_ARRAY, ranges, 1 ); /** 根据H,S两个平面数据统计直方图*/ cvCalcHist( planes, hist, 0, 0 ); /** 获取直方图统计的最大值，用于动态显示直方图*/ float max_value; cvGetMinMaxHistValue( hist, 0, &max_value, 0, 0 ); /** 设置直方图显示图像*/ int height = 240; int width = (h_bins*s_bins*6); IplImage* hist_img = cvCreateImage( cvSize(width,height), 8, 3 ); cvZero( hist_img ); /** 用来进行HSV到RGB颜色转换的临时单位图像*/ IplImage * hsv_color = cvCreateImage(cvSize(1,1),8,3); IplImage * rgb_color = cvCreateImage(cvSize(1,1),8,3); int bin_w = width / (h_bins * s_bins); for(int h = 0; h < h_bins; h++) { for(int s = 0; s < s_bins; s++) { int i = h*s_bins + s; /** 获得直方图中的统计次数，计算显示在图像中的高度*/ float bin_val = cvQueryHistValue_2D( hist, h, s ); int intensity = cvRound(bin_val*height/max_value); /** 获得当前直方图代表的颜色，转换成RGB用于绘制*/ cvSet2D(hsv_color,0,0,cvScalar(h*180.f / h_bins,s*255.f/s_bins,255,0)); cvCvtColor(hsv_color,rgb_color,CV_HSV2BGR); CvScalar color = cvGet2D(rgb_color,0,0); cvRectangle( hist_img, cvPoint(i*bin_w,height), cvPoint((i+1)*bin_w,height - intensity), color, -1, 8, 0 ); } } cvNamedWindow( "Source", 1 ); cvShowImage( "Source", src ); cvNamedWindow( "H-S Histogram", 1 ); cvShowImage( "H-S Histogram", hist_img ); cvWaitKey(0); } 运行效果截图： 形状提取 Candy算子对边缘提取： Code： #include "cv.h" #include "cxcore.h" #include "highgui.h" int main( int argc, char** argv ) { //声明IplImage指针 IplImage* pImg = NULL; IplImage* pCannyImg = NULL; //载入图像，强制转化为Gray pImg = cvLoadImage( "E:\\Download\\test.jpg", 0); //为canny边缘图像申请空间 pCannyImg = cvCreateImage(cvGetSize(pImg), IPL_DEPTH_8U, 1); //canny边缘检测 cvCanny(pImg, pCannyImg, 50, 150, 3); //创建窗口 cvNamedWindow("src", 1); cvNamedWindow("canny",1); //显示图像 cvShowImage( "src", pImg ); cvShowImage( "canny", pCannyImg ); //等待按键 cvWaitKey(0); //销毁窗口 cvDestroyWindow( "src" ); cvDestroyWindow( "canny" ); //释放图像 cvReleaseImage( &pImg ); cvReleaseImage( &pCannyImg ); return 0; } 运行效果截图： 角点提取： Code： #include #include "cv.h" #include "highgui.h" #define MAX_CORNERS 100 int main(void) { int cornersCount=MAX_CORNERS;//得到的角点数目 CvPoint2D32f corners[MAX_CORNERS];//输出角点集合 IplImage *srcImage = 0,*grayImage = 0,*corners1 = 0,*corners2 = 0; int i; CvScalar color = CV_RGB(255,0,0); cvNamedWindow("image",1); //Load the image to be processed srcImage = cvLoadImage("E:\\Download\\1.jpg",1); grayImage = cvCreateImage(cvGetSize(srcImage),IPL_DEPTH_8U,1); //copy the source image to copy image after converting the format //复制并转为灰度图像 cvCvtColor(srcImage,grayImage,CV_BGR2GRAY); //create empty images os same size as the copied images //两幅临时位浮点图像，cvGoodFeaturesToTrack会用到 corners1 = cvCreateImage(cvGetSize(srcImage),IPL_DEPTH_32F,1); corners2 = cvCreateImage(cvGetSize(srcImage),IPL_DEPTH_32F,1); cvGoodFeaturesToTrack(grayImage,corners1,corners2,corners,&cornersCount,0.05, 30,//角点的最小距离是 0,//整个图像 3,0,0.4); printf("num corners found: %d\n",cornersCount); //开始画出每个点 if (cornersCount>0) { for (i=0;i #include #include int main(int argc, char** argv) { IplImage* src = cvLoadImage( "E:\\Download\\2.jpg" , 0 ); IplImage* dst; IplImage* color_dst; CvMemStorage* storage = cvCreateMemStorage(0); CvSeq* lines = 0; int i; if( !src ) return -1; dst = cvCreateImage( cvGetSize(src), 8, 1 ); color_dst = cvCreateImage( cvGetSize(src), 8, 3 ); cvCanny( src, dst, 50, 200, 3 ); cvCvtColor( dst, color_dst, CV_GRAY2BGR ); #if 0 lines = cvHoughLines2( dst, storage, CV_HOUGH_STANDARD, 1, CV_PI/180, 100, 0, 0 ); for( i = 0; i < MIN(lines->total,100); i++ ) { float* line = (float*)cvGetSeqElem(lines,i); float rho = line[0]; float theta = line[1]; CvPoint pt1, pt2; double a = cos(theta), b = sin(theta); double x0 = a*rho, y0 = b*rho; pt1.x = cvRound(x0 + 1000*(-b)); pt1.y = cvRound(y0 + 1000*(a)); pt2.x = cvRound(x0 - 1000*(-b)); pt2.y = cvRound(y0 - 1000*(a)); cvLine( color_dst, pt1, pt2, CV_RGB(255,0,0), 3, CV_AA, 0 ); } #else lines = cvHoughLines2( dst, storage, CV_HOUGH_PROBABILISTIC, 1, CV_PI/180, 50, 50, 10 ); for( i = 0; i < lines->total; i++ ) { CvPoint* line = (CvPoint*)cvGetSeqElem(lines,i); cvLine( color_dst, line[0], line[1], CV_RGB(255,0,0), 3, CV_AA, 0 ); } #endif cvNamedWindow( "Source", 1 ); cvShowImage( "Source", src ); cvNamedWindow( "Hough", 1 ); cvShowImage( "Hough", color_dst ); cvWaitKey(0); return 0; } 运行效果截图： Hough圆提取： Code： #include #include #include #include using namespace std; int main(int argc, char** argv) { IplImage* img; img=cvLoadImage("E:\\Download\\3.jpg", 1); IplImage* gray = cvCreateImage( cvGetSize(img), 8, 1 ); CvMemStorage* storage = cvCreateMemStorage(0); cvCvtColor( img, gray, CV_BGR2GRAY ); cvSmooth( gray, gray, CV_GAUSSIAN, 5, 15 ); // smooth it, otherwise a lot of false circles may be detected CvSeq* circles = cvHoughCircles( gray, storage, CV_HOUGH_GRADIENT, 2, gray->height/4, 200, 100 ); int i; for( i = 0; i < circles->total; i++ ) { float* p = (float*)cvGetSeqElem( circles, i ); cvCircle( img, cvPoint(cvRound(p[0]),cvRound(p[1])), 3, CV_RGB(0,255,0), -1, 8, 0 ); cvCircle( img, cvPoint(cvRound(p[0]),cvRound(p[1])), cvRound(p[2]), CV_RGB(255,0,0), 3, 8, 0 ); cout<<"圆心坐标x= "< #include #include int thresh = 50; IplImage* img = 0; IplImage* img0 = 0; CvMemStorage* storage = 0; CvPoint pt[4];const char* wndname = "Square Detection Demo"; double angle( CvPoint* pt1, CvPoint* pt2, CvPoint* pt0 ) { double dx1 = pt1->x - pt0->x; double dy1 = pt1->y - pt0->y; double dx2 = pt2->x - pt0->x; double dy2 = pt2->y - pt0->y; return (dx1*dx2 + dy1*dy2)/sqrt((dx1*dx1 + dy1*dy1)*(dx2*dx2 + dy2*dy2) + 1e-10); } CvSeq* findSquares4( IplImage* img, CvMemStorage* storage ) { CvSeq* contours; int i, c, l, N = 11; CvSize sz = cvSize( img->width & -2, img->height & -2 ); IplImage* timg = cvCloneImage( img ); IplImage* gray = cvCreateImage( sz, 8, 1 ); IplImage* pyr = cvCreateImage( cvSize(sz.width/2, sz.height/2), 8, 3 ); IplImage* tgray; CvSeq* result; double s, t; CvSeq* squares = cvCreateSeq( 0, sizeof(CvSeq), sizeof(CvPoint), storage ); cvSetImageROI( timg, cvRect( 0, 0, sz.width, sz.height )); // down-scale and upscale the image to filter out the noise cvPyrDown( timg, pyr, 7 ); cvPyrUp( pyr, timg, 7 ); tgray = cvCreateImage( sz, 8, 1 ); // find squares in every color plane of the image for( c = 0; c < 3; c++ ) { cvSetImageCOI( timg, c+1 ); cvCopy( timg, tgray, 0 ); for( l = 0; l < N; l++ ) { if( l == 0 ) { cvCanny( tgray, gray, 0, thresh, 5 ); cvDilate( gray, gray, 0, 1 ); } else { cvThreshold( tgray, gray, (l+1)*255/N, 255, CV_THRESH_BINARY ); } cvFindContours( gray, storage, &contours, sizeof(CvContour),CV_RETR_LIST, CV_CHAIN_APPROX_SIMPLE, cvPoint(0,0) ); while( contours ) { result = cvApproxPoly( contours, sizeof(CvContour), storage,CV_POLY_APPROX_DP, cvContourPerimeter(contours)*0.02, 0 ); if( result->total == 4 && fabs(cvContourArea(result,CV_WHOLE_SEQ)) > 1000 && cvCheckContourConvexity(result) ) { s = 0; for( i = 0; i < 5; i++ ) { if( i >= 2 ) { t = fabs(angle( (CvPoint*)cvGetSeqElem( result, i ),(CvPoint*)cvGetSeqElem( result, i-2 ),(CvPoint*)cvGetSeqElem( result, i-1 ))); s = s > t ? s : t; } } if( s < 0.3 ) for( i = 0; i < 4; i++ ) cvSeqPush( squares, (CvPoint*)cvGetSeqElem( result, i )); } contours = contours->h_next; } } } cvReleaseImage( &gray ); cvReleaseImage( &pyr ); cvReleaseImage( &tgray ); cvReleaseImage( &timg ); return squares; } // the function draws all the squares in the image void drawSquares( IplImage* img, CvSeq* squares ) { CvSeqReader reader; IplImage* cpy = cvCloneImage( img ); int i; cvStartReadSeq( squares, &reader, 0 ); for( i = 0; i < squares->total; i += 4 ) { CvPoint* rect = pt; int count = 4; memcpy( pt, reader.ptr, squares->elem_size ); CV_NEXT_SEQ_ELEM( squares->elem_size, reader ); memcpy( pt + 1, reader.ptr, squares->elem_size ); CV_NEXT_SEQ_ELEM( squares->elem_size, reader ); memcpy( pt + 2, reader.ptr, squares->elem_size ); CV_NEXT_SEQ_ELEM( squares->elem_size, reader ); memcpy( pt + 3, reader.ptr, squares->elem_size ); CV_NEXT_SEQ_ELEM( squares->elem_size, reader ); cvPolyLine( cpy, &rect, &count, 1, 1, CV_RGB(0,255,0), 3, CV_AA, 0 ); } cvShowImage( wndname, cpy ); cvReleaseImage( &cpy ); } void on_trackbar( int a ) { if( img ) drawSquares( img, findSquares4( img, storage ) ); } char* names[] = { "1.jpg", 0 }; int main(int argc, char** argv) { int i, c; storage = cvCreateMemStorage(0); for( i = 0; names[i] != 0; i++ ) { img0 = cvLoadImage( names[i], 1 ); if( !img0 ) { printf("Couldn't load %s\n", names[i] ); continue; } img = cvCloneImage( img0 ); cvNamedWindow( wndname, 1 ); cvCreateTrackbar( "canny thresh", wndname, &thresh, 1000, on_trackbar ); on_trackbar(0); c = cvWaitKey(0); cvReleaseImage( &img ); cvReleaseImage( &img0 ); cvClearMemStorage( storage ); if( c == 27 ) break; } cvDestroyWindow( wndname ); return 0; } 运行效果截图： 边缘直方图提取： Code： #include "cv.h" #include "highgui.h" #include #include #define PI 3.14 int main() { IplImage *src = 0; // source imagre IplImage *histimg = 0; // histogram image CvHistogram *hist = 0; // define multi_demention histogram IplImage* canny; CvMat* canny_m; IplImage* dx; // the sobel x difference IplImage* dy; // the sobel y difference CvMat* gradient; // value of gradient CvMat* gradient_dir; // direction of gradient CvMat* dx_m; // format transform to matrix CvMat* dy_m; CvMat* mask; CvSize size; IplImage* gradient_im; int i,j; float theta; int hdims = 8; // 划分HIST的个数，越高越精确 float hranges_arr[] = {-PI/2,PI/2}; // 直方图的上界和下界 float* hranges = hranges_arr; float max_val; // int bin_w; src=cvLoadImage("E:\\Download\\test.jpg", 0); // force to gray image if(src==0) return -1; cvNamedWindow( "Histogram", 0 ); //cvNamedWindow( "src", 0); size=cvGetSize(src); canny=cvCreateImage(cvGetSize(src),8,1);//边缘图像 dx=cvCreateImage(cvGetSize(src),32,1);//x方向上的差分//此处的数据类型为U 不怕溢出吗？ dy=cvCreateImage(cvGetSize(src),32,1); gradient_im=cvCreateImage(cvGetSize(src),32,1);//梯度图像 canny_m=cvCreateMat(size.height,size.width,CV_32FC1);//边缘矩阵 dx_m=cvCreateMat(size.height,size.width,CV_32FC1); dy_m=cvCreateMat(size.height,size.width,CV_32FC1); gradient=cvCreateMat(size.height,size.width,CV_32FC1);//梯度矩阵 gradient_dir=cvCreateMat(size.height,size.width,CV_32FC1);//梯度方向矩阵 mask=cvCreateMat(size.height,size.width,CV_32FC1);//掩码 cvCanny(src,canny,60,180,3);//边缘检测 cvConvert(canny,canny_m);//把图像转换为矩阵 cvSobel(src,dx,1,0,3);// 一阶X方向的图像差分:dx cvSobel(src,dy,0,1,3);// 一阶Y方向的图像差分:dy cvConvert(dx,dx_m); cvConvert(dy,dy_m); cvAdd(dx_m,dy_m,gradient); // value of gradient//梯度不是等于根号下x的导数的平方加上y导数的平方吗？ cvDiv(dx_m,dy_m,gradient_dir); // direction for(i=0;ibins, hist->bins, max_val ? 255. / max_val : 0., 0 ); // 缩放bin 到区间[0,255] ，比例系数 cvZero( histimg ); bin_w = histimg->width /16; // hdims: 条的个数，则bin_w 为条的宽度 // 画直方图 for( i = 0; i < hdims; i++ ) { double val = ( cvGetReal1D(hist->bins,i)*histimg->height/255 ); // 返回单通道数组的指定元素， 返回直方图第i条的大小，val为histimg中的i条的高度 CvScalar color = CV_RGB(255,255,0); //(hsv2rgb(i*180.f/hdims);//直方图颜色 cvRectangle( histimg, cvPoint(100+i*bin_w,histimg->height),cvPoint(100+(i+1)*bin_w,(int)(histimg->height - val)), color, 1, 8, 0 ); // 画直方图——画矩形，左下角，右上角坐标 } cvShowImage( "src", src); cvShowImage( "Histogram", histimg ); cvWaitKey(0); cvDestroyWindow("src"); cvDestroyWindow("Histogram"); cvReleaseImage( &src ); cvReleaseImage( &histimg ); cvReleaseHist ( &hist ); return 0; } 运行效果截图： 视频流中边缘检测： Code： #include "highgui.h" #include "cv.h" #include "stdio.h" #include int main(int argc,char ** argv) { IplImage * laplace = 0; IplImage * colorlaplace = 0; IplImage * planes[3] = {0,0,0}; CvCapture *capture = 0; //从摄像头读取 /*if(argc == 1 ||( argc==2 && strlen(argv[1])==1 && isdigit(argv[1][0]) )) capture = cvCaptureFromCAM(argc == 2 ? argv[1][0] -'0':0);*/ //从文件中读取 /* else if(argc == 2)*/ capture = cvCaptureFromAVI("1.avi"); if(!capture) { fprintf(stderr,"Could not initialize capturing...\n"); return -1; } cvNamedWindow("Laplacian",1); cvNamedWindow("video",1); //循环捕捉，直到用户按键跳出循环体 for(;;) { IplImage * frame =0; //抓起一祯 frame = cvQueryFrame(capture); if(!frame) break; if(!laplace) { //创建图像 for(int i=0;i<3;i++) planes[i] = cvCreateImage(cvSize(frame->width,frame->height),IPL_DEPTH_8U,1); laplace = cvCreateImage(cvSize(frame->width,frame->height),IPL_DEPTH_16S,1); colorlaplace=cvCreateImage(cvSize(frame->width,frame->height),IPL_DEPTH_8U,3); } cvCvtPixToPlane(frame,planes[0],planes[1],planes[2],0); for(int i=0;i<3;i++) { //交换，如通道变换 cvLaplace(planes[i],laplace,3); //使用线性变换转换输入函数元素成为无符号整形 cvConvertScaleAbs(laplace,planes[i],1,0); } cvCvtPlaneToPix(planes[0],planes[1],planes[2],0,colorlaplace); //结构相同（- 顶—左结构,1 - 底—左结构） colorlaplace->origin = frame->origin; //高斯滤波，平滑图像 // cvSmooth(colorlaplace, colorlaplace, CV_GAUSSIAN, 1, 0, 0); //形态学滤波,闭运算 cvDilate(colorlaplace, colorlaplace, 0, 1);//膨胀 cvErode(colorlaplace, colorlaplace, 0, 1);//腐蚀 cvShowImage("video", frame); cvShowImage("Laplacian",colorlaplace); if(cvWaitKey(10)>0) break; } cvReleaseCapture(&capture); cvDestroyWindow("Laplacian"); cvDestroyWindow("video"); return 0; } 运行效果截图： 纹理提取： Code： #include #include #include "cv.h" #include "highgui.h" int main(int argc, char* argv[]) { int tmp[8]={0}; int sum=0;int k=0; IplImage* img,*dst; img=cvLoadImage("E:\\Download\\2.jpg",0); CvScalar s; cvNamedWindow("img",NULL); cvNamedWindow("dst",NULL); cvShowImage("img",img); uchar* data=(uchar*)img->imageData; int step=img->widthStep; dst=cvCreateImage(cvSize(img->width,img->height),img->depth,1); dst->widthStep=img->widthStep; for(int i=1;iheight-1;i++) for(int j=1;jwidth-1;j++) { if(data[(i-1)*step+j-1]>data[i*step+j]) tmp[0]=1; else tmp[0]=0; if(data[i*step+(j-1)]>data[i*step+j]) tmp[1]=1; else tmp[1]=0; if(data[(i+1)*step+(j-1)]>data[i*step+j]) tmp[2]=1; else tmp[2]=0; if (data[(i+1)*step+j]>data[i*step+j]) tmp[3]=1; else tmp[3]=0; if (data[(i+1)*step+(j+1)]>data[i*step+j]) tmp[4]=1; else tmp[4]=0; if(data[i*step+(j+1)]>data[i*step+j]) tmp[5]=1; else tmp[5]=0; if(data[(i-1)*step+(j+1)]>data[i*step+j]) tmp[6]=1; else tmp[6]=0; if(data[(i-1)*step+j]>data[i*step+j]) tmp[7]=1; else tmp[7]=0; for(k=0;k<=7;k++) sum+=abs(tmp[k]-tmp[k+1]); sum=sum+abs(tmp[7]-tmp[0]); if (sum<=2) s.val[0]=(tmp[0]*128+tmp[1]*64+tmp[2]*32+tmp[3]*16+tmp[4]*8+tmp[5]*4+tmp[6]*2+tmp[7]); else s.val[0]=59; cvSet2D(dst,i,j,s); } cvShowImage("dst",dst); cvWaitKey(-1); return 0; } 运行效果截图：
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