OPENCV特征提取代码总结

1、特征提取代码总结来自 特征提取代码总结颜色提取颜色直方图提取：code:#include <cv.h> #include <highgui.h> #include <iostream> using namespace std;int main( int argc, char* argv )iplimage * src= cvloadimage(“e:downloadtest1.jpg“,1);iplimage* hsv = cvcreateimage( cvgetsize(src), 8, 3 ); iplimage* h_plane = cvcreatei

2、mage( 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 重量划分为 16 个等级，s 重量划分为 8 个等级*/ int h_bins = 16, s_bins = 8;int hist_size = h_bins, s_bins;/* h 重量的变化范围*/float h_

3、ranges = 0, 180 ;/* s 重量的变化范围*/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 );

4、/* 依据 h,s 两个平面数据统计直方图*/ cvcalchist( planes, hist, 0, 0 );/* 猎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 )

5、;/* 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*/ flo

6、at 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

7、_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：外形提取candy 算子对边缘提取：code：#include “cv.h“ #include “cxcore

8、.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 graypimg = cvloadimage( “e:downloadtest.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, 1

9、50, 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：#in

10、clude <stdio.h> #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 cornersmax_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

11、“,1);/load the image to be processedsrcimage = cvloadimage(“e:download1.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

12、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 corn

13、ers found: %dn“,cornerscount);/开头画出每个点if (cornerscount>0)for (i=0;i<cornerscount;i+)cvcircle(srcimage,cvpoint(int)(cornersi.x),(int)(cornersi.y),2,color,2,cv_aa,0);cvshowimage(“image“,srcimage); cvsaveimage(“imagedst.png“,srcimage); cvreleaseimage(&srcimage); cvreleaseimage(&grayimage)

14、; cvreleaseimage(&corners1); cvreleaseimage(&corners2); cvwaitkey(0);return 0;运行效果截图：h ough 直线提取：code：#include <cv.h> #include <highgui.h> #include <math.h>int main(int argc, char* argv)iplimage* src = cvloadimage( “e:download2.jpg“ , 0 ); iplimage* dst;iplimage* color_dst;

15、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 0lines = cvhoughlines2( dst, storage

16、, 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 = line0;float theta = line1; cvpoint pt1, pt2;double a = cos(theta), b = sin(theta); double x0 = a*rho, y0 = b*rho;#elsept1.x = cvround(x0 + 1000*(-b

17、); 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 );lines = cvhoughlines2( dst, storage, cv_hough_probabilistic, 1, cv_pi/180, 50, 50, 10 ); for( i = 0; i < lines->total; i+ )#endifcvpoint*

18、line = (cvpoint*)cvgetseqelem(lines,i);cvline( color_dst, line0, line1, cv_rgb(255,0,0), 3, cv_aa, 0 );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 <cv.h> #include

19、<highgui.h> #include <math.h> #include <iostream> using namespace std;int main(int argc, char* argv)iplimage* img; img=cvloadimage(“e:download3.jpg“, 1);iplimage* gray = cvcreateimage( cvgetsize(img), 8, 1 ); cvmemstorage* storage = cvcreatememstorage(0); cvcvtcolor( img, gray, cv_

20、bgr2gray );cvsmooth( gray, gray, cv_gaussian, 5, 15 );/ smooth it, otherwise a lot of false circles may be detectedcvseq* circles = cvhoughcircles( gray, storage, cv_hough_gradient, 2, gray->height/4, 200, 1 00 );int i;for( i = 0; i < circles->total; i+ )float* p = (float*)cvgetseqelem( cir

21、cles, i );cvcircle( img, cvpoint(cvround(p0),cvround(p1), 3, cv_rgb(0,255,0), -1, 8, 0);cvcircle( img, cvpoint(cvround(p0),cvround(p1), cvround(p2), cv_rgb(255,0,0), 3, 8, 0 );cout<<“圆心坐标 x= “<<cvround(p0)<<endl<<“圆心坐标 y= “<<cvround(p1)<<endl; cout<<“半径=“<

22、;<cvround(p2)<<endl;cout<<“圆数量=“<<circles->total<<endl; cvnamedwindow( “circles“, 1 ); cvshowimage( “circles“, img ); cvwaitkey(0);return 0;运行效果截图：hough 矩形提取：code：#include “cv.h“ #include “highgui.h“ #include <stdio.h> #include <math.h> #include <string.h

23、> int thresh = 50; iplimage* img = 0; iplimage* img0 = 0;cvmemstorage* storage = 0;cvpoint pt4;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 - pt

24、0->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*

25、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.w

26、idth, 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

27、; l < n; l+ )if( l = 0 )cvcanny( tgray, gray, 0, thresh, 5 ); cvdilate( gray, gray, 0, 1 );elsecvthreshold( tgray, gray, (l+1)*255/n, 255, cv_thresh_binary );cvfindcontours( gray, storage, &contours, sizeof(cvcontour),cv_retr_list, cv_chain_approx_si mple, cvpoint(0,0) );while( contours )resu

28、lt = cvapproxpoly( contours, sizeof(cvcontour), storage,cv_poly_approx_dp, cvcontourper imeter(contours)*0.02, 0 );if( result->total = 4 && fabs(cvcontourarea(result,cv_whole_seq) > 1000 &&cvcheckcont ourconvexity(result) )s = 0;for( i = 0; i < 5; i+ )if( i >= 2 )t = fabs

29、(angle( (cvpoint*)cvgetseqelem( result, i ),(cvpoint*)cvgetseqelem( result, i-2 ),(c vpoint*)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 );

30、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,

31、 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

32、 + 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

33、); 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; namesi != 0; i+ )img0 = cvloadimage( namesi, 1 ); if( !img0 )printf(“couldn”

34、t load %sn“, namesi ); 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 )bre

35、ak;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 <stdio.h>#include <ctype.h> #define pi 3.14 int main()iplimage *src = 0; / source imagre iplimage *histimg = 0; / histogram imagecvhistogram *hist = 0; / define multi_demention histo

36、gram iplimage* canny;cvmat* canny_m;iplimage* dx; / the sobel x difference iplimage* dy; / the sobel y difference cvmat* gradient; / value of gradientcvmat* gradient_dir; / direction of gradient cvmat* dx_m; / format transform to matrix cvmat* dy_m;cvmat* mask; cvsizesize;iplimage* gradient_im; int

37、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:downloadtest.jpg“, 0); / force to gray image if(src=0) return -1;cvnamedwindow( “histogram“, 0 );/cvnamedwindow( “src“, 0); size=cvge

38、tsize(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,s

39、ize.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,ca

40、nny_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;i<size.height;i+) for(j=0;j<size.w

41、idth;j+)if(cvmget(canny_m,i,j)!=0 && cvmget(dx_m,i,j)!=0)/此行是什么意思？只看边缘上的方向？theta=cvmget(gradient_dir,i,j); theta=atan(theta);cvmset(gradient_dir,i,j,theta);elsecvmset(gradient_dir,i,j,0);hist = cvcreatehist( 1, &hdims, cv_hist_array, &hranges, 1 );/ 创建一个指定尺寸的直方图，并返回创建的直方图指针histimg =

42、cvcreateimage( cvsize(320,200), 8, 3 ); / 创建一个图像，通道cvzero( histimg ); / 清； cvconvert(gradient_dir,gradient_im);/把梯度方向矩阵转化为图像cvcalchist( &gradient_im, hist, 0, canny ); / 计算直方图cvgetminmaxhistvalue( hist, 0, &max_val, 0, 0 ); / 只找最大值cvconvertscale( hist->bins, hist->bins, max_val ? 255.

43、/ 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

44、(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“);

45、 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 <ctype.h>int main(int argc,char * argv)iplimage * laplace = 0; iplimage * colorla

46、place = 0; iplimage * planes3 = 0,0,0; cvcapture *capture = 0;/从摄像头读取/*if(argc = 1 |( argc=2 && strlen(argv1)=1 && isdigit(argv10) ) capture = cvcapturefromcam(argc = 2 ? argv10 -”0”:0);*/从文件中读取/* else if(argc = 2)*/capture = cvcapturefromavi(“1.avi“); if(!capture)fprintf(stderr,“cou

47、ld not initialize capturing.n“); return -1;cvnamedwindow(“laplacian“,1); cvnamedwindow(“video“,1);/循环捕获，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+)planesi = cvcreateimage(cvsize(frame->width,frame->height),ip

48、l_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,planes0,planes1,planes2,0); for(int i=0;i<3;i+)/交换，如通道变换cvlaplace(planesi,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,planesi,1,0);cvcvtplanetopix(planes0,planes1,planes2,0,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(colo