基于OPENCV的多种特征提取总结.docx

发布时间：2022-05-29 发布人：admin 分类：说明书资料大小：2.49M 资料格式：docx 举报版权申诉

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特征提取代码总结颜色提取 • 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

Hough 直线提取： • Code： #include #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++ ) { 0 ); float* p = (float*)cvGetSeqElem( circles, i ); cvCircle( img, cvPoint(cvRound(p[0]),cvRound(p[1])), 3, CV_RGB(0,255,0), -1, 8, 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= "<

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