OpenCV特征提取

Posted 2021-02-09 sownchz

http://www.cnblogs.com/yingying0907/archive/2011/08/06/2129472.html

 

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:\\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 <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 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 ",cornersCount);

 

//开始画出每个点

if (cornersCount>0)

{

for (i=0;i<cornersCount;i++)

{

cvCircle(srcImage,cvPoint((int)(corners[i].x),(int)(corners[i].y)),2,color,2,CV_AA,0);

}

}

cvShowImage("image",srcImage);

cvSaveImage("imagedst.png",srcImage);

 

cvReleaseImage(&srcImage);

cvReleaseImage(&grayImage);

cvReleaseImage(&corners1);

cvReleaseImage(&corners2);

 

cvWaitKey(0);

return 0;

}

运行效果截图：

 

 

 

?  Hough直线提取：

Code：

 

#include <cv.h>

#include <highgui.h>

#include <math.h>

 

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 <cv.h>

#include <highgui.h>

#include <math.h>

#include <iostream>

 

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= "<<cvRound(p[0])<<endl<<"圆心坐标y= "<<cvRound(p[1])<<endl;

          cout<<"半径="<<cvRound(p[2])<<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>

 

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 ); 

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