opencv 检测直线 圆 矩形

               

检测直线:cvHoughLinescvHoughLines2

检测圆:cvHoughCircles

检测矩形:opencv中没有对应的函数,下面有段代码可以检测矩形,是通过先找直线,然后找到直线平行与垂直的四根线。

 

检测直线代码:

/* This is a standalone program. Pass an image name as a first parameter of the program.

   Switch between standard and probabilistic Hough transform by changing "#if 1" to "#if 0" and back */

#include <cv.h>

#include <highgui.h>

#include <math.h>

 

int main(int argc, char** argv)

{

    const char* filename = argc >= 2 ? argv[1] : "pic1.png";

    IplImage* src = cvLoadImage( filename, 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;

}

 

 

检测圆代码:

#include <cv.h>

#include <highgui.h>

#include <math.h>

 

int main(int argc, char** argv)

{

    IplImage* img;

    if( argc == 2 && (img=cvLoadImage(argv[1], 1))!= 0)

    {

        IplImage* gray = cvCreateImage( cvGetSize(img), 8, 1 );

        CvMemStorage* storage = cvCreateMemStorage(0);

        cvCvtColor( img, gray, CV_BGR2GRAY );

        cvSmooth( gray, gray, CV_GAUSSIAN, 9, 9 ); // 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 );

        }

        cvNamedWindow( "circles", 1 );

        cvShowImage( "circles", img );

    }

    return 0;

}

 

 

检测矩形代码:

/*
在程序里找寻矩形
*/
#ifdef _CH_
#pragma package <opencv>
#endif
 
#ifndef _EiC
#include "cv.h"
#include "highgui.h"
#include <stdio.h>
#include <math.h>
#include <string.h>
#endif
 
int thresh = 50;
IplImage* img = 0;
IplImage* img0 = 0;
CvMemStorage* storage = 0;
CvPoint pt[4];
const char* wndname = "Square Detection Demo";
 
// helper function:
// finds a cosine of angle between vectors
// from pt0->pt1 and from pt0->pt2 
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);
}
 
// returns sequence of squares detected on the image.
// the sequence is stored in the specified memory storage
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 ); // make a copy of input image
    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;
    // create empty sequence that will contain points -
    // 4 points per square (the square's vertices)
    CvSeq* squares = cvCreateSeq( 0, sizeof(CvSeq), sizeof(CvPoint), storage );
    
    // select the maximum ROI in the image
    // with the width and height divisible by 2
    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++ )
    {
        // extract the c-th color plane
        cvSetImageCOI( timg, c+1 );
        cvCopy( timg, tgray, 0 );
        
        // try several threshold levels
        for( l = 0; l < N; l++ )
        {
            // hack: use Canny instead of zero threshold level.
            // Canny helps to catch squares with gradient shading   
            if( l == 0 )
            {
                // apply Canny. Take the upper threshold from slider
                // and set the lower to 0 (which forces edges merging) 
                cvCanny( tgray, gray, 0, thresh, 5 );
                // dilate canny output to remove potential
                // holes between edge segments 
                cvDilate( gray, gray, 0, 1 );
            }
            else
            {
                // apply threshold if l!=0:
                //     tgray(x,y) = gray(x,y) < (l+1)*255/N ? 255 : 0
                cvThreshold( tgray, gray, (l+1)*255/N, 255, CV_THRESH_BINARY );
            }
            
            // find contours and store them all as a list
            cvFindContours( gray, storage, &contours, sizeof(CvContour),
                CV_RETR_LIST, CV_CHAIN_APPROX_SIMPLE, cvPoint(0,0) );
            
            // test each contour
            while( contours )
            {
                // approximate contour with accuracy proportional
                // to the contour perimeter
                result = cvApproxPoly( contours, sizeof(CvContour), storage,
                    CV_POLY_APPROX_DP, cvContourPerimeter(contours)*0.02, 0 );
                // square contours should have 4 vertices after approximation
                // relatively large area (to filter out noisy contours)
                // and be convex.
                // Note: absolute value of an area is used because
                // area may be positive or negative - in accordance with the
                // contour orientation
                if( result->total == 4 &&
                    fabs(cvContourArea(result,CV_WHOLE_SEQ)) > 1000 &&
                    cvCheckContourConvexity(result) )
                {
                    s = 0;
                    
                    for( i = 0; i < 5; i++ )
                    {
                        // find minimum angle between joint
                        // edges (maximum of cosine)
                        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 cosines of all angles are small
                    // (all angles are ~90 degree) then write quandrange
                    // vertices to resultant sequence 
                    if( s < 0.3 )
                        for( i = 0; i < 4; i++ )
                            cvSeqPush( squares,
                                (CvPoint*)cvGetSeqElem( result, i ));
                }
                
                // take the next contour
                contours = contours->h_next;
            }
        }
    }
    
    // release all the temporary images
    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;
    
    // initialize reader of the sequence
    cvStartReadSeq( squares, &reader, 0 );
    
    // read 4 sequence elements at a time (all vertices of a square)
    for( i = 0; i < squares->total; i += 4 )
    {
        CvPoint* rect = pt;
        int count = 4;
        
        // read 4 vertices
        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 );
        
        // draw the square as a closed polyline 
        cvPolyLine( cpy, &rect, &count, 1, 1, CV_RGB(0,255,0), 3, CV_AA, 0 );
    }
    
    // show the resultant image
    cvShowImage( wndname, cpy );
    cvReleaseImage( &cpy );
}
 
 
void on_trackbar( int a )
{
    if( img )
        drawSquares( img, findSquares4( img, storage ) );
}
 
char* names[] = { "pic1.png", "pic2.png", "pic3.png",
                  "pic4.png", "pic5.png", "pic6.png", 0 };
 
int main(int argc, char** argv)
{
    int i, c;
    // create memory storage that will contain all the dynamic data
    storage = cvCreateMemStorage(0);
 
    for( i = 0; names[i] != 0; i++ )
    {
        // load i-th image
        img0 = cvLoadImage( names[i], 1 );
        if( !img0 )
        {
            printf("Couldn't load %s/n", names[i] );
            continue;
        }
        img = cvCloneImage( img0 );
        
        // create window and a trackbar (slider) with parent "image" and set callback
        // (the slider regulates upper threshold, passed to Canny edge detector) 
        cvNamedWindow( wndname, 1 );
        cvCreateTrackbar( "canny thresh", wndname, &thresh, 1000, on_trackbar );
        
        // force the image processing
        on_trackbar(0);
        // wait for key.
        // Also the function cvWaitKey takes care of event processing
        c = cvWaitKey(0);
        // release both images
        cvReleaseImage( &img );
        cvReleaseImage( &img0 );
        // clear memory storage - reset free space position
        cvClearMemStorage( storage );
        if( c == 27 )
            break;
    }
    
    cvDestroyWindow( wndname );
    
    return 0;
}
 
#ifdef _EiC
main(1,"squares.c");
#endif

 

           

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