opencv检测直线、圆、矩形

检测直线：cvHoughLines，cvHoughLines2

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

#include

#include

 

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 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 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

#include

#include

 

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 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 

#endif

#ifndef _EiC

#include "cv.h"

#include "highgui.h"

#include 

#include 

#include 

#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 

        {

            // 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 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