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 <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