Opencv検出直線、円、矩形

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検出直線:cvHoughLines,cvHoughLines 2
検出円:cvHoughCircles
検出矩形:opencvには対応する関数がありません.次のセグメントコードは矩形を検出します.まず直線を探してから、直線が平行で垂直な4本の線を見つけます.
直線コードの検出:
/* 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 < 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;
}
円コードの検出:
#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 < 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;
}
矩形コードの検出:
/*
        
*/
#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
", 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