【opencv+C++】在图像中找四边形

转载 2014年11月15日 14:02:40

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/*
这个程序的基本思想是：对输入的图像进行滤波去掉噪音，然后进行canny边缘检测，之后进行膨胀，然后寻找轮廓，对轮廓进行多边形的逼近，检测多边形的点数是否是4而且各个角的的余弦是否是小于某个值，程序中认为是0.3，然后就判断该多边形是四边形，之后根据这四个点画出该图像。
ps：我对程序中余弦定理的使用感觉公式用错了
*/
#include "stdafx.h"
#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";
// 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;
//1e-10就是“aeb”的形式，表示a乘以10的b次方。
//其中b必须是整数，a可以是小数。
//?余弦定理CosB=(a^2+c^2-b^2)/2ac？？所以这里的计算似乎有问题
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
//使用gaussian金字塔分解对输入图像向下采样，首先对它输入的图像用指定滤波器
//进行卷积，然后通过拒绝偶数的行与列来下采样
cvPyrDown( timg, pyr, 7 );
//函数 cvPyrUp 使用Gaussian 金字塔分解对输入图像向上采样。首先通过在图像中插入 0 偶数行和偶数列，然后对得到的图像用指定的滤波器进行高斯卷积，其中滤波器乘以4做插值。所以输出图像是输入图像的 4 倍大小。
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
//函数 cvSetImageCOI 基于给定的值设置感兴趣的通道。值 0 意味着所有的通道都被选定, 1 意味着第一个通道被选定等等。
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,60, 180, 3 );
// dilate canny output to remove potential
// holes between edge segments
//使用任意结构元素膨胀图像
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 );
cvThreshold( tgray, gray, 50, 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
//用指定精度逼近多边形曲线
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
//cvContourArea 计算整个轮廓或部分轮廓的面积
//cvCheckContourConvexity测试轮廓的凸性
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[] = { "E:\\1.jpg", "E:\\2.jpg", "E:\\3.jpg",
"E:\\4.jpg", "E:\\5.jpg", 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,0 );
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;
}

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【opencv+C++】在图像中找四边形

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