1

i used a program to detect square in an image. that is working well with the image that i download from the internet. but what should i do is detect squares of the image which is taken from a camera. first of all i extracted images from video and then i try to detect square from those set of images but the code is not working for those extracted images(but that is working well with other images ). what should i do to complete that task?

#ifdef _CH_
#pragma package <opencv>
#endif

#define CV_NO_BACKWARD_COMPATIBILITY

#include <opencv2/opencv.hpp> 
#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;
//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 &&
                    cvContourArea(result,CV_WHOLE_SEQ,0) > 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 pt[4], *rect = pt;
        int count = 4;

        // read 4 vertices
        CV_READ_SEQ_ELEM( pt[0], reader );
        CV_READ_SEQ_ELEM( pt[1], reader );
        CV_READ_SEQ_ELEM( pt[2], reader );
        CV_READ_SEQ_ELEM( pt[3], 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( "Square Detection Demo", cpy );
    cvReleaseImage( &cpy );
}


//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;
    //    }
        img0 = cvLoadImage("frame_21.jpg");
        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( "qq");

        // find and draw the squares
        drawSquares( img, findSquares4( img, storage ) );

        // 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( (char)c == 27 )
            break;*/
  /*  }*/

//    cvDestroyWindow( "qq" );

    return 0;
}

This is the sample image that extracted from video -----> road sign

Thar1988
  • 511
  • 3
  • 9
  • 21

1 Answers1

1

I tested the code on different images it is working fine for all images,there is a if condition is the findsuqares4 function

                if( result->total == 4 &&
                cvContourArea(result,CV_WHOLE_SEQ,0) > 10000 &&
                cvCheckContourConvexity(result) )

The 10000 is the threshold for squares to be detected. I mean squares having area more than 10000 are detected rest all will be discarded. SO you need to change the threshold according to your requirement. I uploaded a result with threshold 100. See the result.

Squares detected

G453
  • 1,446
  • 10
  • 13
  • thank you for replying.yes i also check the code with several images that i downloaded from the internet and code is gave correct output. but the thing is i should develop a system which detect road sign.system capture video from a camera and then extracted frames from the video. i'm going to detect frames which has square shape board(probably that can be road sign or advertisement board)from those extracted images and send those frames(which has square) to other function for more works.i attached one of the extracted image to the question. are there any method to solve this problem. – Thar1988 Aug 11 '12 at 12:23