OpenCV: chessboard corners detection Test

OpenCV 함수 cvFindChessboardCorners()와 cvDrawChessboardCorners() 사용

bool findChessboardCorners(const Mat& image, Size patternSize, vector<Point2f>& corners, int flags=CV_CALIB_CB_ADAPTIVE_THRESH+ CV_CALIB_CB_NORMALIZE_IMAGE)¶

Finds the positions of the internal corners of the chessboard.

Parameters:

image – Source chessboard view; it must be an 8-bit grayscale or color image patternSize – The number of inner corners per chessboard row and column ( patternSize = cvSize(points _ per _ row,points _ per _ colum) = cvSize(columns,rows) ) corners – The output array of corners detected flags – Various operation flags, can be 0 or a combination of the following values: CV_CALIB_CB_ADAPTIVE_THRESH use adaptive thresholding to convert the image to black and white, rather than a fixed threshold level (computed from the average image brightness). CV_CALIB_CB_NORMALIZE_IMAGE normalize the image gamma with EqualizeHist before applying fixed or adaptive thresholding. CV_CALIB_CB_FILTER_QUADS use additional criteria (like contour area, perimeter, square-like shape) to filter out false quads that are extracted at the contour retrieval stage.

file:///Users/lym/opencv/src/cv/cvcalibinit.cpp

cvcalibinit.cpp

https://code.ros.org/trac/opencv/browser/tags/2.1/opencv/src/cv/cvcalibinit.cpp

void drawChessboardCorners(Mat& image, Size patternSize, const Mat& corners, bool patternWasFound)¶

Renders the detected chessboard corners.

Parameters:	image – The destination image; it must be an 8-bit color image patternSize – The number of inner corners per chessboard row and column. (patternSize = cvSize(points _ per _ row,points _ per _ colum) = cvSize(columns,rows) ) corners – The array of corners detected patternWasFound – Indicates whether the complete board was found or not . One may just pass the return value FindChessboardCorners her

Learning OpenCV: Chapter 11. Camera Models and Calibration: Chessboards
381p

640x480

console:

finding chessboard corners...
what = 1
chessboard corners: 215.5, 179
#0=(215.5, 179)    #1=(237.5, 178.5)    #2=(260.5, 178)    #3=(283.5, 177.5)    #4=(307, 177)    #5=(331.5, 175.5)    #6=(355.5, 174.5)    #7=(380.5, 174)    #8=(405.5, 173.5)    #9=(430.5, 172.5)    #10=(212.5, 201.5)    #11=(235.5, 201.5)    #12=(258, 200.5)    #13=(280.5, 200.5)    #14=(305.5, 199.5)    #15=(330, 198.5)    #16=(354.5, 198)    #17=(379.5, 197.5)    #18=(405.5, 196.5)    #19=(430.5, 196)    #20=(210, 224.5)    #21=(232.5, 224.5)    #22=(256, 223.5)    #23=(280, 224)    #24=(304, 223)    #25=(328.5, 222.5)    #26=(353.5, 222)    #27=(378.5, 221.5)    #28=(404.5, 221.5)    #29=(430.5, 220.5)    #30=(207, 247.5)    #31=(230.5, 247.5)    #32=(253.5, 247.5)    #33=(277.5, 247)    #34=(303, 247)    #35=(327, 246.5)    #36=(352, 246.5)    #37=(377.5, 246)    #38=(403.5, 245.5)    #39=(430, 245.5)    #40=(204.5, 271.5)    #41=(227.5, 271.5)    #42=(251.5, 271.5)    #43=(275.5, 271.5)    #44=(300, 272)    #45=(325.5, 271.5)    #46=(351, 271)    #47=(376.5, 271.5)    #48=(403, 271.5)    #49=(429.5, 271)    #50=(201.5, 295.5)    #51=(225.5, 295.5)    #52=(249.5, 296)    #53=(273.5, 296.5)    #54=(299, 297)    #55=(324, 296)    #56=(349.5, 296.5)    #57=(375.5, 296.5)    #58=(402.5, 296.5)    #59=(429, 297)   

finished

finding chessboard corners...
what = 0
chessboard corners: 0, 0
#0=(0, 0)    #1=(0, 0)    #2=(0, 0)    #3=(0, 0)    #4=(0, 0)    #5=(0, 0)    #6=(0, 0)    #7=(0, 0)    #8=(0, 0)    #9=(0, 0)    #10=(0, 0)    #11=(0, 0)    #12=(0, 0)    #13=(0, 0)    #14=(0, 0)    #15=(0, 0)    #16=(0, 0)    #17=(0, 0)    #18=(0, 0)    #19=(0, 0)    #20=(0, 0)    #21=(0, 0)    #22=(0, 0)    #23=(0, 0)    #24=(0, -2.22837e-29)    #25=(-2.22809e-29, -1.99967)    #26=(4.2039e-45, -2.22837e-29)    #27=(-2.22809e-29, -1.99968)    #28=(4.2039e-45, 1.17709e-43)    #29=(6.72623e-44, 1.80347e-42)    #30=(0, 0)    #31=(4.2039e-45, 1.45034e-42)    #32=(-2.2373e-29, -1.99967)    #33=(4.2039e-45, 2.52094e-42)    #34=(-2.2373e-29, -1.99969)    #35=(-2.22634e-29, -1.99968)    #36=(4.2039e-45, 1.17709e-43)    #37=(6.72623e-44, 1.80347e-42)    #38=(0, 0)    #39=(0, 1.80347e-42)    #40=(3.36312e-44, 5.46787e-42)    #41=(6.45718e-42, 5.04467e-44)    #42=(0, 1.80347e-42)    #43=(6.48101e-42, 5.48188e-42)    #44=(0, 1.4013e-45)    #45=(4.2039e-45, 0)    #46=(1.12104e-44, -2.22837e-29)    #47=(-2.22809e-29, -1.99969)    #48=(4.2039e-45, 6.72623e-44)    #49=(6.16571e-44, 1.80347e-42)    #50=(0, 0)    #51=(1.4013e-45, -2.27113e-29)    #52=(4.56823e-42, -1.99969)    #53=(4.2039e-45, -2.20899e-29)    #54=(-2.2373e-29, -1.9997)    #55=(-2.22619e-29, -1.99969)    #56=(4.2039e-45, 6.72623e-44)    #57=(-1.9997, 1.80347e-42)    #58=(0, -2.22957e-29)    #59=(-2.23655e-29, -2.20881e-29)   

finished

finding chessboard corners...
what = 0
chessboard corners: 0, 0
#0=(0, 0)    #1=(0, 0)    #2=(0, 0)    #3=(0, 0)    #4=(0, 0)    #5=(0, 0)    #6=(0, 0)    #7=(0, 0)    #8=(0, 0)    #9=(0, 0)    #10=(0, 0)    #11=(0, 0)    #12=(0, 0)    #13=(0, 0)    #14=(0, 0)    #15=(0, 0)    #16=(0, 0)    #17=(0, 0)    #18=(0, 0)    #19=(0, 0)    #20=(0, 0)    #21=(0, 0)    #22=(0, 0)    #23=(0, 0)    #24=(0, -2.22837e-29)    #25=(-2.22809e-29, -1.99967)    #26=(4.2039e-45, -2.22837e-29)    #27=(-2.22809e-29, -1.99968)    #28=(4.2039e-45, 1.17709e-43)    #29=(6.72623e-44, 1.80347e-42)    #30=(0, 0)    #31=(4.2039e-45, 1.45034e-42)    #32=(-2.2373e-29, -1.99967)    #33=(4.2039e-45, 2.52094e-42)    #34=(-2.2373e-29, -1.99969)    #35=(-2.22634e-29, -1.99968)    #36=(4.2039e-45, 1.17709e-43)    #37=(6.72623e-44, 1.80347e-42)    #38=(0, 0)    #39=(0, 1.80347e-42)    #40=(3.36312e-44, 5.46787e-42)    #41=(6.45718e-42, 5.04467e-44)    #42=(0, 1.80347e-42)    #43=(6.48101e-42, 5.48188e-42)    #44=(0, 1.4013e-45)    #45=(4.2039e-45, 0)    #46=(1.12104e-44, -2.22837e-29)    #47=(-2.22809e-29, -1.99969)    #48=(4.2039e-45, 6.72623e-44)    #49=(6.16571e-44, 1.80347e-42)    #50=(0, 0)    #51=(1.4013e-45, -2.27113e-29)    #52=(4.56823e-42, -1.99969)    #53=(4.2039e-45, -2.20899e-29)    #54=(-2.2373e-29, -1.9997)    #55=(-2.22619e-29, -1.99969)    #56=(4.2039e-45, 6.72623e-44)    #57=(-1.9997, 1.80347e-42)    #58=(0, -2.22957e-29)    #59=(-2.23655e-29, -2.20881e-29)   

finished

source code:

// Test: chessboard detection

#include <OpenCV/OpenCV.h> // frameworks on mac
//#include <cv.h>
//#include <highgui.h>

#include <iostream>
using namespace std;


int main()
{

    IplImage* image = cvLoadImage( "DSCN3310.jpg", 1 );
   
/*    IplImage* image = 0;
    // initialize capture from a camera
    CvCapture* capture = cvCaptureFromCAM(0); // capture from video device #0
    cvNamedWindow("camera");
                
    while(1) {
        if ( !cvGrabFrame(capture) ){
            printf("Could not grab a frame\n\7");
            exit(0);
        }
        else {
            cvGrabFrame( capture ); // capture a frame
            image = cvRetrieveFrame(capture); // retrieve the captured frame
*/           
//            cvShowImage( "camera", image );
            cvNamedWindow( "camera" );  cvShowImage( "camera", image );
   
            cout << endl << "finding chessboard corners..." << endl;
            CvPoint2D32f corners[60];
            int numCorners[60];
            //cvFindChessboardCorners(<#const void * image#>, <#CvSize pattern_size#>, <#CvPoint2D32f * corners#>, <#int * corner_count#>, <#int flags#>)
            int what = cvFindChessboardCorners( image, cvSize(10,6), corners, numCorners, CV_CALIB_CB_ADAPTIVE_THRESH );
            cout << "what = " << what << endl;
            cout << "chessboard corners: " << corners[0].x << ", " << corners[0].y << endl;            
       
    for( int n = 0; n < 60; n++ )
    {
        cout << "#" << n << "=(" << corners[n].x << ", " << corners[n].y << ")\t";
    }
    cout << endl;
       
            // cvDrawChessboardCorners(<#CvArr * image#>, <#CvSize pattern_size#>, <#CvPoint2D32f * corners#>, <#int count#>, <#int pattern_was_found#>)
    cvDrawChessboardCorners( image, cvSize(10,6), corners, 60, what );   
   
   
    cvNamedWindow( "chessboard" ); cvMoveWindow( "chessboard", 200, 200 ); cvShowImage( "chessboard", image );
    cvSaveImage( "chessboard.bmp", image );       
            cvWaitKey(0);
//        }
//    }
   
    cout << endl << "finished" << endl;
//   cvReleaseCapture( &capture ); // release the capture source
    cvDestroyAllWindows();
   
    return 0;
}