adjust corners and crop the image openCV

Question

I am using open CV,in IOS. I already detected the boundary of the paper sheet in an Image as show in image and , Now I have to drag these boundary line on touch for adjusti

Answer 1

After you got the corners you have to deskewing the paper and "extract" it to a new image.

You should do the following:

1. Sort corner points (the order matters; they must be in the same order in both vectors)
2. cv::getAffineTransform
3. cv::warpAffine

I wrote myself a helper function, which takes a std::vector with four cv::Point in it and sorts them in clockwise order beginning in the upper left. For more information on this topic take a look at these thread:

• Sort points in clockwise order?
• Sort Four Points in Clockwise Order
• Sorting of Points in 2D space

Another thing you should take into account is the size of the paper you want to extract. In my example I assume you're extracting a DIN A4 paper (210x297mm). Feel free to edit paperWidth and paperHeight inside my code.

Combining everything looks like this:

// Helper
cv::Point getCenter( std::vector<cv::Point> points ) {

    cv::Point center = cv::Point( 0.0, 0.0 );

    for( size_t i = 0; i < points.size(); i++ ) {
        center.x += points[ i ].x;
        center.y += points[ i ].y;
    }

    center.x = center.x / points.size();
    center.y = center.y / points.size();

    return center;

}

// Helper;
// 0----1
// |    |
// |    |
// 3----2
std::vector<cv::Point> sortSquarePointsClockwise( std::vector<cv::Point> square ) {

    cv::Point center = getCenter( square );

    std::vector<cv::Point> sorted_square;
    for( size_t i = 0; i < square.size(); i++ ) {
        if ( (square[i].x - center.x) < 0 && (square[i].y - center.y) < 0 ) {
            switch( i ) {
                case 0:
                    sorted_square = square;
                    break;
                case 1:
                    sorted_square.push_back( square[1] );
                    sorted_square.push_back( square[2] );
                    sorted_square.push_back( square[3] );
                    sorted_square.push_back( square[0] );
                    break;
                case 2:
                    sorted_square.push_back( square[2] );
                    sorted_square.push_back( square[3] );
                    sorted_square.push_back( square[0] );
                    sorted_square.push_back( square[1] );
                    break;
                case 3:
                    sorted_square.push_back( square[3] );
                    sorted_square.push_back( square[0] );
                    sorted_square.push_back( square[1] );
                    sorted_square.push_back( square[2] );
                    break;
            }
            break;
        }
    }

    return sorted_square;

}

// Helper
float distanceBetweenPoints( cv::Point p1, cv::Point p2 ) {

    if( p1.x == p2.x ) {
        return abs( p2.y - p1.y );
    }
    else if( p1.y == p2.y ) {
        return abs( p2.x - p1.x );
    }
    else {
        float dx = p2.x - p1.x;
        float dy = p2.y - p1.y;
        return sqrt( (dx*dx)+(dy*dy) );
    }
}

cv::Mat getPaperAreaFromImage( cv::Mat image, std::vector<cv::Point> square )
{

    // declare used vars
    int paperWidth  = 210; // in mm, because scale factor is taken into account
    int paperHeight = 297; // in mm, because scale factor is taken into account
    cv::Point2f imageVertices[4];
    float distanceP1P2;
    float distanceP1P3;
    BOOL isLandscape = true;
    int scaleFactor;
    cv::Mat paperImage;
    cv::Mat paperImageCorrected;
    cv::Point2f paperVertices[4];

    // sort square corners for further operations
    square = sortSquarePointsClockwise( square );

    // rearrange to get proper order for getPerspectiveTransform()
    imageVertices[0] = square[0];
    imageVertices[1] = square[1];
    imageVertices[2] = square[3];
    imageVertices[3] = square[2];

    // get distance between corner points for further operations
    distanceP1P2 = distanceBetweenPoints( imageVertices[0], imageVertices[1] );
    distanceP1P3 = distanceBetweenPoints( imageVertices[0], imageVertices[2] );

    // calc paper, paperVertices; take orientation into account
    if ( distanceP1P2 > distanceP1P3 ) {
        scaleFactor =  ceil( lroundf(distanceP1P2/paperHeight) ); // we always want to scale the image down to maintain the best quality possible
        paperImage = cv::Mat( paperWidth*scaleFactor, paperHeight*scaleFactor, CV_8UC3 );
        paperVertices[0] = cv::Point( 0, 0 );
        paperVertices[1] = cv::Point( paperHeight*scaleFactor, 0 );
        paperVertices[2] = cv::Point( 0, paperWidth*scaleFactor );
        paperVertices[3] = cv::Point( paperHeight*scaleFactor, paperWidth*scaleFactor );
    }
    else {
        isLandscape = false;
        scaleFactor =  ceil( lroundf(distanceP1P3/paperHeight) ); // we always want to scale the image down to maintain the best quality possible
        paperImage = cv::Mat( paperHeight*scaleFactor, paperWidth*scaleFactor, CV_8UC3 );
        paperVertices[0] = cv::Point( 0, 0 );
        paperVertices[1] = cv::Point( paperWidth*scaleFactor, 0 );
        paperVertices[2] = cv::Point( 0, paperHeight*scaleFactor );
        paperVertices[3] = cv::Point( paperWidth*scaleFactor, paperHeight*scaleFactor );
    }

    cv::Mat warpMatrix = getPerspectiveTransform( imageVertices, paperVertices );
    cv::warpPerspective(_image, paperImage, warpMatrix, paperImage.size(), cv::INTER_LINEAR, cv::BORDER_CONSTANT );

    // we want portrait output
    if ( isLandscape ) {
        cv::transpose(paperImage, paperImageCorrected);
        cv::flip(paperImageCorrected, paperImageCorrected, 1);
        return paperImageCorrected;
    }

    return paperImage;

}

Usage:

// ... get paper square ...

cv::Mat paperImage = getPaperAreaFromImage( srcImage, paperSquare );

Answer 2

What you should do is :

1. Feed the 4 corners that you have found and the 4 real corners of the image to cv::getPerspectiveTransform. It will give you a matrix of the perspective transformation that will warp the quadrangle to the whole image.

2. Use cv::WarpPerspective to create the image you want.

The links will take you to the documentation.

EDIT : You could use cv::findHomography to do step 1. But this is more about having a lot of corresponding points and outliers.

EDIT : Here is an example. It is with the C interface but you could easily make it to work with the c++

#include <stdio.h>
#include "highgui.h"
#include "cv.h"

int main( int argc, char** argv ) {
    // cvLoadImage determines an image type and creates datastructure with appropriate size
    IplImage* img = cvLoadImage( argv[1], CV_LOAD_IMAGE_COLOR);
    IplImage* img1 = cvCreateImage(
            cvSize(img->width, img->height),
            img->depth,
            img->nChannels
            );

    cvNamedWindow( "out", CV_WINDOW_AUTOSIZE );
    cvShowImage( "out", img1 );
    // create a window. Window name is determined by a supplied argument
    cvNamedWindow( argv[1], CV_WINDOW_AUTOSIZE );
    // Display an image inside and window. Window name is determined by a supplied argument
    cvShowImage( argv[1], img );

    // The part you need
    // Here is the points that you take the image from (the small quadrangle)
    CvPoint2D32f first[4] = {
      {0,0},
      {(img->width /4)* 3, img->height /4    },
      { img->width /4    ,(img->height /4) *3},
      {(img->width /4)* 3,(img->height /4) *3},
    };
    // Here are the points that you draw the quadrangle into (the four corners)
    CvPoint2D32f second[4] = {
      {0,0},
      {img->width,0},
      {0,img->height},
      {img->width,img->height}
    };
    // The part you need
    CvMat *transform = cvCreateMat(3,3, CV_32F);
    cvGetPerspectiveTransform(first,second, transform);
    cvWarpPerspective(img, img1, transform, CV_INTER_LINEAR+CV_WARP_FILL_OUTLIERS,
        cvScalarAll(0));
    // End of part you need

    cvShowImage( "out", img1 );


    // wait indefinitely for keystroke
    cvWaitKey(0);
    // release pointer to an object
    cvReleaseImage( &img );
    // Destroy a window
    cvDestroyWindow( argv[1] );
}

You should replace the array first with end points of the quadrangle you have found.

EDIT : Here are some samples. I haven't looked them very well.

Geometric Image Transformations

cvGetPerspectiveTransform