How to Deskew a Set of Points Using cv::warpPerspective?

Executing cv::warpPerspective for a Fake Deskewing on a Set of cv::Point

Question: How do I achieve a deskewing effect on a set of points using cv::warpPerspective? The points are not in a particular order and are stored within a vector.

Understanding the Issue:

• Incorrect point ordering: The order of points in the input and output vectors must match to achieve the desired transformation.
• Incorrect image size: The output image should have a width and height matching the bounding rectangle of the deskewed object.

Steps for Fake Deskewing:

1. Correct Point Ordering: Ensure the order of points in both input and output vectors follows the same sequence (e.g., top-left, bottom-left, bottom-right, top-right).
2. Rotated Rectangle Adjustment: Use cv::minAreaRect() to create a rotated rectangle around the input points. However, note that this method may slightly alter the original point coordinates.
3. Affine Transform: Utilize the affine transform functions, cv::getAffineTransform() and cv::warpAffine(), as they are computationally more efficient for this specific deskewing operation.
4. Different Output Size: To have the deskewed image contain only the object of interest, define a new image size (e.g., cv::Size(width, height)) that matches the bounding rectangle size.
5. Apply Affine Transform: Pass the input image, input points, output points, and the defined output size to cv::warpAffine() to perform the actual deskewing transformation.

Example Code:

#include <opencv2/opencv.hpp>

int main() {
    // Input image
    Mat src = imread("input.jpg");

    // Input points (not in particular order)
    vector<Point> points = {
        Point(408, 69), // Top-left
        Point(72, 2186), // Bottom-left
        Point(1584, 2426), // Bottom-right
        Point(1912, 291), // Top-right
    };

    // Rotated rectangle (bounding box)
    RotatedRect boundingRect = minAreaRect(Mat(points));

    // Corrected point ordering
    Point2f vertices[3];
    vertices[0] = boundingRect.center + boundingRect.size * 0.5f; // Top-left
    vertices[1] = boundingRect.center + boundingRect.size * 0.5f; // Bottom-left
    vertices[1].y += boundingRect.size.height;
    vertices[2] = boundingRect.center - boundingRect.size * 0.5f; // Bottom-right

    // Output point ordering
    Point2f outputVertices[3];
    outputVertices[0] = Point(0, 0); // Top-left
    outputVertices[1].x = outputVertices[0].x + boundingRect.size.width; // Bottom-left
    outputVertices[1].y = outputVertices[1].x;
    outputVertices[2] = outputVertices[0]; // Bottom-right

    // Affine transformation matrix
    Mat transformationMatrix = getAffineTransform(vertices, outputVertices);

    // Deskewed image with corrected size
    Mat deskewedImage;
    Size outputSize(boundingRect.size.width, boundingRect.size.height);
    warpAffine(src, deskewedImage, transformationMatrix, outputSize, INTER_LINEAR);

    // Save deskewed image
    imwrite("deskewed.jpg", deskewedImage);
}

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