• 图像几何变换之透视变换


    1. 基本原理

      透视变换(Perspective Transformation)的本质是将图像投影到一个新的视平面,其通用变换公式为:

      

      (u,v)为原始图像像素坐标,(x=x’/w’,y=y’/w’)为变换之后的图像像素坐标。透视变换矩阵图解如下:

      

      仿射变换(Affine Transformation)可以理解为透视变换的特殊形式。透视变换的数学表达式为:

      

      所以,给定透视变换对应的四对像素点坐标,即可求得透视变换矩阵;反之,给定透视变换矩阵,即可对图像或像素点坐标完成透视变换,如下图所示:

      

    2. OpenCV透视变换函数

    Mat getPerspectiveTransform(const Point2f* src, const Point2f* dst)
    // Calculate a perspective transform from four pairs of the corresponding points.
    // src – Coordinates of quadrangle vertices in the source image.
    // dst – Coordinates of the corresponding quadrangle vertices in the destination image.
    
    void warpPerspective(InputArray src, OutputArray dst, InputArray M, Size dsize, int flags=INTER_LINEAR, int borderMode=BORDER_CONSTANT, const Scalar& borderValue=Scalar())
    // Apply a perspective transform to an image.
    // src – Source image.
    // dst – Destination image that has the size dsize and the same type as src.
    // M – 3*3 transformation matrix.
    // dsize – Size of the destination image.
    // flags – Combination of interpolation methods and the optional flag WARP_INVERSE_MAP that means that M is the inverse transformation (dstsrc).
    // borderMode – Pixel extrapolation method. When borderMode=BORDER_TRANSPARENT, it means that the pixels in the destination image that corresponds to the “outliers” in the source image are not modified by the function.
    // borderValue – Value used in case of a constant border. By default, it is 0.
    

    3. 程序

    #include <iostream>
    
    #include "highgui.h"
    #include "opencv2/imgproc/imgproc.hpp"
    
    int main()
    {
    	// get original image.
    	cv::Mat originalImage = cv::imread("road.png");
    	
    	// perspective image.
    	cv::Mat perspectiveImage;
    	
    	// perspective transform
    	cv::Point2f objectivePoints[4], imagePoints[4];
    
    	// original image points.
    	imagePoints[0].x = 10.0; imagePoints[0].y = 457.0;
    	imagePoints[1].x = 395.0; imagePoints[1].y = 291.0;
    	imagePoints[2].x = 624.0; imagePoints[2].y = 291.0;
    	imagePoints[3].x = 1000.0; imagePoints[3].y = 457.0;
    
    	// objective points of perspective image.
    	// move up the perspective image : objectivePoints.y - value .
    	// move left the perspective image : objectivePoints.x - value.
    	double moveValueX = 0.0;
    	double moveValueY = 0.0;
    
    	objectivePoints[0].x = 46.0 + moveValueX; objectivePoints[0].y = 920.0 + moveValueY;
    	objectivePoints[1].x = 46.0 + moveValueX; objectivePoints[1].y = 100.0 + moveValueY;
    	objectivePoints[2].x = 600.0 + moveValueX; objectivePoints[2].y = 100.0 + moveValueY;
    	objectivePoints[3].x = 600.0 + moveValueX; objectivePoints[3].y = 920.0 + moveValueY;
    
    	cv::Mat transform = cv::getPerspectiveTransform(objectivePoints, imagePoints);
    
    	// perspective.
    	cv::warpPerspective(originalImage,
    		                perspectiveImage,
    						transform,
    						cv::Size(originalImage.rows, originalImage.cols),
    						cv::INTER_LINEAR | cv::WARP_INVERSE_MAP);
    
    	// cv::imshow("perspective image", perspectiveImage);
    	// cvWaitKey(0);
    
    	cv::imwrite("perspectiveImage.png", perspectiveImage);
    
    	return 0;
    }
    

      原始图像及其透视变换结果:

      

      

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  • 原文地址:https://www.cnblogs.com/liekkas0626/p/5262942.html
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