OpenCV圖像幾何變換之透視變換

更新時間：2021年03月19日 15:10:17 作者：liekkas0626

這篇文章主要為大家詳細介紹了OpenCV圖像幾何變換之透視變換，文中示例代碼介紹的非常詳細，具有一定的參考價值，感興趣的小伙伴們可以參考一下

本文實例為大家分享了OpenCV圖像幾何變換之透視變換的具體代碼，供大家參考，具體內容如下

1. 基本原理

透視變換（Perspective Transformation）的本質是將圖像投影到一個新的視平面，其通用變換公式為：

（u，v）為原始圖像像素坐標，（x=x'/w'，y=y'/w'）為變換之后的圖像像素坐標。透視變換矩陣圖解如下：

仿射變換（Affine Transformation）可以理解為透視變換的特殊形式。透視變換的數學表達式為：

所以，給定透視變換對應的四對像素點坐標，即可求得透視變換矩陣；反之，給定透視變換矩陣，即可對圖像或像素點坐標完成透視變換，如下圖所示：

2. OpenCV透視變換函數

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;
}

原始圖像及其透視變換結果：