这篇文章主要为大家展示了“OpenCV图像几何变换之透视变换的示例分析”，内容简而易懂，条理清晰，希望能够帮助大家解决疑惑，下面让小编带领大家一起研究并学习一下“OpenCV图像几何变换之透视变换的示例分析”这篇文章吧。
创新互联于2013年创立，是专业互联网技术服务公司，拥有项目网站制作、成都网站制作网站策划，项目实施与项目整合能力。我们以让每一个梦想脱颖而出为使命，1280元桂平做网站,已为上家服务,为桂平各地企业和个人服务,联系电话:18982081108
本文实例为大家分享了OpenCV图像几何变换之透视变换的具体代码，供大家参考，具体内容如下
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 (dstsrc). // 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#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：
以上是“OpenCV图像几何变换之透视变换的示例分析”这篇文章的所有内容，感谢各位的阅读！相信大家都有了一定的了解，希望分享的内容对大家有所帮助，如果还想学习更多知识，欢迎关注创新互联行业资讯频道！
