OpenCV代码提取 warpPerspective函数的实现

               

 For perspective transformation, you need a 3x3 transformation matrix. Straight lines will remain straight even after the transformation. To find this transformation matrix, you need 4 points on the input image and corresponding points on the output image. Among these 4 points,3 of them should not be collinear.

 透视变换(perspective transformation)是将图像投影到一个新的视平面，也称为投影映射。

         公式：dst(x,y) = src((M11x+M12y+M13)/(M31x+M32y+M33), (M21x+M22y+M23)/(M31x+M32y+M33))

 仿射变换与透视变换的区别：

 (1)、仿射变换，它可以将矩形转换成平行四边形，也可以将矩形的边压扁但必须保持边是平行的，也可以将矩形旋转或者按比例缩放。透视变换除了能够处理仿射变换的操作外，还可以将矩形转换成梯形。即仿射变换后还是平行四边形，透视变换后是四边形。因此可以说仿射变换是透视变换的一个子集。

         (2)、在OpenCV中，基于2*3矩阵进行的变换，是图像的仿射变换；基于3*3矩阵进行的变换，是图像的透视变换或者单应性映射。图像透视变换多用于图像校正

         下图是截取的《Learning OpenCV》一书中的插图：

 目前支持uchar和float两种类型，经测试，与OpenCV3.1结果完全一致。

 实现代码warpPerspective.hpp：

// fbc_cv is free software and uses the same licence as OpenCV// Email: [email protected]#ifndef FBC_CV_WARP_PERSPECTIVE_HPP_#define FBC_CV_WARP_PERSPECTIVE_HPP_/* reference: include/opencv2/imgproc.hpp              modules/imgproc/src/imgwarp.cpp*/#include <typeinfo>#include "core/mat.hpp"#include "core/invert.hpp"#include "imgproc.hpp"#include "remap.hpp"namespace fbc {// Calculates a perspective transform from four pairs of the corresponding pointsFBC_EXPORTS int getPerspectiveTransform(const Point2f src1[], const Point2f src2[], Mat_<double, 1>& dst);// Applies a perspective transformation to an image// The function cannot operate in - place// support type: uchar/float/* \f[\texttt{ dst } (x, y) = \texttt{ src } \left(\frac{ M_{ 11 } x + M_{ 12 } y + M_{ 13 } }{M_{ 31 } x + M_{ 32 } y + M_{ 33 }}, \frac{ M_{ 21 } x + M_{ 22 } y + M_{ 23 } }{M_{ 31 } x + M_{ 32 } y + M_{ 33 }} \right)\f]*/template<typename _Tp1, typename _Tp2, int chs1, int chs2>int warpPerspective(const Mat_<_Tp1, chs1>& src, Mat_<_Tp1, chs1>& dst, const Mat_<_Tp2, chs2>& M_, int flags = INTER_LINEAR, int borderMode = BORDER_CONSTANT, const Scalar& borderValue = Scalar()){ FBC_Assert(src.data != NULL && dst.data != NULL && M_.data != NULL); FBC_Assert(src.cols > 0 && src.rows > 0 && dst.cols > 0 && dst.rows > 0); FBC_Assert(src.data != dst.data); FBC_Assert(typeid(double).name() == typeid(_Tp2).name() && M_.rows == 3 && M_.cols == 3); FBC_Assert((typeid(uchar).name() == typeid(_Tp1).name()) || (typeid(float).name() == typeid(_Tp1).name())); // uchar/float double M[9]; Mat_<double, 1> matM(3, 3, M); int interpolation = flags & INTER_MAX; if (interpolation == INTER_AREA)  interpolation = INTER_LINEAR; if (!(flags & WARP_INVERSE_MAP))  invert(M_, matM); Range range(0, dst.rows); const int BLOCK_SZ = 32; short XY[BLOCK_SZ*BLOCK_SZ * 2], A[BLOCK_SZ*BLOCK_SZ]; int x, y, x1, y1, width = dst.cols, height = dst.rows; int bh0 = std::min(BLOCK_SZ / 2, height); int bw0 = std::min(BLOCK_SZ*BLOCK_SZ / bh0, width); bh0 = std::min(BLOCK_SZ*BLOCK_SZ / bw0, height); for (y = range.start; y < range.end; y += bh0) {  for (x = 0; x < width; x += bw0) {   int bw = std::min(bw0, width - x);   int bh = std::min(bh0, range.end - y); // height   Mat_<short, 2> _XY(bh, bw, XY), matA;   Mat_<_Tp1, chs1> dpart;   dst.getROI(dpart, Rect(x, y, bw, bh));   for (y1 = 0; y1 < bh; y1++) {    short* xy = XY + y1*bw * 2;    double X0 = M[0] * x + M[1] * (y + y1) + M[2];    double Y0 = M[3] * x + M[4] * (y + y1) + M[5];    double W0 = M[6] * x + M[7] * (y + y1) + M[8];    if (interpolation == INTER_NEAREST) {     x1 = 0;     for (; x1 < bw; x1++) {      double W = W0 + M[6] * x1;      W = W ? 1. / W : 0;      double fX = std::max((double)INT_MIN, std::min((double)INT_MAX, (X0 + M[0] * x1)*W));      double fY = std::max((double)INT_MIN, std::min((double)INT_MAX, (Y0 + M[3] * x1)*W));      int X = saturate_cast<int>(fX);      int Y = saturate_cast<int>(fY);      xy[x1 * 2] = saturate_cast<short>(X);      xy[x1 * 2 + 1] = saturate_cast<short>(Y);     }    } else {     short* alpha = A + y1*bw;     x1 = 0;     for (; x1 < bw; x1++) {      double W = W0 + M[6] * x1;      W = W ? INTER_TAB_SIZE / W : 0;      double fX = std::max((double)INT_MIN, std::min((double)INT_MAX, (X0 + M[0] * x1)*W));      double fY = std::max((double)INT_MIN, std::min((double)INT_MAX, (Y0 + M[3] * x1)*W));      int X = saturate_cast<int>(fX);      int Y = saturate_cast<int>(fY);      xy[x1 * 2] = saturate_cast<short>(X >> INTER_BITS);      xy[x1 * 2 + 1] = saturate_cast<short>(Y >> INTER_BITS);      alpha[x1] = (short)((Y & (INTER_TAB_SIZE - 1))*INTER_TAB_SIZE + (X & (INTER_TAB_SIZE - 1)));     }    }   }   if (interpolation == INTER_NEAREST) {    remap(src, dpart, _XY, Mat_<float, 1>(), interpolation, borderMode, borderValue);   } else {    Mat_<ushort, 1> _matA(bh, bw, A);    remap(src, dpart, _XY, _matA, interpolation, borderMode, borderValue);   }  } } return 0;}} // namespace fbc#endif // FBC_CV_WARP_PERSPECTIVE_HPP_

 测试代码test_warpPerspective.cpp：

#include "test_warpPerspective.hpp"#include <assert.h>#include <opencv2/opencv.hpp>#include <warpPerspective.hpp>int test_getPerspectiveTransform(){ cv::Mat matSrc = cv::imread("E:/GitCode/OpenCV_Test/test_images/lena.png", 1); if (!matSrc.data) {  std::cout << "read image fail" << std::endl;  return -1; } fbc::Point2f src_vertices[4], dst_vertices[4]; src_vertices[0] = fbc::Point2f(0, 0); src_vertices[1] = fbc::Point2f(matSrc.cols - 5, 0); src_vertices[2] = fbc::Point2f(matSrc.cols - 10, matSrc.rows - 1); src_vertices[3] = fbc::Point2f(8, matSrc.rows - 13); dst_vertices[0] = fbc::Point2f(17, 21); dst_vertices[1] = fbc::Point2f(matSrc.cols - 23, 19); dst_vertices[2] = fbc::Point2f(matSrc.cols / 2 + 5, matSrc.rows / 3 + 7); dst_vertices[3] = fbc::Point2f(55, matSrc.rows / 5 + 33); fbc::Mat_<double, 1> warpMatrix(3, 3); fbc::getPerspectiveTransform(src_vertices, dst_vertices, warpMatrix); cv::Point2f src_vertices_[4], dst_vertices_[4]; src_vertices_[0] = cv::Point2f(0, 0); src_vertices_[1] = cv::Point2f(matSrc.cols - 5, 0); src_vertices_[2] = cv::Point2f(matSrc.cols - 10, matSrc.rows - 1); src_vertices_[3] = cv::Point2f(8, matSrc.rows - 13); dst_vertices_[0] = cv::Point2f(17, 21); dst_vertices_[1] = cv::Point2f(matSrc.cols - 23, 19); dst_vertices_[2] = cv::Point2f(matSrc.cols / 2 + 5, matSrc.rows / 3 + 7); dst_vertices_[3] = cv::Point2f(55, matSrc.rows / 5 + 33); cv::Mat warpMatrix_ = cv::getPerspectiveTransform(src_vertices_, dst_vertices_); assert(warpMatrix.cols == warpMatrix_.cols && warpMatrix.rows == warpMatrix_.rows); assert(warpMatrix.step == warpMatrix_.step); for (int y = 0; y < warpMatrix.rows; y++) {  const fbc::uchar* p = warpMatrix.ptr(y);  const uchar* p_ = warpMatrix_.ptr(y);  for (int x = 0; x < warpMatrix.step; x++) {   assert(p[x] == p_[x]);  } } return 0;}int test_warpPerspective_uchar(){ cv::Mat matSrc = cv::imread("E:/GitCode/OpenCV_Test/test_images/lena.png", 1); if (!matSrc.data) {  std::cout << "read image fail" << std::endl;  return -1; } for (int interpolation = 0; interpolation < 5; interpolation++) {  fbc::Point2f src_vertices[4], dst_vertices[4];  src_vertices[0] = fbc::Point2f(0, 0);  src_vertices[1] = fbc::Point2f(matSrc.cols - 5, 0);  src_vertices[2] = fbc::Point2f(matSrc.cols - 10, matSrc.rows - 1);  src_vertices[3] = fbc::Point2f(8, matSrc.rows - 13);  dst_vertices[0] = fbc::Point2f(17, 21);  dst_vertices[1] = fbc::Point2f(matSrc.cols - 23, 19);  dst_vertices[2] = fbc::Point2f(matSrc.cols / 2 + 5, matSrc.rows / 3 + 7);  dst_vertices[3] = fbc::Point2f(55, matSrc.rows / 5 + 33);  fbc::Mat_<double, 1> warpMatrix(3, 3);  fbc::getPerspectiveTransform(src_vertices, dst_vertices, warpMatrix);  fbc::Mat_<uchar, 3> mat(matSrc.rows, matSrc.cols, matSrc.data);  fbc::Mat_<uchar, 3> warp_dst;  warp_dst.zeros(mat.rows, mat.cols);  fbc::warpPerspective(mat, warp_dst, warpMatrix, interpolation);  cv::Point2f src_vertices_[4], dst_vertices_[4];  src_vertices_[0] = cv::Point2f(0, 0);  src_vertices_[1] = cv::Point2f(matSrc.cols - 5, 0);  src_vertices_[2] = cv::Point2f(matSrc.cols - 10, matSrc.rows - 1);  src_vertices_[3] = cv::Point2f(8, matSrc.rows - 13);  dst_vertices_[0] = cv::Point2f(17, 21);  dst_vertices_[1] = cv::Point2f(matSrc.cols - 23, 19);  dst_vertices_[2] = cv::Point2f(matSrc.cols / 2 + 5, matSrc.rows / 3 + 7);  dst_vertices_[3] = cv::Point2f(55, matSrc.rows / 5 + 33);  // Get the Perspective Transform  cv::Mat warpMatrix_ = cv::getPerspectiveTransform(src_vertices_, dst_vertices_);  // Set the dst image the same type and size as src  cv::Mat warp_dst_ = cv::Mat::zeros(matSrc.rows, matSrc.cols, matSrc.type());  cv::Mat mat_;  matSrc.copyTo(mat_);  // Apply the Affine Transform just found to the src image  cv::warpPerspective(mat_, warp_dst_, warpMatrix_, warp_dst_.size(), interpolation);  assert(warp_dst.cols == warp_dst_.cols && warp_dst.rows == warp_dst_.rows);  assert(warp_dst.step == warp_dst_.step);  for (int y = 0; y < warp_dst.rows; y++) {   const fbc::uchar* p = warp_dst.ptr(y);   const uchar* p_ = warp_dst_.ptr(y);   for (int x = 0; x < warp_dst.step; x++) {    assert(p[x] == p_[x]);   }  } } return 0;}int test_warpPerspective_float(){ cv::Mat matSrc = cv::imread("E:/GitCode/OpenCV_Test/test_images/lena.png", 1); if (!matSrc.data) {  std::cout << "read image fail" << std::endl;  return -1; } cv::cvtColor(matSrc, matSrc, CV_BGR2GRAY); matSrc.convertTo(matSrc, CV_32FC1); for (int interpolation = 0; interpolation < 5; interpolation++) {  fbc::Point2f src_vertices[4], dst_vertices[4];  src_vertices[0] = fbc::Point2f(0, 0);  src_vertices[1] = fbc::Point2f(matSrc.cols - 5, 0);  src_vertices[2] = fbc::Point2f(matSrc.cols - 10, matSrc.rows - 1);  src_vertices[3] = fbc::Point2f(8, matSrc.rows - 13);  dst_vertices[0] = fbc::Point2f(17, 21);  dst_vertices[1] = fbc::Point2f(matSrc.cols - 23, 19);  dst_vertices[2] = fbc::Point2f(matSrc.cols / 2 + 5, matSrc.rows / 3 + 7);  dst_vertices[3] = fbc::Point2f(55, matSrc.rows / 5 + 33);  fbc::Mat_<double, 1> warpMatrix(3, 3);  fbc::getPerspectiveTransform(src_vertices, dst_vertices, warpMatrix);  fbc::Mat_<float, 1> mat(matSrc.rows, matSrc.cols, matSrc.data);  fbc::Mat_<float, 1> warp_dst;  warp_dst.zeros(mat.rows, mat.cols);  fbc::warpPerspective(mat, warp_dst, warpMatrix, interpolation);  cv::Point2f src_vertices_[4], dst_vertices_[4];  src_vertices_[0] = cv::Point2f(0, 0);  src_vertices_[1] = cv::Point2f(matSrc.cols - 5, 0);  src_vertices_[2] = cv::Point2f(matSrc.cols - 10, matSrc.rows - 1);  src_vertices_[3] = cv::Point2f(8, matSrc.rows - 13);  dst_vertices_[0] = cv::Point2f(17, 21);  dst_vertices_[1] = cv::Point2f(matSrc.cols - 23, 19);  dst_vertices_[2] = cv::Point2f(matSrc.cols / 2 + 5, matSrc.rows / 3 + 7);  dst_vertices_[3] = cv::Point2f(55, matSrc.rows / 5 + 33);  // Get the Perspective Transform  cv::Mat warpMatrix_ = cv::getPerspectiveTransform(src_vertices_, dst_vertices_);  // Set the dst image the same type and size as src  cv::Mat warp_dst_ = cv::Mat::zeros(matSrc.rows, matSrc.cols, matSrc.type());  cv::Mat mat_;  matSrc.copyTo(mat_);  // Apply the Affine Transform just found to the src image  cv::warpPerspective(mat_, warp_dst_, warpMatrix_, warp_dst_.size(), interpolation);  assert(warp_dst.cols == warp_dst_.cols && warp_dst.rows == warp_dst_.rows);  assert(warp_dst.step == warp_dst_.step);  for (int y = 0; y < warp_dst.rows; y++) {   const fbc::uchar* p = warp_dst.ptr(y);   const uchar* p_ = warp_dst_.ptr(y);   for (int x = 0; x < warp_dst.step; x++) {    assert(p[x] == p_[x]);   }  } } return 0;}

 GitHub：https://github.com/fengbingchun/OpenCV_Test