本文就是通过opencv中提供的透视变换函数cv::WarpPerspective(),将左边的图像变换为右边的图像
原文网址：
具体流程为：
a)载入图像→灰度化→边缘处理得到边缘图像（edge map）
cv::Mat im = cv::imread(filename);
cv::Mat gray;
cvtColor(im,gray,CV_BGR2GRAY);
Canny(gray,gray,100,150,3);
b)霍夫变换进行直线检测，此处使用的是probabilistic Hough transform（cv::HoughLinesP）而不是standard Hough transform（cv::HoughLines）
std::vector<Vec4i> lines;
cv::HoughLinesP(gray,lines,1,CV_PI/180,70,30,10);
for(int i = 0; i < lines.size(); i++)
line(im,cv::Point(lines[i][0],lines[i][1]),cv::Point(lines[i][2],lines[i][3]),Scalar(255,0,0),2,8,0);
c)通过上面的图我们可以看出，通过霍夫变换检测到的直线并没有将整个边缘包含，但是我们要求的是四个顶点所以并不一定要直线真正的相交，下面就要求四个顶点的坐标，公式为：
| 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | cv::Point2f computeIntersect(cv::Vec4i a, cv::Vec4i b) { int x1 = a[0], y1 = a[1], x2 = a[2], y2 = a[3]; int x3 = b[0], y3 = b[1], x4 = b[2], y4 = b[3]; if ( float d = (( float )(x1-x2) * (y3-y4)) - ((y1-y2) * (x3-x4))) { cv::Point2f pt; pt.x = ((x1*y2 - y1*x2) * (x3-x4) - (x1-x2) * (x3*y4 - y3*x4)) / d; pt.y = ((x1*y2 - y1*x2) * (y3-y4) - (y1-y2) * (x3*y4 - y3*x4)) / d; return pt; } else return cv::Point2f(-1, -1); } |
| 1 2 3 4 5 6 7 8 9 10 | std::vector<cv::Point2f> corners; for ( int i = 0; i < lines.size(); i++) { for ( int j = i+1; j < lines.size(); j++) { cv::Point2f pt = computeIntersect(lines[i], lines[j]); if (pt.x >= 0 && pt.y >= 0) corners.push_back(pt); } } |
d）检查是不是四边形
| 1 2 3 4 5 6 7 8 9 | std::vector<cv::Point2f> approx; cv::approxPolyDP(cv::Mat(corners), approx, cv::arcLength(cv::Mat(corners), true ) * 0.02, true ); if (approx.size() != 4) { std::cout << "The object is not quadrilateral!" << std::endl; return -1; } |
e)确定四个顶点的具体位置（top-left, bottom-left, top-right, and bottom-right corner）→通过四个顶点求出映射矩阵来.
void sortCorners(std::vector<cv::Point2f>& corners, cv::Point2f center) { std::vector<cv::Point2f> top, bot; for ( int i = 0; i < corners.size(); i++) { if (corners[i].y < center.y) top.push_back(corners[i]); else bot.push_back(corners[i]); } cv::Point2f tl = top[0].x > top[1].x ? top[1] : top[0]; cv::Point2f tr = top[0].x > top[1].x ? top[0] : top[1]; cv::Point2f bl = bot[0].x > bot[1].x ? bot[1] : bot[0]; cv::Point2f br = bot[0].x > bot[1].x ? bot[0] : bot[1]; corners.clear(); corners.push_back(tl); corners.push_back(tr); corners.push_back(br); corners.push_back(bl); } |
下面是获得中心点坐标然后利用上面的函数确定四个顶点的坐标
for ( int i = 0; i < corners.size(); i++) center += corners[i]; center *= (1. / corners.size()); sortCorners(corners, center); |
定义目的图像并初始化为0
cv::Mat quad = cv::Mat::zeros(300, 220, CV_8UC3); |
获取目的图像的四个顶点
std::vector<cv::Point2f> dst_pt; dst.push_back(cv::Point2f(0,0)); dst.push_back(cv::Point2f(quad.cols,0)); dst.push_back(cv::Point2f(quad.cols,quad.rows)); dst.push_back(cv::Point2f(0,quad.rows)); |
计算映射矩阵
cv::Mat transmtx = cv::getPerspectiveTransform(corners, quad_pts); |
进行透视变换并显示结果
cv::warpPerspective(im, quad, transmtx, quad.size()); cv::imshow( "quadrilateral" , quad); |