opencv利用霍夫变换检测直线进行图片校正

#include<opencv2/opencv.hpp>#include <iostream>using namespace cv;using namespace std;#define ERROR 1234//度数转换double DegreeTrans(double theta){ double res = theta / CV_PI * 180; return res;}//逆时针旋转图像degree角度（原尺寸） void rotateImage(Mat src, Mat& img_rotate, double degree){ //旋转中心为图像中心  Point2f center; center.x = float(src.cols / 2.0); center.y = float(src.rows / 2.0); int length = 0; length = sqrt(src.cols*src.cols + src.rows*src.rows); //计算二维旋转的仿射变换矩阵  Mat M = getRotationMatrix2D(center, degree, 1); warpAffine(src, img_rotate, M, Size(length, length), 1, 0, Scalar(255, 255, 255));//仿射变换，背景色填充为白色 }//通过霍夫变换计算角度double CalcDegree(const Mat &srcImage, Mat &dst){ Mat midImage, dstImage; Canny(srcImage, midImage, 50, 200, 3); cvtColor(midImage, dstImage, CV_GRAY2BGR); //通过霍夫变换检测直线 vector<Vec2f> lines; HoughLines(midImage, lines, 1, CV_PI / 180, 300, 0, 0);//第5个参数就是阈值，阈值越大，检测精度越高 //cout << lines.size() << endl; //由于图像不同，阈值不好设定，因为阈值设定过高导致无法检测直线，阈值过低直线太多，速度很慢 //所以根据阈值由大到小设置了三个阈值，如果经过大量试验后，可以固定一个适合的阈值。 if (!lines.size()) {  HoughLines(midImage, lines, 1, CV_PI / 180, 200, 0, 0); } //cout << lines.size() << endl; if (!lines.size()) {  HoughLines(midImage, lines, 1, CV_PI / 180, 150, 0, 0); } //cout << lines.size() << endl; if (!lines.size()) {  cout << "没有检测到直线！" << endl;  return ERROR; } float sum = 0; //依次画出每条线段 for (size_t i = 0; i < lines.size(); i++) {  float rho = lines[i][0];  float theta = lines[i][1];  Point pt1, pt2;  //cout << theta << endl;  double a = cos(theta), b = sin(theta);  double x0 = a*rho, y0 = b*rho;  pt1.x = cvRound(x0 + 1000 * (-b));  pt1.y = cvRound(y0 + 1000 * (a));  pt2.x = cvRound(x0 - 1000 * (-b));  pt2.y = cvRound(y0 - 1000 * (a));  //只选角度最小的作为旋转角度  sum += theta;  line(dstImage, pt1, pt2, Scalar(55, 100, 195), 1, CV_AA); //Scalar函数用于调节线段颜色  imshow("直线探测效果图", dstImage); } float average = sum / lines.size(); //对所有角度求平均，这样做旋转效果会更好 cout << "average theta:" << average << endl; double angle = DegreeTrans(average) - 90; rotateImage(dstImage, dst, angle); //imshow("直线探测效果图2", dstImage); return angle;}void ImageRecify(const char* pInFileName, const char* pOutFileName){ double degree; Mat src = imread(pInFileName); imshow("原始图", src); int srcWidth, srcHight; srcWidth = src.cols; srcHight = src.rows; cout << srcWidth << " " << srcHight << endl; Mat dst; src.copyTo(dst); //倾斜角度矫正 degree = CalcDegree(src, dst); if (degree == ERROR) {  cout << "矫正失败！" << endl;  return; } rotateImage(src, dst, degree); cout << "angle:" << degree << endl; imshow("旋转调整后", dst); Mat resulyImage = dst(Rect(0, 0, srcWidth, srcHight)); //根据先验知识，估计好文本的长宽，再裁剪下来 imshow("裁剪之后", resulyImage); imwrite("recified.jpg", resulyImage);}int main(){ ImageRecify("jiao.jpg", "FinalImage.jpg"); waitKey(); return 0;}