利用霍夫变换检测直线,校正拍摄倾斜的图片
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#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;
}
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效果图如下所示:
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原文链接:https://blog.csdn.net/lly_117/article/details/79405947