opencv检测图像直线

#include<opencv2/opencv.hpp>
#include<iostream>
using namespace std;
using namespace cv;
Mat src, dst;
int main(void) {
src = imread("..\\lineDetect.jpg");
if (src.empty()) {
cout << "Loading image failed!" << endl;
return -;
} //图片大小不合适，先对图片进行缩放
resize(src, src, Size(src.rows/, src.cols/));
imshow("Sources image", src);
//图片的方向不对，用仿射变换调整至正确位置
//图片需要逆时针旋转90度
double angel = ;
Point center = Point(src.cols/,src.rows/);
//由于仿射变换后导致图像不全，用下面方法解决
Rect mask = RotatedRect(center, Size(src.cols,src.rows), angel).boundingRect();
//对仿射中心进行调整
Mat h = getRotationMatrix2D(center, angel, );
h.at<double>(, ) += mask.width / - center.x;
h.at<double>(, ) += mask.height / - center.y;
//获取仿射矩阵
Mat temp;
warpAffine(src, temp, h ,Size(src.rows,src.cols),,,Scalar(,,));
copyTo(temp, dst, Mat()); Mat gray;
cvtColor(temp, gray, COLOR_BGR2GRAY);
//反向二值化图像
Mat binary;
threshold(gray, binary, ,, THRESH_BINARY_INV);
//通过开操作消除文字，保留直线
Mat kernel = getStructuringElement(MORPH_RECT, Size(, ));
morphologyEx(binary, binary, MORPH_OPEN, kernel);
//通过膨胀操作使直线更明显
Mat kernel1 = getStructuringElement(MORPH_RECT, Size(, ));
dilate(binary, binary, kernel1);
//imshow("temp image",binary);
//霍夫直线检测
vector<Vec4f> linesPoint;
HoughLinesP(binary, linesPoint, , CV_PI / , , , );
for (int i = ; i < linesPoint.size(); i++){
line(dst, Point(linesPoint[i][], linesPoint[i][]), Point(linesPoint[i][], linesPoint[i][]), Scalar(,,), );
}
imshow("Object image", dst);
waitKey();
return ;
}