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该程序可以实现读取图片,然后将图片校正
int main()
{
Mat src = imread("30.png");
imshow("src img", src);
Mat source = src.clone();
Mat bkup = src.clone();
Mat img = src.clone();
cvtColor(img, img, CV_RGB2GRAY); //二值化
imshow("gray", img);
//equalizeHist(img, img);
//imshow("equal", img);
GaussianBlur(img, img, Size(5, 5), 0, 0); //高斯滤波
//获取自定义核
Mat element = getStructuringElement(MORPH_RECT, Size(3, 3)); //第一个参数MORPH_RECT表示矩形的卷积核,当然还可以选择椭圆形的、交叉型的
//膨胀操作
dilate(img, img, element); //实现过程中发现,适当的膨胀很重要
imshow("dilate", img);
Canny(img, img, 30, 120, 3); //边缘提取
imshow("get contour", img);
vector<vector<Point> > contours;
vector<vector<Point> > f_contours;
std::vector<cv::Point> approx2;
//注意第5个参数为CV_RETR_EXTERNAL,只检索外框
findContours(img, f_contours, CV_RETR_EXTERNAL, CV_CHAIN_APPROX_NONE); //找轮廓
//求出面积最大的轮廓
int max_area = 0;
int index;
for (int i = 0; i < f_contours.size(); i )
{
double tmparea = fabs(contourArea(f_contours[i]));
if (tmparea > max_area)
{
index = i;
max_area = tmparea;
}
}
contours.push_back(f_contours[index]);
cout << contours.size() << endl; //因为我写的是找出最外层轮廓,所以理论上只有一个轮廓
vector<Point> tmp = contours[0];
for (int line_type = 1; line_type <= 3; line_type )
{
cout << "line_type: " << line_type << endl;
Mat black = img.clone();
black.setTo(0);
drawContours(black, contours, 0, Scalar(255), line_type); //注意线的厚度,不要选择太细的
imshow("show contour", black);
std::vector<Vec4i> lines;
std::vector<cv::Point2f> corners;
std::vector<cv::Point2f> approx;
int para = 10;
int flag = 0;
int round = 0;
for (; para < 300; para )
{
cout << "round: " << round << endl;
lines.clear();
corners.clear();
approx.clear();
center = Point2f(0, 0);
cv::HoughLinesP(black, lines, 1, CV_PI / 180, para, 30, 10);
//过滤距离太近的直线
std::set<int> ErasePt;
for (int i = 0; i < lines.size(); i )
{
for (int j = i 1; j < lines.size(); j )
{
if (IsBadLine(abs(lines[i][0] - lines[j][0]), abs(lines[i][1] - lines[j][1])) && (IsBadLine(abs(lines[i][2] - lines[j][2]), abs(lines[i][3] - lines[j][3]))))
{
ErasePt.insert(j);//将该坏线加入集合
}
}
}
int Num = lines.size();
while (Num != 0)
{
std::set<int>::iterator j = ErasePt.find(Num);
if (j != ErasePt.end())
{
lines.erase(lines.begin() Num - 1);
}
Num--;
}
if (lines.size() != 4)
{
continue;
}
//计算直线的交点,保存在图像范围内的部分
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 && pt.x <= src.cols && pt.y <= src.rows) //保证交点在图像的范围之内
corners.push_back(pt);
}
}
if (corners.size() != 4)
{
continue;
}
#if 1
bool IsGoodPoints = true;
//保证点与点的距离足够大以排除错误点
for (int i = 0; i < corners.size(); i )
{
for (int j = i 1; j < corners.size(); j )
{
int distance = sqrt((corners[i].x - corners[j].x)*(corners[i].x - corners[j].x) (corners[i].y - corners[j].y)*(corners[i].y - corners[j].y));
if (distance < 5)
{
IsGoodPoints = false;
}
}
}
if (!IsGoodPoints) continue;
#endif
cv::approxPolyDP(cv::Mat(corners), approx, cv::arcLength(cv::Mat(corners), true) * 0.02, true);
if (lines.size() == 4 && corners.size() == 4 && approx.size() == 4)
{
flag = 1;
break;
}
}
// Get mass center
for (int i = 0; i < corners.size(); i )
center = corners[i];
center *= (1. / corners.size());
if (flag)
{
cout << "we found it!" << endl;
cv::circle(bkup, corners[0], 3, CV_RGB(255, 0, 0), -1);
cv::circle(bkup, corners[1], 3, CV_RGB(0, 255, 0), -1);
cv::circle(bkup, corners[2], 3, CV_RGB(0, 0, 255), -1);
cv::circle(bkup, corners[3], 3, CV_RGB(255, 255, 255), -1);
cv::circle(bkup, center, 3, CV_RGB(255, 0, 255), -1);
imshow("backup", bkup);
cout << "corners size" << corners.size() << endl;
// cv::waitKey();
// bool sort_flag = sort_corners(corners);
// if (!sort_flag) cout << "fail to sort" << endl;
sortCorners(corners, center);
cout << "corners size" << corners.size() << endl;
cout << "tl:" << corners[0] << endl;
cout << "tr:" << corners[1] << endl;
cout << "br:" << corners[2] << endl;
cout << "bl:" << corners[3] << endl;
CalcDstSize(corners);
cv::Mat quad = cv::Mat::zeros(g_dst_hight, g_dst_width, CV_8UC3);
std::vector<cv::Point2f> quad_pts;
quad_pts.push_back(cv::Point2f(0, 0));
quad_pts.push_back(cv::Point2f(quad.cols, 0));
quad_pts.push_back(cv::Point2f(quad.cols, quad.rows));
quad_pts.push_back(cv::Point2f(0, quad.rows));
cv::Mat transmtx = cv::getPerspectiveTransform(corners, quad_pts);
cv::warpPerspective(source, quad, transmtx, quad.size());
imshow("find", bkup);
cv::imshow("quadrilateral", quad);
/*如果需要二值化就解掉注释把*/
/*
Mat local,gray;
cvtColor(quad, gray, CV_RGB2GRAY);
int blockSize = 25;
int constValue = 10;
adaptiveThreshold(gray, local, 255, CV_ADAPTIVE_THRESH_MEAN_C, CV_THRESH_BINARY, blockSize, constValue);
imshow("二值化", local);
*/
cv::waitKey();
return 0;
}
}
cout << "can not transform!" << endl;
waitKey();
}