OpenCV实现倾斜文字校正

```cpp
Clicking the label of each trackbar enables editing the trackbar values manually.

@param trackbarname Name of the created trackbar.\\第一个参数为滑动条的名称
@param winname Name of the window that will be used as a parent of the created trackbar. \\ 滑动条所依附的窗口名称
@param value Optional pointer to an integer variable whose value reflects the position of the slider. Upon creation, the slider position is defined by this variable.
\\ 引用值，即拖动滑动条所改变的值，需要提前定义，定义好的值即为滑动条的初始值。
@param count Maximal position of the slider. The minimal position is always 0. \\滑动条的最大位置
@param onChange Pointer to the function to be called every time the slider changes position. This function should be prototyped as void Foo(int,void\*); , where the first parameter is the trackbar position and the second parameter is the user data (see the next parameter). If the callback is the NULL pointer, no callbacks are called, but only value is updated.
\\ 定义回调函数，每次滑动滑动条都会调用这个回调函数。回调函数的格式为 void Foo(int,void*)其中第一个参数为轨迹条的位置，第二个参数是用户数据userdata。
@param userdata User data that is passed as is to the callback. It can be used to handle trackbar events without using global variables.
\\ 用户传递给回调函数的数据userdata，这里使用的是全局变量，因此这一项可以忽略。

CV_EXPORTS int createTrackbar(const String& trackbarname, const String& winname,
                              int* value, int count,
                              TrackbarCallback onChange = 0,
                              void* userdata = 0);

### Canny边缘检测

使用Canny边缘检测算法提取文本图像的边缘

`

```cpp

CV_EXPORTS_W void Canny( InputArray image, OutputArray edges,
                         double threshold1, double threshold2,
                         int apertureSize = 3, bool L2gradient = false );

Mat src_dilate;
Mat kernel = getStructuringElement(MORPH_RECT, Size(11, 11), Point());
// 创建结构元素的大小，第一个参数为结构元素的形状（矩形MORPH_RECT,十字形结构MORPH_CROSS,椭圆形结构MORPH_ELLIPSE),第二个参数为结构元素的大小，第三个参数为锚点的位置。
dilate(Canny_edge, src_dilate, kernel, Point(-1, -1), 1, BORDER_DEFAULT);
// 膨胀图像，第一个参数为输入图像，第二个为输出图像，第三个参数为结构元素，第四个参数为锚点的位置，第五个参数为迭代的次数，最后一个参数为边界填充的类型

vector<vector<Point>> Contours;
// 定义边缘的点集
vector<Vec4i> hierarchy;
// 定义边缘的层次关系
findContours(src_dilate, Contours, hierarchy, RETR_TREE, CHAIN_APPROX_NONE, Point());

CV_EXPORTS_W void findContours( InputArray image, OutputArrayOfArrays contours,
                              OutputArray hierarchy, int mode,
                              int method, Point offset = Point());

CV_EXPORTS_W RotatedRect minAreaRect( InputArray points );

Mat Rotation = getRotationMatrix2D(center,RRect_degree,1.0);
Mat output;
warpAffine(src,output,Rotation,src.size(),INTER_CUBIC,BORDER_CONSTANT,Scalar(255,255,255));
// 输入要变换图像，输出图像，定义旋转矩阵，定义插值方式，边界类型（边界类型需要注意）

#include <iostream>
#include <opencv2/opencv.hpp>
#include <opencv2/highgui.hpp>
#include <opencv2/calib3d.hpp>

using namespace std;
using namespace cv;

// Define Mat
Mat src, gray_src, dst;
const char *IWindow = "InputWindow";
const char *OWindow = "OutputWindow";
int canny_threshold = 100;
int threshold_level = 255;

void Canny_function(int, void *);

int main(int argc, char **argv) {
    src = imread("D:/Delete/imageTextR.png");
    if (src.empty()) {
        cout << "Could not load image" << endl;
        return -1;
    }
    // Covert to GrayScale
    cvtColor(src, gray_src, COLOR_BGR2GRAY);
    namedWindow(IWindow, WINDOW_AUTOSIZE);
    imshow(IWindow, src);
    namedWindow(OWindow, WINDOW_AUTOSIZE);
    createTrackbar("Canny_Threshold", IWindow, &canny_threshold, threshold_level, Canny_function);

    waitKey();
    return 0;
}

void Canny_function(int, void *) {
    Mat Canny_edge;
    Canny(gray_src, Canny_edge, canny_threshold, canny_threshold * 2, 3, false);
    //Display Canny_edge
    //imshow(OWindow,Canny_edge);

    Mat src_dilate;
    Mat kernel = getStructuringElement(MORPH_RECT, Size(11, 11), Point());
    dilate(Canny_edge, src_dilate, kernel, Point(-1, -1), 1, BORDER_DEFAULT);
    //Display Dilate image
    imshow(OWindow,src_dilate);

    // Find Contour
    vector<vector<Point>> Contours;
    vector<Vec4i> hierarchy;
    findContours(src_dilate, Contours, hierarchy, RETR_TREE, CHAIN_APPROX_NONE, Point());

    // Select the Max area Contour
    double MaxAreaRRect = 0;
    int SizeContour = 0;
    for (size_t t = 0; t < Contours.size(); t++) {
        RotatedRect RRect = minAreaRect(Contours[t]);
        double AreaRRect = 0;
        AreaRRect = RRect.size.area();
        MaxAreaRRect = max(MaxAreaRRect, AreaRRect);
    }

    double RRect_degree = 0;
    dst = src.clone(); // 这里涉及是否复制数据的问题
    for (size_t t = 0; t < Contours.size(); t++) {
        RotatedRect RRect = minAreaRect(Contours[t]);
        double AreaRRect = RRect.size.area();
        if (AreaRRect == MaxAreaRRect ) {
            SizeContour = SizeContour + 1;
            // Rotate degree
            RRect_degree = RRect.angle;
            // Draw this rectangle
            Point2f vertex[4];
            RRect.points(vertex);
            for (int i = 0; i < 4; i++) {
                line(dst, Point(vertex[i]), Point(vertex[(i + 1) % 4]), Scalar(0, 255, 0), 2, LINE_8);
            }
        }
    }
    cout << "SizeContour : \t "<< SizeContour <<endl;
    cout << "Rotated Rectangle angle : " << RRect_degree << endl;

    //imshow(OWindow, dst);

    Point2f center(src.cols/2,src.rows/2);
    Mat Rotation = getRotationMatrix2D(center,RRect_degree,1.0);
    Mat output;
    warpAffine(src,output,Rotation,src.size(),INTER_CUBIC,BORDER_CONSTANT,Scalar(255,255,255));


    // Display Rotate Rectangle
    namedWindow("Final_Result",WINDOW_AUTOSIZE);
    imshow("Final_Result", output);


}