边缘检测

记录下项目中的一点东西。

//=======================================================================================
// ParkingSystem.cpp
// 
//=======================================================================================
// 5inch HDMI LCD 800x480
// DPI = sqrt(800^2 + 480^2) / 5 = 186.6 像素/英寸
// 屏幕宽 = 800 / 186.6 = 4.28 英寸 = 10.87 CM
// 屏幕高 = 480 / 186.6 = 2.57 英寸 = 6.52  CM
//
/*

x(图像中物体间距离)     X(实际中距离)
--------------------  =  -------------
f(焦距)                 D(相机到物体垂直距离)

焦距 f 取: 10 cm
相机到物体垂直距离 D 取: 50 cm

*/

#include <opencv2\opencv.hpp>
#include <iostream>
#include <string>
#include <vector>
#include <cmath>
#include <windows.h>
#include <process.h>
//#include "RaspiCamCV.h"

using namespace cv;
using namespace std;

const int CAMERA_WIDTH    = 400;
const int CAMERA_HEIGHT    = 400;
const int g_WIDTH = 400;
const int g_HEIGHT = 400;

// 像素阈值
const int THRESHOLD = 255;
// DPI
const float LCD_DPI = 186.6;
// 焦距(CM)
const int CAMERA_FOCUS = 10;
// 相机到物体垂直距离(CM)
const int CAMERA_TO_OBJECT_DISTANCE = 50;

// grobal variable
static cv::Mat g_srcImage, g_srcGrayImage, g_edge, g_dstImage;
static vector<Vec4i> g_allLines;
static Point point1, point2;
static Point VideoCenter(199, 199);

// 推荐的高低阈值比在2:1到3:1之间
const int CANNY_threshold1 = 30;
const int CANNY_threshold2 = 80;

const int HoughLines_threshold = 150;


void Image_Processing();
void DrawLine(Mat &img, Point start, Point end);
void DrawHoughLines(Mat &img);
float findDistanceBetweenPointsI(const CvPoint p1, const CvPoint p2);
float CalcuteDistance(const CvPoint point1, const CvPoint point2, const CvPoint point3);


//main
//=======================================================================================
int main()
{

    VideoCapture videoCapture(0);
    videoCapture.set(CV_CAP_PROP_FRAME_WIDTH, CAMERA_WIDTH);
    videoCapture.set(CV_CAP_PROP_FRAME_HEIGHT, CAMERA_HEIGHT);

    cvNamedWindow("window1");
    cvMoveWindow("window1", 0, 40);
    cvNamedWindow("window2");
    cvMoveWindow("window2", g_WIDTH + 1, 40);

    while (1)
    {
        Mat cameraFrame;
        videoCapture >> cameraFrame;
        if (cameraFrame.empty()) 
        {
            cerr << "ERROR: Couldn't grab the next camera frame." << endl;
            exit(1);
        }

        // Get a copy of the camera frame that we can draw onto.
        Mat displayedFrame;
        cameraFrame.copyTo(displayedFrame);
        cameraFrame.copyTo(g_srcImage);

        Image_Processing();
        Mat finalImage(g_WIDTH,g_HEIGHT, CV_8UC3, Scalar(0, 0, 0));
        DrawHoughLines(finalImage);


        // Show the camera frame on the screen.
        imshow("window1", displayedFrame);
        // Show the final frame on the screen.
        imshow("window2", finalImage);


        // IMPORTANT: Wait for atleast 20 milliseconds, so that the image can be displayed on the screen!
        // Also checks if a key was pressed in the GUI window. Note that it should be a "char" to support Linux.
        char keypress = waitKey(20);  // This is needed if you want to see anything!
        if (keypress == VK_ESCAPE) 
        {   // Escape Key
            // Quit the program!
            break;
        }

    }

    cvDestroyWindow("window1");
    cvDestroyWindow("window2");
    return 0;
}


// 图像预处理
void Image_Processing()
{
    cvtColor(g_srcImage, g_srcImage, COLOR_BGR2GRAY);;
    
    equalizeHist(g_srcImage, g_srcGrayImage);

    // 先使用 3x3内核来降噪
    blur(g_srcGrayImage, g_edge, Size(3, 3));
    // 运行Canny算子，边缘检测
    Canny(g_edge, g_edge, CANNY_threshold1, CANNY_threshold2, 3);

    // 霍夫线变换
    HoughLinesP(g_edge, g_allLines, 1, CV_PI / 180, HoughLines_threshold, 50, 10);

}

// 画直线
void DrawLine(Mat &img, Point start, Point end)
{
    int thickness = 1;
    int lineType = 8;
    // 红色，细
    line(img,
        start,
        end,
        Scalar(0, 0, 255),
        thickness,
        lineType);
}

// 画霍夫线变换后的直线
void DrawHoughLines(Mat &img)
{
    Vec4i L;
    for (size_t i = 0; i < g_allLines.size(); i++)
    {
        L = g_allLines[i];
        DrawLine(img, Point(L[0], L[1]), Point(L[2], L[3]));
    }
}

float findDistanceBetweenPointsI(const CvPoint p1, const CvPoint p2)
{
    // Calc the pythagoras distance.
    int dx = (p1.x - p2.x);
    int dy = (p1.y - p2.y);
    return sqrt((float)(dx * dx + dy * dy));
}

// 计算 point3 到由 point1和point2构成的直线距离
float CalcuteDistance(const CvPoint point1, const CvPoint point2, const CvPoint point3)
{
    float K, D;
    if (point2.x == point1.x)
    {
        return fabs(float((point3.x - point1.x)));
    }
    else if (point2.y == point1.y)
    {
        return fabs(float((point3.y - point1.y)));
    }
    else
    {
        /*

        A*x + B*y + C = 0
        d = | A*x0 + B*y0 + C | / sqrt(A^2 + B^2)

        K = (y2 - y1) / (x2 - x1)
        K*x - y + y1 - K*x1 = 0

        */
        K = (float(point2.y - point1.y) / float(point2.x - point1.x));
        D = fabs(K*point3.x - point3.y + point1.y - K*point1.x) / sqrt(K*K + 1);
        return D;
    }
}