opencv之图像区域选择（7）

た入场券 2022-05-28 11:12 211阅读 0赞

main.cpp

//暗色异物处理
    #include <stdio.h>
    #include <stdlib.h>
    #include <math.h>
    #include <vector>
    #include <opencv2/opencv.hpp>
    #include <opencv2/imgproc.hpp>
    //#include <valarray>
    //#include <numeric>
    
    using namespace cv;
    using namespace std;
    
    void Dark_detection(Mat &inputimage1, Mat &inputimage2, Mat &outputimage);
    void frame_sub(Mat &inputimage1, Mat &inputimage2, Mat &outputimage, int pos);
    
    int main()
    {
        Mat image1 = imread("1.jpg");
        Mat image2 = imread("2.jpg");
        Mat outimage;
        outimage.create(image1.rows, image1.cols, image1.type());
        Dark_detection(image1, image2, outimage);
        imshow("outimage", outimage);
    }
    
    void Dark_detection(Mat &inputimage1, Mat &inputimage2, Mat &outputimage)  //暗色异物检测
    {
        frame_sub(inputimage1, inputimage2, outputimage, 90);
    
        //寻找最外层轮廓
        vector<vector<Point>> contours;
        vector<Vec4i> hierarchy;
        findContours(outputimage, contours, hierarchy, RETR_EXTERNAL, CHAIN_APPROX_NONE, Point());
    
        Mat outputimageContours = Mat::zeros(outputimage.size(), CV_8UC1);    //最小外接矩形画布
        //怎样从二值化的输出图像中选出异物所在位置？
        for(int i = 0; i < contours.size(); i++)
        {
            drawContours(outputimageContours, contours, i, Scalar(255), 1, 8, hierarchy);   //绘制轮廓
            RotatedRect rect = minAreaRect(contours[i]);   //寻找的是异物的最小外接矩形框
            Point2f p[4];
            rect.points(p);
    
            for(int j = 0; j <= 3; j++)
            {
                //cout<<"Points are:"<<p[j]<<endl;
                line(outputimageContours, p[j], p[(j+1)%4], Scalar(255), 2);  //line:第二个参数表示直线起点，第三个表示直线终点，第四个颜色，第五个是线条粗细
            }
            //对每个矩形框内的0像素点进行同化
    
    
        }
        imshow("MinAreaRect", outputimageContours);
    }
    
    void frame_sub(Mat &inputimage1, Mat &inputimage2, Mat &outputimage, int pos)   //差分并二值化
    {
        uchar *data1 = NULL;
        uchar *data2 = NULL;
        uchar *data3 = NULL;
        int i, j;
    
        outputimage = inputimage1.clone();
        int rowNumber = outputimage.rows;
        int colNumber = outputimage.cols*outputimage.channels();
        int step = outputimage.step/sizeof(uchar);
        data1 = (uchar*)inputimage1.data;
        data2 = (uchar*)inputimage2.data;
        data3 = (uchar*)outputimage.data;
    
        for(i = 0; i < rowNumber; i++)
        {
            for(j = 0; j < colNumber; j++)
            {
                if(fabs(data2[i*step + j] - data1[i*step + j]) > pos)
                    data3[i*step + j] = 255;
                else
                    data3[i*step + j] = 0;
            }
        }
    }
    
    
    
    //直线表示
    //定义Point2f结构体
    struct Point2f
    {
        float x;
        float y;
    };
    
    //定义直线参数结构体
    struct LinePara
    {
        float k;
        float b;
    };
    
    //获取直线参数
    void getLinePara(float &x1, float &y1, float &x2, float &y2, LinePara &LP)
    {
        int m = 0;
        m = x2 - x1;
    
        if(0 == m)
        {
            LP.k = 0;
            LP.b = y1 - LP.k*x1;
        }
        else
        {
            LP.k = (y2-y1)/(x2-x1);
            LP.b = y1 - LP.k*x1;
        }
    }
    
    //获取两点的距离，判断点两侧的p1，p2分布在p的两侧
    float getLength(Point2f a, Point2f b)
    {
        float disx = a.x - b.x;
        float disy = a.x - b.x;
        float num = (disx * disx) + (disy * disy);
        return sqart(num);
    }

结果

![70][]

失败的几个例子：

1.main.cpp

#include <stdio.h>
    #include <stdlib.h>
    #include <math.h>
    #include <vector>
    #include <opencv2/opencv.hpp>
    #include <opencv2/imgproc.hpp>
    
    using namespace cv;
    using namespace std;
    
    int main()
    {
        Mat imageSource=imread("1.jpg");
        imshow("Source Image",imageSource);
        Mat image;
        blur(imageSource,image,Size(3,3));
        threshold(image,image,0,255,CV_THRESH_OTSU);
        imshow("Threshold Image",image);
    
        //寻找最外层轮廓
        vector<vector<Point>> contours;
        vector<Vec4i> hierarchy;
        findContours(image,contours,hierarchy,RETR_EXTERNAL,CHAIN_APPROX_NONE,Point());
    
        Mat imageContours=Mat::zeros(image.size(),CV_8UC1);	//最小外接矩形画布
        Mat imageContours1=Mat::zeros(image.size(),CV_8UC1); //最小外结圆画布
        for(int i=0;i<contours.size();i++)
        {
            //绘制轮廓
            drawContours(imageContours,contours,i,Scalar(255),1,8,hierarchy);
            drawContours(imageContours1,contours,i,Scalar(255),1,8,hierarchy);
    
    
            //绘制轮廓的最小外结矩形
            RotatedRect rect=minAreaRect(contours[i]);
            Point2f P[4];
            rect.points(P);
            for(int j=0;j<=3;j++)
            {
                line(imageContours,P[j],P[(j+1)%4],Scalar(255),2);
            }
    
            //绘制轮廓的最小外结圆
            Point2f center; float radius;
            minEnclosingCircle(contours[i],center,radius);
            circle(imageContours1,center,radius,Scalar(255),2);
    
        }
        imshow("MinAreaRect",imageContours);
        imshow("MinAreaCircle",imageContours1);
        waitKey(0);
        return 0;
    }

2.main.cpp

[70]: /images/20220528/1f07879f8e6a4212ab8e155581d1bb8f.png