OpenCV通過透視變換實現矯正圖像詳解

1、概述

案例:使用OpenCV將一張折射的圖片給矯正過來

實現步驟:

1.載入圖像

2.圖像灰度化

3.二值分割

4.形態學操作去除噪點

5.輪廓發現

6.使用霍夫直線檢測,檢測上下左右四條直線(有可能是多條,但是無所謂)

7.繪制出直線

8.尋找與定位上下左右是條直線

9.擬合四條直線方程

10.計算四條直線的交點,ps:這四個交點其實就是我們最終要尋找的,用於透視變換使用的

11.進行透視變換

12.輸出透視變換的結果

說明:

解釋一下為啥是上面那些步驟。

1.其實我們的最終目的是通過透視矩陣getPerspectiveTransform+透視變換warpPerspective來完成圖像的矯正

2.但是getPerspectiveTransform需要兩個參數,輸入矩陣參數和目標矩陣參數。

3.由於輸入矩陣參數就是原圖像是個角的頂點,由於我們沒有所以要求出來

4.所以我們以上的所有步驟都是為11、12步打基礎的

ps:核心就是利用透視矩陣做透視變換

重點:

1.直線方程y=kx+c

2.如果兩條直線有交點,則必有k1x1+c1=k2x2+c2

2、代碼演示

//【1】載入圖像
    Mat src = imread(filePath);
    if(src.empty()){
        qDebug()<<"圖片為空";
        return;
    }
    imshow("src",src);
 
    //【2】圖像灰度化
    Mat gray;
    cvtColor(src,gray,COLOR_BGR2GRAY);
    //【3】執行二值分割
    threshold(gray,gray,0,255,THRESH_BINARY_INV|THRESH_OTSU);
    imshow("threshold",gray);
    //【4】執行形態學開操作去除圖像中的造點
    Mat kernel = getStructuringElement(MORPH_RECT,Size(5,5),Point(-1,-1));
    morphologyEx(gray,gray,MORPH_CLOSE,kernel,Point(-1,-1),3);
    imshow("morphologyEx",gray);
    //【5】輪廓發現
    bitwise_not(gray,gray);
    imshow("bitwise_not",gray);
 
    vector<vector<Point>> contours;
    vector<Vec4i> hier;
    RNG rng(12345);
    findContours(gray,contours,hier,RETR_TREE,CHAIN_APPROX_SIMPLE);
    Mat colorImage = Mat::zeros(gray.size(),CV_8UC3);
    for(size_t i = 0;i<contours.size();i++){
        Rect rect = boundingRect(contours[i]);
        //過濾目標輪廓
        if(rect.width<src.cols-5&&rect.height<src.rows-5&&rect.width>src.cols/2){
            drawContours(colorImage,contours,i,Scalar(rng.uniform(0,255),rng.uniform(0,255),rng.uniform(0,255)),1);
        }
 
    }
    imshow("findContours",colorImage);
 
    //【6】使用霍夫直線檢測
    vector<Vec4i> lines;
    cvtColor(colorImage,colorImage,COLOR_BGR2GRAY);
    kernel = getStructuringElement(MORPH_RECT,Size(3,3),Point(-1,-1));
    dilate(colorImage,colorImage,kernel,Point(-1,-1),1);
    imshow("colorImage_gray",colorImage);
    int accu = min(src.cols*0.5, src.rows*0.5);
    HoughLinesP(colorImage,lines,1,CV_PI/180,accu,accu,0);
    //【7】繪制出直線
    Mat lineColorImage = Mat::zeros(gray.size(),CV_8UC3);
    qDebug()<<"line count:"<<lines.size();
    for(size_t i = 0;i<lines.size();i++){
        Vec4i ll = lines[i];
        line(lineColorImage,Point(ll[0],ll[1]),Point(ll[2],ll[3]),Scalar(rng.uniform(0,255),rng.uniform(0,255),rng.uniform(0,255)),2,LINE_8);
    }
    imshow("lines",lineColorImage);
 
 
    //【8】尋找與定位上下左右四條直線
    int deltah  = 0;
    int width = src.cols;
    int height = src.rows;
    Vec4i topLine, bottomLine;
    Vec4i leftLine, rightLine;
    for(size_t i=0;i<lines.size();i++){
        Vec4i ln = lines[i];
        deltah  = abs(ln[3]-ln[1]);//直線高度
        if (ln[3] < height / 2.0 && ln[1] < height / 2.0 && deltah < accu - 1) {
            if (topLine[3] > ln[3] && topLine[3]>0) {
                topLine = lines[i];
            } else {
                topLine = lines[i];
            }
        }
        if (ln[3] > height / 2.0 && ln[1] > height / 2.0 && deltah < accu - 1) {
            bottomLine = lines[i];
        }
        if (ln[0] < width / 2.0 && ln[2] < width/2.0) {
            leftLine = lines[i];
        }
        if (ln[0] > width / 2.0 && ln[2] > width / 2.0) {
            rightLine = lines[i];
        }
    }
 
    //直線方程y=kx+c
    // 【9】擬合四條直線方程
    float k1, c1;
    k1 = float(topLine[3] - topLine[1]) / float(topLine[2] - topLine[0]);
    c1 = topLine[1] - k1*topLine[0];
    float k2, c2;
    k2 = float(bottomLine[3] - bottomLine[1]) / float(bottomLine[2] - bottomLine[0]);
    c2 = bottomLine[1] - k2*bottomLine[0];
    float k3, c3;
    k3 = float(leftLine[3] - leftLine[1]) / float(leftLine[2] - leftLine[0]);
    c3 = leftLine[1] - k3*leftLine[0];
    float k4, c4;
    k4 = float(rightLine[3] - rightLine[1]) / float(rightLine[2] - rightLine[0]);
    c4 = rightLine[1] - k4*rightLine[0];
 
    // 【10】四條直線交點,其實最終的目的就是找這是條直線的交點
    Point p1; // 左上角
    p1.x = static_cast<int>((c1 - c3) / (k3 - k1));
    p1.y = static_cast<int>(k1*p1.x + c1);
    Point p2; // 右上角
    p2.x = static_cast<int>((c1 - c4) / (k4 - k1));
    p2.y = static_cast<int>(k1*p2.x + c1);
    Point p3; // 左下角
    p3.x = static_cast<int>((c2 - c3) / (k3 - k2));
    p3.y = static_cast<int>(k2*p3.x + c2);
    Point p4; // 右下角
    p4.x = static_cast<int>((c2 - c4) / (k4 - k2));
    p4.y = static_cast<int>(k2*p4.x + c2);
 
    // 顯示四個點坐標
    circle(lineColorImage, p1, 2, Scalar(255, 0, 0), 2, 8, 0);
    circle(lineColorImage, p2, 2, Scalar(255, 0, 0), 2, 8, 0);
    circle(lineColorImage, p3, 2, Scalar(255, 0, 0), 2, 8, 0);
    circle(lineColorImage, p4, 2, Scalar(255, 0, 0), 2, 8, 0);
    line(lineColorImage, Point(topLine[0], topLine[1]), Point(topLine[2], topLine[3]), Scalar(0, 255, 0), 2, 8, 0);
    imshow("four corners", lineColorImage);
 
    // 【11】透視變換
    vector<Point2f> src_corners(4);
    src_corners[0] = p1;
    src_corners[1] = p2;
    src_corners[2] = p3;
    src_corners[3] = p4;
 
    vector<Point2f> dst_corners(4);
    dst_corners[0] = Point(0, 0);
    dst_corners[1] = Point(width, 0);
    dst_corners[2] = Point(0, height);
    dst_corners[3] = Point(width, height);
 
    // 【12】獲取透視變換矩陣,並最終顯示變換後的結果
    Mat resultImage;
    Mat warpmatrix = getPerspectiveTransform(src_corners, dst_corners);
    warpPerspective(src, resultImage, warpmatrix, resultImage.size(), INTER_LINEAR);
    imshow("Final Result", resultImage);

3、示例圖片

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