OpenCV矩形(長方/正方形) 檢測/尋找/搜尋/標定/標記

資料來源: https://mp.weixin.qq.com/s?subscene=23&__biz=MzIwMTE1NjQxMQ==&mid=2247485054&idx=1&sn=00eeb26a329e4e76a64ebfc4947ea6b0&chksm=96f3742aa184fd3cd6b43a9baca40f7cb3aa9bdf8d8ec73ba7592c1cdd491c6b320f218c565d&scene=7&key=391633c74d74d5c5ed92b8067722b7e9b8d4e714acfab02e293b75646deb5cb257bcc223d04293e52a34ba2d25cadfaeac15bd60a4097c79af272c759b9531a823b14fd912172ee14a9b73d5ba36b1b1&ascene=0&uin=MjIwODk2NDgxNw%3D%3D&devicetype=Windows+10+x64&version=62090529&lang=zh_TW&exportkey=AtFJkF12184D%2BLzw%2B92OGW0%3D&pass_ticket=XpKWTSs5D5AL70GOlf8f9nsq1J8zPUMrL3oMN4foYQdpL15qi6CeXIEotrwM%2FZ4t

https://github.com/alyssaq/opencv

結果圖:

其算法流程：

    1.中值濾波去噪；

    2.依次提取不同的顏色通道（BGR）檢測矩形；

    3.對每一通道使用canny檢測邊緣或者使用多個閾值二值化；

    4.使用findContours函數查找輪廓；

    5.使用approxPolyDP函數去除多邊形輪廓一些小的波折；

    6.找到同時滿足面積較大和形狀為凸的四邊形；

    7.判斷輪廓中兩兩鄰接直線夾角餘弦是否小於0.3（意味著角度在90度附近），是則此四邊形為找到的矩形。

code:

// The "Square Detector" program.
// It loads several images sequentially and tries to find squares in
// each image

#include "opencv2/core/core.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/highgui/highgui.hpp"

#include <iostream>
#include <math.h>
#include <string.h>

using namespace cv;
using namespace std;

static void help()
{
    cout <<
    "\nA program using pyramid scaling, Canny, contours, contour simpification and\n"
    "memory storage to find squares in a list of images\n"
    "Returns sequence of squares detected on the image.\n"
    "the sequence is stored in the specified memory storage\n"
    "Call:\n"
    "./squares\n"
    "Using OpenCV version %s\n" << CV_VERSION << "\n" << endl;
}


int thresh = 50, N = 5;
const char* wndname = "Square Detection Demo";

// helper function:
// finds a cosine of angle between vectors
// from pt0->pt1 and from pt0->pt2
static double angle( Point pt1, Point pt2, Point pt0 )
{
    double dx1 = pt1.x - pt0.x;
    double dy1 = pt1.y - pt0.y;
    double dx2 = pt2.x - pt0.x;
    double dy2 = pt2.y - pt0.y;
    return (dx1*dx2 + dy1*dy2)/sqrt((dx1*dx1 + dy1*dy1)*(dx2*dx2 + dy2*dy2) + 1e-10);
}

// returns sequence of squares detected on the image.
// the sequence is stored in the specified memory storage
static void findSquares( const Mat& image, vector<vector<Point> >& squares )
{
    squares.clear();

//s    Mat pyr, timg, gray0(image.size(), CV_8U), gray;

    // down-scale and upscale the image to filter out the noise
    //pyrDown(image, pyr, Size(image.cols/2, image.rows/2));
    //pyrUp(pyr, timg, image.size());


    // blur will enhance edge detection
    Mat timg(image);
    medianBlur(image, timg, 9);
    Mat gray0(timg.size(), CV_8U), gray;

    vector<vector<Point> > contours;

    // find squares in every color plane of the image
    for( int c = 0; c < 3; c++ )
    {
        int ch[] = {c, 0};
        mixChannels(&timg, 1, &gray0, 1, ch, 1);

        // try several threshold levels
        for( int l = 0; l < N; l++ )
        {
            // hack: use Canny instead of zero threshold level.
            // Canny helps to catch squares with gradient shading
            if( l == 0 )
            {
                // apply Canny. Take the upper threshold from slider
                // and set the lower to 0 (which forces edges merging)
                Canny(gray0, gray, 5, thresh, 5);
                // dilate canny output to remove potential
                // holes between edge segments
                dilate(gray, gray, Mat(), Point(-1,-1));
            }
            else
            {
                // apply threshold if l!=0:
                //     tgray(x,y) = gray(x,y) < (l+1)*255/N ? 255 : 0
                gray = gray0 >= (l+1)*255/N;
            }

            // find contours and store them all as a list
            findContours(gray, contours, RETR_LIST, CHAIN_APPROX_SIMPLE);

            vector<Point> approx;

            // test each contour
            for( size_t i = 0; i < contours.size(); i++ )
            {
                // approximate contour with accuracy proportional
                // to the contour perimeter
                approxPolyDP(Mat(contours[i]), approx, arcLength(Mat(contours[i]), true)*0.02, true);

                // square contours should have 4 vertices after approximation
                // relatively large area (to filter out noisy contours)
                // and be convex.
                // Note: absolute value of an area is used because
                // area may be positive or negative - in accordance with the
                // contour orientation
                if( approx.size() == 4 &&
                    fabs(contourArea(Mat(approx))) > 1000 &&
                    isContourConvex(Mat(approx)) )
                {
                    double maxCosine = 0;

                    for( int j = 2; j < 5; j++ )
                    {
                        // find the maximum cosine of the angle between joint edges
                        double cosine = fabs(angle(approx[j%4], approx[j-2], approx[j-1]));
                        maxCosine = MAX(maxCosine, cosine);
                    }

                    // if cosines of all angles are small
                    // (all angles are ~90 degree) then write quandrange
                    // vertices to resultant sequence
                    if( maxCosine < 0.3 )
                        squares.push_back(approx);
                }
            }
        }
    }
}


// the function draws all the squares in the image
static void drawSquares( Mat& image, const vector<vector<Point> >& squares )
{
    for( size_t i = 0; i < squares.size(); i++ )
    {
        const Point* p = &squares[i][0];

        int n = (int)squares[i].size();
        //dont detect the border
        if (p-> x > 3 && p->y > 3)
          polylines(image, &p, &n, 1, true, Scalar(0,255,0), 3, LINE_AA);
    }

    imshow(wndname, image);
}


int main(int /*argc*/, char** /*argv*/)
{
    static const char* names[] = { "imgs/2Stickies.jpg", "imgs/manyStickies.jpg",0 };
    help();
    namedWindow( wndname, 1 );
    vector<vector<Point> > squares;

    for( int i = 0; names[i] != 0; i++ )
    {
        Mat image = imread(names[i], 1);
        if( image.empty() )
        {
            cout << "Couldn't load " << names[i] << endl;
            continue;
        }

        findSquares(image, squares);
        drawSquares(image, squares);
        //imwrite( "out", image );
        int c = waitKey();
        if( (char)c == 27 )
            break;
    }

    return 0;
}