c++ - 从图像中获取数字

Question

在这里，我试图取出相同大小的 block ，以便为 OCR 应用程序准备好数字

第一次尝试通过固定步长移动的小代码，但由于数字之间的空格，它在某些位置跳得很高，主要问题是最后 5 位数字，有时它们是 2 个数字，空格然后是 3 个数字，有时它们是 3 个数字，空格然后是 2 个数字，如果 5 个数字很大，最后可能是 5 个数字

第二次尝试我使用了 FindContour，当它找到对象时，我调整了矩形的大小以适合它，但问题是它没有按从左到右或相反的顺序给我数字。

那我该如何处理呢？

第一次尝试:

void DetectEqualRectangles(Mat image){
 resize(image,image,Size(810,52));
int k=0;
for(int i=0;i<14;i++){
    rectangle(image,Point(k,0),Point(45+k,52),Scalar(0,0,255),1,8,0);
    imshow("1",image);
    waitKey(0);
    if(i==0){k+=70;}
    else if(i==2){k+=71;}
    else if(i==4){k+=75;}
    else if(i==6){k+=78;}
    else if(i==8){k+=76;}
    else{k+=50;}
}}

第二次尝试:

void DetectUsingContours(Mat image){
resize(image,image,Size(810,52));
Mat gray;int BrightnessIndicator=0;
cvtColor(image,gray,CV_BGR2GRAY);

GaussianBlur(gray,gray,Size(5,5),3,0); // applying a gaussianBlur
BrightnessIndicator=EstimateBrighteness(image); // getting the approximate value for the brightness

cout<<BrightnessIndicator<<endl;
threshold(gray,gray,BrightnessIndicator-33,255,CV_THRESH_BINARY_INV); //thresholding
imshow("s",gray);

vector< vector<Point> > Contour;
findContours(gray,Contour,CV_RETR_EXTERNAL,CV_CHAIN_APPROX_SIMPLE);     //finding outer contours
cout<<Contour.size();
for(int i=0;i<Contour.size();i++){

   Rect bounding = boundingRect(Contour[i]);  // draw a rectangle
   if(bounding.x>15 && bounding.x<image.cols-50){bounding.x-=15;bounding.width=50;}
   else if(bounding.x>image.cols-50){bounding.x=image.cols-40;bounding.width=40;}
   else{bounding.x=0;bounding.width=50;}


    bounding.y-=bounding.y;
    bounding.height=image.rows;
  //  rectangle(image,bounding,Scalar(0,255,0),1,8,0);

    Mat CroppedImage=image(bounding);
    stringstream ss;
    ss<<"C:\\Users\\cdc\\Desktop\\GSC\\ExtractingNumbers\\"<<i<<".jpg";
    imwrite(ss.str(),CroppedImage);
    imshow("5",image);
    imshow("23",CroppedImage);
    waitKey(0);
}}

这是原始图像:

Answer 1

只需按 std::sort 对结果进行排序

#include <opencv2/core.hpp>
#include <opencv2/highgui.hpp>
#include <opencv2/imgproc.hpp>

#include <algorithm>
#include <iostream>
#include <sstream>

using namespace cv;
using namespace std;

void DetectUsingContours(Mat &image)
{
    resize(image,image,Size(810,52));
    Mat gray;
    cvtColor(image,gray,CV_BGR2GRAY);

    GaussianBlur(gray,gray,Size(5,5),3,0); // applying a gaussianBlur
    threshold(gray, gray,0, 255,
              CV_THRESH_BINARY_INV | CV_THRESH_OTSU); //thresholding
    imshow("s",gray);

    vector< vector<Point> > Contour;
    findContours(gray,Contour,CV_RETR_EXTERNAL,CV_CHAIN_APPROX_SIMPLE);     //finding outer contours
    cout<<Contour.size();
    std::vector<cv::Rect> rects;
    for(size_t i=0;i<Contour.size();i++){

        Rect bounding = boundingRect(Contour[i]);  // draw a rectangle
        if(bounding.x>15 && bounding.x<image.cols-50){bounding.x-=15;bounding.width=50;}
        else if(bounding.x>image.cols-50){bounding.x=image.cols-40;bounding.width=40;}
        else{bounding.x=0;bounding.width=50;}

        bounding.y-=bounding.y;
        bounding.height=image.rows;
        rects.emplace_back(bounding);
    }

    auto func = [](cv::Rect const &lhs, cv::Rect const &rhs)
    {
      return lhs.x < rhs.x;
    };
    std::sort(std::begin(rects), std::end(rects), func);
    for(size_t i = 0; i != rects.size(); ++i){
        Mat CroppedImage=image(rects[i]);
        stringstream ss;
        ss<<"C:/Users/cdc/Desktop/GSC/ExtractingNumbers/"<<i<<".jpg";
        imwrite(ss.str(),CroppedImage);
        imshow("5",image);
        imshow("23",CroppedImage);
        waitKey(0);
    }
}

int main()
{
    DetectUsingContours(cv::imread("tVVEl.jpg"));

    return 0;
}

我用自适应阈值做阈值，你不需要自己估计亮度。