Getting numbers out of an image

Question

Here I am trying to get out Equal sized blocks to get the numbers ready for an OCR application

1st try through little code that moves by fixed steps while at some positions it jumps high due to the space between numbers , the main problem is at the last 5 digits , sometimes they are 2 numbers , space then 3 numbers , sometimes they are 3 numbers , space then 2 numbers and finally they maybe 5 numbers if the 5 numbers are big

2nd try i used FindContour and when it find the object i resize the rectangle to fit it but the problem is that it didn't give me the numbers in-order from left to right or the opposite.

so how can i deal with that ?

1st try:

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;}
}}

2nd try:

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);
}}

and here it is the original images:

score 1 · Answer 1 · answered Sep 04 '15 at 04:58

Just sort the result by std::sort

#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;
}

I use adaptive threshold to do the thresholding, you do not need to estimate the brightness by yourself.

Getting numbers out of an image

1 Answers1