How do I count number of tabs in screenshot using OpenCV houghlines?

Question

I am trying to count number of tabs in screenshot using OpenCV. I first cropped my image to limit to chrome tabs. Then I used edge detection, Canny algorithm to find edges in chrome. Then I am using Houghlines to find number of tabs, but I am not getting the required ouput through Houghlines. Below is my code and output.

import cv2
import numpy as np
import math
from matplotlib import pyplot as plt
img = cv2.imread('1.png')

gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
edges = cv2.Canny(gray,50,200,apertureSize = 3)
cv2.imwrite('result.png',edges)
lines = cv2.HoughLines(edges,1,np.pi/180,50)

for rho,theta in lines[0]:
  slope = 180*theta*1.0/np.pi
  if slope > 110 and slope <148: # for identifying chrome tab angle (right slope line of each tab)
    a = np.cos(theta)
    b = np.sin(theta)
    x0 = a*rho
    y0 = b*rho
    x1 = int(x0 + 1000*(-b))
    y1 = int(y0 + 1000*(a))
    x2 = int(x0 - 1000*(-b))
    y2 = int(y0 - 1000*(a))
    cv2.line(img,(x1,y1),(x2,y2),(0,0,255),3)
cv2.imwrite('result2.png',img)

PSchn PSchn · Accepted Answer · 2016-08-23T14:47:57

Very interesting:D A really simple solution would be to binarize your image and to define a line in the upper area of the image and get the gray values. Then you could count the intersections. Here is an example:

The fancy algorithms arent always the best solution. Define what you want to do and try to find a solution as simple as possible.

Here is my solution in C++. Quick and dirty ;)

#include "opencv2/imgproc.hpp"
#include "opencv2/highgui.hpp"
#include <vector>
#include <stdlib.h>
#include <stdio.h>

using namespace cv;
using namespace std;

Mat src, binary, morph, gray, morph_rgb;

/**
*Compute number of tabs 
*/
int getNumberOfTabs(Mat& src, int start_col, int stop_col, int search_row, bool draw=false);

/**
* @function main
*/
int main(int argc, char** argv)
{
    const int morph_size = 2;
    const int start_col = 5;
    const int stop_col = 1750;
    const int row_index = 2;
    /// Load an image
    src = imread("C:\\Users\\phili\\Pictures\\Tab.png", 1);

    //Convert for binarization
    cvtColor(src, gray, CV_RGB2GRAY);
    threshold(gray, binary, 164, 255, 1);

    //Remove icons and text on tabs
    Mat element = getStructuringElement(CV_SHAPE_RECT, Size(2 * morph_size + 1, 2 * morph_size + 1), Point(morph_size, morph_size));
    morphologyEx(binary, morph, CV_MOP_OPEN, element);

    int nmb_tabs = getNumberOfTabs(morph, start_col, stop_col, row_index, true);

    imshow("Original", src);
    imshow("Binary", binary);
    imshow("Binary", morph);


    /// Wait until user finishes program
    while (true)
    {
        int c;
        c = waitKey(20);
        if ((char)c == 27)
        {
            break;
        }
    }

}

int getNumberOfTabs(Mat& src,int start_col,int stop_col, int row_index, bool draw)
{
    int length = stop_col - start_col;

    //Extract gray value profil
    Mat profil = cv::Mat(0, length, CV_8U);
    profil = src.colRange(start_col, stop_col).row(row_index);

    Mat src_rgb;
    if (draw)
    {       
        cvtColor(src, src_rgb, CV_GRAY2RGB);
        line(src_rgb, Point(start_col, row_index), Point(stop_col, row_index), Scalar(0, 0, 255), 2);
    }

    //Convolve profil with [1 -1] to detect edges
    unsigned char* input = (unsigned char*)(profil.data);
    vector<int> positions;
    for (int i = 0; i < stop_col - start_col - 1; i++)
    {
        //Kernel
        int first = input[i];
        int second = input[i + 1];
        int ans = first - second;

        //Positiv or negativ slope ?
        if (ans < 0)
        {
            positions.push_back(i + 1);
            if(draw)
                circle(src_rgb, Point(i + start_col, row_index), 2, Scalar(255,0, 0), -1);
        }
        else if (ans > 0)
        {
            positions.push_back(i);
            if (draw)
                circle(src_rgb, Point(i + start_col + 1, row_index), 2, Scalar(255,0, 0), -1);
        }

    }
    if (draw)
        imshow("Detected Edges", src_rgb);
    //Number of tabs
    return positions.size() / 2;
}

and the results with the search line in red and the detected edges in blue:

How do I count number of tabs in screenshot using OpenCV houghlines?

1 Answers