Thresholding

After removing the background, we only have to binarize the image for future segmentation. We are going to do this with threshold. Threshold is a simple function that sets each pixel's values to a maximum value (255, for example). If the pixel's value is greater than the threshold value or if the pixel's value is lower than the threshold value, it will be set to a minimum (0):

Now, we are going to apply the threshold function using two different threshold values: we will use a 30 threshold value when we remove the light/background because all non-interesting regions are black. This is because we apply background removal. We will also a medium value threshold (140) when we do not use a light removal method, because we have a white background. This last option is used to allow us to check the results with and without background removal:

  // Binarize image for segment 
  Mat img_thr; 
  if(method_light!=2){ 
   threshold(img_no_light, img_thr, 30, 255, THRESH_BINARY); 
  }else{ 
   threshold(img_no_light, img_thr, 140, 255, THRESH_BINARY_INV); 
  } 

Now, we are going to continue with the most important part of our application: the segmentation. We are going to use two different approaches or algorithms here: connected components and find contours.