Detecting and Extracting Rectangular based Structure [closed]

edit

I am currently working on a python script to extract specific rectangular feature from an image that has multiple objects.

I would like to extract each object individually as seen below. The problem I am having is that my code works onlly on clear images with no background noise and high resolution. The image on the right does not get detected at all for some reason as its noisier, the edges are rough and it's lower resolution image.

Appreciate any help I can get with this.

import numpy as np
import cv2 
from matplotlib import pyplot as plt
import os


mypath='path\\images'
onlyfiles = [ f for f in os.listdir(mypath) if os.path.isfile(os.path.join(mypath,f)) ]
images = np.empty(len(onlyfiles), dtype=object)
for n in range(0, len(onlyfiles)):
   images[n] = cv2.imread( os.path.join(mypath,onlyfiles[n]) )

   gwash = images[n] #import image

   gwashBW = cv2.cvtColor(gwash, cv2.COLOR_RGB2GRAY) #change to grayscale

   height = np.size(gwash, 0)
   width = np.size(gwash, 1)

   ret,thresh1 = cv2.threshold(gwashBW ,41,255,cv2.THRESH_BINARY) 


   kernel = np.ones((1,1),np.uint8) 

   erosion = cv2.erode(thresh1, kernel,iterations = 31) 
   opening = cv2.morphologyEx(erosion, cv2.MORPH_OPEN, kernel)
   closing = cv2.morphologyEx(opening, cv2.MORPH_CLOSE, kernel) 

   _,contours, hierarchy = cv2.findContours(closing,cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE) 

   areas = [] #list to hold all areas

  for i,contour in enumerate(contours):
      ar = cv2.contourArea(contour)
      areas.append(ar)
      cnt = contour
      (x, y, w, h) = cv2.boundingRect(cnt)
       if cv2.contourArea(cnt) > 60000 and cv2.contourArea(cnt) < (height*width):
          if hierarchy[0,i,3] == -1:
             cv2.rectangle(gwash, (x,y), (x+w,y+h), (255, 0, 0), 12)


  plt.subplot2grid((2,5),(0,n)),plt.imshow(gwash)
  plt.title('Extraction'), plt.xticks([]), plt.yticks([])


plt.show()