title: Find area between black contours
body: <p>I have a white contour, with black inside and around.
  I need to find the biggest circle that have only white areea inside, without holes, and does not contain black area from outside of the contour. For now, I can not find good way to do so.
  I am using openCv and Numpy in Python. of course if any other library is necessary I would like to hear.</p>
  <p>##Update##</p>
  <p>At first, I was trying with this code, but it gave me the biggest circle without consider the holes in it:</p>
  <pre><code>def get_biggest_area_inside_contour(self,image,index):
  
  image_bin=cv2.cvtColor(image,cv2.COLOR_RGB2GRAY) 
  retval,image_bin=cv2.threshold(image_bin,biggest_circle_thresh,255,cv2.THRESH_BINARY) 
  contours, hierarchy = cv2.findContours(image_bin.copy(),cv2.RETR_CCOMP,cv2.CHAIN_APPROX_SIMPLE) 
  image_with_contour=np.zeros(image.shape, np.uint8) 
  dist=np.zeros((image.shape[0],image.shape[1])) 
  for ind_y in range(image.shape[0]): 
      for ind_x in range(image.shape[1]): 
          dist[ind_y,ind_x] = cv2.pointPolygonTest(max_contour,(ind_x,ind_y),True)
  </code></pre>
  <p>As answered to me, there is a solution for that problem.
  The thing is I didn't managed to pass the code from MATLAB to python.
  The code is:</p>
  <pre><code>def get_biggest_area_inside_contour(self,image,index):
  
      image_bin=cv2.cvtColor(image,cv2.COLOR_RGB2GRAY)
      _,image_bin=cv2.threshold(image_bin,biggest_circle_thresh,255,cv2.THRESH_BINARY)
      contours, _ = cv2.findContours(image_bin.copy(),cv2.RETR_CCOMP,cv2.CHAIN_APPROX_SIMPLE)
      max_contour=contours[0]
      max_area=cv2.contourArea(contours[0])
      #Find the biggest white contour, some times can be little white surrond by black area
      for _cnt in contours:
          _area = cv2.contourArea(_cnt)
          if _area&gt;max_area:
              max_area=_area
              max_contour=_cnt 
      gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
      _blurred = cv2.GaussianBlur(gray, (5, 5), 0)
      _threshold = cv2.threshold(_blurred, biggest_circle_thresh, 255, cv2.THRESH_BINARY)[1]
      result_img=cv2.drawContours(_threshold,max_contour,-1,(255,255,255),1)
      contours, _ = cv2.findContours(result_img.copy(),cv2.RETR_CCOMP,cv2.CHAIN_APPROX_SIMPLE)
      #cv2.namedWindow('img {}'.format(index), cv2.WINDOW_NORMAL)
      #cv2.imshow('img {}'.format(index), result_img)
  
      apdp = cv2.approxPolyDP(max_contour,1,True)
      ap = [(a[0][0],a[0][1]) for a in apdp]
      vor_ap = Voronoi(ap,incremental=True)
      spined = []
      for ridge in contours:
          x, y, w, h = cv2.boundingRect(ridge)
          if cv2.pointPolygonTest(max_contour,(x,y),True) &lt; 0.0 or cv2.pointPolygonTest(max_contour,(x+w,y+h),True) &lt; 0.0:
              continue
          else:
              if tuple((x,y)) not in spined:
                  spined.append([tuple((x,y))])
              if tuple((x+w,y)) not in spined:
                  spined.append([tuple((x+w,y))])
              if tuple((x,y+h)) not in spined:
                  spined.append([tuple((x,y+h))])  
              if tuple((x+w,y+h)) not in spined:
                  spined.append([tuple((x+w,y+h))])                                 
      if len(spined)&gt;0:
          for index in range(0,len(spined)):
              vor_ap.add_points(spined[index])
      fig=plt.figure(index)
      ax = fig.add_subplot(111)        
      voronoi_plot_2d(vor_ap, point_size=5, ax=ax)
      plt.scatter([s[0][0] for s in spined],[s[0][1] for s in spined])
      plt.plot([a[1] for a in ap],[a[0] for a in ap])
      if len(spined)&gt;0:
          borders_and_holes=ap
          for i in range (0,len(spined)):
              borders_and_holes.append(spined[i])
          points=np.vstack(borders_and_holes)
          dt = Delaunay(points)
          ##cc = compute_triangle_circumcenters(dt.points, dt.simplices) Not sure how to do this
          #plt.plot(cc[:, 0], cc[:, 1], &quot;.k&quot;)
      plt.show()
  </code></pre>
  <p><a href="https://i.stack.imgur.com/nGnCj.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/nGnCj.png" alt="enter image description here" /></a></p>