Reg: Copy blob based on the area of the blob size

Objective: Copy the bigger blobs in another mask image

I have a threshold image with blobs as shown:

How could I copy the bigger blobs into a mask image and leave out the one-pixel blobs?

My code (but I am not getting the desired result):

import numpy as np
import cv2

ref_img = cv2.imread('threshold.jpg', 0)
thresh = np.copy(ref_img)
cnts,_ = cv2.findContours(ref_img, cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE)
mask = np.zeros(ref_img.shape, dtype="uint8")
for c in cnts:
   (x,y),radius = cv2.minEnclosingCircle(c)
   area = cv2.contourArea(c)
   if int(area) < 1:
      cv2.circle(mask, (int(x), int(y)), int(radius), (255, 255, 255), -1)

cv2.imshow('img', mask)
cv2.waitKey(0)

Note: Using OpenCV 2.4.x

Here is one of the method you can use to achieve your goal. Explanations are provided in the comments of the code

import numpy as np
import cv2

ref_img = cv2.imread('threshold.jpg', 0)


img, cnts,_ = cv2.findContours(ref_img, cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE)
mask = np.zeros(ref_img.shape, dtype="uint8")
for c in cnts:
   # Get the bounding rect surrounding your blobs
   x,y,w,h = cv2.boundingRect(c) 

   # Calculating the area of the rect is similar to the area of the blob minus the complexity
   area = w*h

   # For box area bigger than one, copy the information from the source image to the mask. 
   # Since the bounding box contains all the relevant information, just copy the entire box to the mask.
   if int(area) > 1 :
    mask[y:y+h,x:x+w] = ref_img[y:y+h,x:x+w]




cv2.imshow('img', mask)
cv2.waitKey(0)