Connected Component labelling -gray scale image

Question

I tried to modify the code given in http://stackoverflow.com/questions/1989987/my-own-ocr-program-in-python for finding the connected components in a gray scale image. Ive attached the code,sample image and output below.

Sample Image
Output:

But the connected components obtained is not correct. Please suggest some solution for this problem..Thanks.

import sys, numpy

from array import array

import OtsuAlgorithm

import pymorph

from OtsuAlgorithm import * 

from PIL import Image, ImageDraw

import random

class Region():

    def __init__(self, x, y):
        self._pixels = [(x, y)]
        self._min_x = x
        self._max_x = x
        self._min_y = y
        self._max_y = y

    def add(self, x, y):
        self._pixels.append((x, y))
        self._min_x = min(self._min_x, x)
        self._max_x = max(self._max_x, x)
        self._min_y = min(self._min_y, y)
        self._max_y = max(self._max_y, y)

    def box(self):
        return [(self._min_x, self._min_y), (self._max_x, self._max_y)]



def find_regions(im): #im -> Binarized Image Array

     height  = len(im)

        width=len(im[0])

        #Height & Width of Image Array- > 510 x 520

        regions = {}
     pixel_region = [[0 for y in range(height)] for x in range(width)]
        print 'Height& Width of pixel_region'
        print len(pixel_region),len(pixel_region[0])
        equivalences = {}
     n_regions = 0
       #first pass. find regions.
     for x in xrange(width-1):
         for y in xrange(height-1):
             #look for a black pixel
              if im[y][x]== 1: #BLACK

                         # get the region number from north or west
                         # or create new region

    region_n = 0 if y == 0 else pixel_region[x][y-1]
                  region_w = 0 if x == 0 else pixel_region[x-1][y]

                                region_nw= 0 if (x == 0 or y == 0) else pixel_region[x-1][y-1]

    wd = width-1
                                hd=height-1

    region_ne= 0 if (x == hd ) else pixel_region[x+1][y-1]
                                region_e= 0 if (x==hd) else pixel_region[x+1][y]
                                region_s= 0 if (y==wd) else pixel_region[x][y+1] 

                  max_region = max(region_n, region_w,region_ne,region_nw,region_e,region_s)
    #max_region = max(region_n, region_w)
                  if max_region > 0:


                       new_region = min(filter(lambda i: i > 0, (region_n,region_w,region_ne,region_nw,region_e,region_s)))

                       #update equivalences
                       if max_region > new_region:
                           if max_region in equivalences:
                                equivalences[max_region].add(new_region)
                           else:

                                equivalences[max_region] = set((new_region,))
                  else:
                       #no neighbours uniquely label the region
                       n_regions += 1
                       new_region = n_regions
                  pixel_region[x][y] = new_region

      #Scan image again, assigning all equivalent regions the same region value.
     for x in xrange(width):
         for y in xrange(height):
                 r = pixel_region[x][y]
                 if r > 0:
                      while r in equivalences:
                          r = min(equivalences[r])
                                        pixel_region[x][y]=r 
                       if not r in regions:
                           regions[r] = Region(x, y)
                       else:
                           regions[r].add(x, y)
        for k, v in equivalences.iteritems():
         print k, v

        regionCords=list(regions.itervalues())

        return regionCords

def main():

     im = Image.open("/home/hsrd/Desktop/Images_OCR/Screenshot.tif")#Width:520 Height: 510 

     image_array= im.getdata()

     width,height=im.size 

     pixdata=list(image_array)

     otsu=OtsuAlgorithm()

     threshold=otsu.calculateOptimalThreshold(width,height,pixdata)

     a=pymorph.binary(im,threshold)#binarize Image

     regions = find_regions(a)

     draw = ImageDraw.Draw(im)
     for r in regions:
         draw.rectangle(r.box(), outline="red")
     del draw 
     output = file("output.png", "wb")
     im.save(output)
     output.close()

if __name__ == "__main__":
        main()