Q: How segment an Image I have one image data in the following format:
200406011215.goes12ir
print im.format, im.size, im.mode

MCIDAS (1732, 2600) L
These images are composed of lines and elements with their corresponding value of brightness ( 0 -255). I'm trying to make a script that targets a region with certain properties.
script:
import Image
im = Image.open("/home/mcidas/Documents/datos/200404031215.goes12ir")
im.show()

How I can target a region of the displayed image whose brightness value is > 205?
Anyone have an idea how I can identify and draw a mark(may be circle) on the regions of the image that meets the specified value)

A: You can use numpy's broadcasting to filter out the pixels above a threshold. This will work much better if you blur the image beforehand. A full working example (without blurring) is given below, just adapt to your needs:
import numpy as np
from pylab import *

# Generate random data with a "bright spot"
N = 100
line = np.linspace(-3,3,N)
X, Y = meshgrid(line,line)
Z  = np.exp(-((X+1)**2+(Y-1)**2)) 
Z += np.random.random(Z.shape)*.5

subplot(121)
imshow(Z,cmap=gray(), origin="lower", extent=[-3,3,-3,3])

Z2 = Z.copy()
# Identify regions that are brighter than threshold on z_scale
threshold = .8
idx = Z2>threshold

Z2[~idx] = None
Z2[idx ] = 1

subplot(122)
imshow(Z2,cmap=gray(), origin="lower", extent=[-3,3,-3,3])

# Place a dot at the "center" of the pixels found
CM = [X[idx].mean(), Y[idx].mean()]
scatter(*CM, s=100,color='red')

show()


