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import Image
import numpy
import scipy.ndimage as ndi
import matplotlib
import matplotlib.pyplot as plt
from matplotlib.collections import PatchCollection
from matplotlib.patches import Rectangle
import pylab

# Bild laden
im0 = Image.open("test.bmp")
im0 = numpy.asarray(im0)[:,:,0]  # nur einen Kanal verwenden

# Linien finden
median = ndi.median_filter(im0, size=3).astype(float)
im = abs(im0 - median)

# Binarisierung
im = im > 100

# Connectect Component Labeling
im = ndi.binary_dilation(im, structure=[[1,1,1,1,1]])
im = ndi.label(im)[0]
segments = ndi.find_objects(im)

patches = []
for s1, s2 in segments:
    y1, x1 = s1.start, s2.start
    y2, x2 = s1.stop, s2.stop

    height = y2 - y1
    width = x2 - x1

    # Segmente nach div. Kriterien filtern
    if (2*height) > width: continue
    if height * width < 50: continue
    if height > 16: continue
    if height * width > 20*1000: continue

    patches.append(Rectangle([x1-.5, y1-.5], width, height))

# Plotten
ax = plt.axes()
pylab.imshow(im0)
colors = 200*numpy.random.rand(len(patches))
collection = PatchCollection(patches, cmap=matplotlib.cm.jet, alpha=0.4)
collection.set_array(numpy.array(colors))
ax.add_collection(collection)
plt.show()

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0 0 0 0 0
0 1 0 1 0
0 0 0 1 1
0 0 1 1 0

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0 0 0 0 0
0 1 0 2 0
0 0 0 2 2
0 0 2 2 0

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import sys
from math import sin, cos, sqrt, pi
import cv
import urllib2

# toggle between CV_HOUGH_STANDARD and CV_HOUGH_PROBILISTIC
USE_STANDARD = False
	
if __name__ == "__main__":
    if len(sys.argv) > 1:
       filename = sys.argv[1]
       src = cv.LoadImage(filename, cv.CV_LOAD_IMAGE_GRAYSCALE)
    else:
        url = 'https://code.ros.org/svn/opencv/trunk/opencv/doc/pics/building.jpg'
        filedata = urllib2.urlopen(url).read()
        imagefiledata = cv.CreateMatHeader(1, len(filedata), cv.CV_8UC1)
        cv.SetData(imagefiledata, filedata, len(filedata))
        src = cv.DecodeImageM(imagefiledata, cv.CV_LOAD_IMAGE_GRAYSCALE)
	
	
    cv.NamedWindow("Source", 1)
    cv.NamedWindow("Hough", 1)
	
    while True:
        dst = cv.CreateImage(cv.GetSize(src), 8, 1)
        color_dst = cv.CreateImage(cv.GetSize(src), 8, 3)
        storage = cv.CreateMemStorage(0)
        lines = 0
        cv.Canny(src, dst, 50, 200, 3)
        cv.CvtColor(dst, color_dst, cv.CV_GRAY2BGR)
	
        if USE_STANDARD:
            lines = cv.HoughLines2(dst, storage, cv.CV_HOUGH_STANDARD, 1, pi / 180, 100, 0, 0)
            for (rho, theta) in lines[:100]:
                a = cos(theta)
                b = sin(theta)
                x0 = a * rho
                y0 = b * rho
                pt1 = (cv.Round(x0 + 1000*(-b)), cv.Round(y0 + 1000*(a)))
                pt2 = (cv.Round(x0 - 1000*(-b)), cv.Round(y0 - 1000*(a)))
                cv.Line(color_dst, pt1, pt2, cv.RGB(255, 0, 0), 3, 8)
        else:
            lines = cv.HoughLines2(dst, storage, cv.CV_HOUGH_PROBABILISTIC, 1, pi / 180, 50, 50, 10)
            for line in lines:
                cv.Line(color_dst, line[0], line[1], cv.CV_RGB(255, 0, 0), 1, 8)
	
        cv.ShowImage("Source", src)
        cv.ShowImage("Hough", color_dst)

        k = cv.WaitKey(0)
        if k == ord(' '):
            USE_STANDARD = not USE_STANDARD
        if k == 27:
            break