hough_transform.py

from math import hypot, pi, cos, sin
from PIL import Image
import numpy as np

def hough(im, ntx=460, mry=360):
    "Calculate Hough transform."
    pim = im.load()
    nimx, mimy = im.size
    mry = int(mry/2)*2 #Make sure that this is even
    him = Image.new("L", (ntx, mry), 255)
    phim = him.load()
 
    rmax = hypot(nimx, mimy)
    dr = rmax / (mry/2)
    dth = pi / ntx
 
    for jx in xrange(nimx):
        for iy in xrange(mimy):
            col = pim[jx, iy]
            if col < 1: continue #when color is black (0)
            for jtx in xrange(ntx):
                th = dth * jtx
                r = jx*cos(th) + iy*sin(th)
                iry = mry/2 + int(r/dr+0.5)
                phim[jtx, iry] -= 1 #update values in the accumulator (here we are subtracting 1 instead of adding, idea is the same)
    return him
 
def test():
    "Test Hough transform image previously obtained form Canny Edge Detection."
    im = Image.open("mycanny.jpg").convert("L")
    him = hough(im)
    him.save("ho5.bmp")
 
if __name__ == "__main__": test()