• Stony Brook University

• CSE 527

midterm_hough_transform

September 26, 2019

In [1]: import numpy as np

import pandas as pd

import matplotlib.pyplot as plt

0.1 Problem Setup

In [2]: angles = np.arange(-90, 91, 15, dtype=np.float32) # * np.pi / 180

intercepts = np.arange(-1, 8)

points = [(0,0), (1,6), (2,4), (3,6), (4,8)]

print "angles: ", angles

print "intercepts: ", intercepts

print "points: ", points

angles: [-90. -75. -60. -45. -30. -15. 0. 15. 30. 45. 60. 75. 90.]

intercepts: [-1 0 1 2 3 4 5 6 7]

points: [(0, 0), (1, 6), (2, 4), (3, 6), (4, 8)]

0.2 Question b

In [3]: vote_table = np.zeros((len(angles), len(intercepts)), dtype=int)

eps = 0.5

angles_pi = angles * np.pi / 180

# hough transform

for i in xrange(len(angles_pi)):

ang = angles_pi[i]

for j in xrange(len(intercepts)):

intercept = intercepts[j]

for pt in points:

if abs(pt[0] * np.tan(ang) + intercept - pt[1]) < eps:

vote_table[i,j] = vote_table[i,j] + 1

vote_table_df = pd.DataFrame(vote_table, index=angles, columns=intercepts)

display(vote_table_df)

1

-1 0 1 2 3 4 5 6 7

-90.0 0 1 0 0 0 0 0 0 0

-75.0 0 1 0 0 0 0 0 0 0

-60.0 0 1 0 0 0 0 0 0 1

-45.0 0 1 0 0 0 0 0 1 1

-30.0 0 1 0 0 0 0 1 0 1

-15.0 0 1 0 0 0 0 1 1 1

0.0 0 1 0 0 0 1 0 2 0

15.0 0 1 0 0 1 0 1 1 1

30.0 0 1 0 0 1 1 1 1 0

45.0 0 1 0 1 1 1 1 0 0

60.0 0 1 3 0 0 1 0 0 0

75.0 0 1 0 1 0 0 0 0 0

90.0 0 1 0 0 0 0 0 0 0