hough_line.py

import scipy
import numpy as np
import matplotlib.pyplot as plt


def hough_line(image):
    """Simple implementation of hougline algorithm

    Args:
        image (np.array): the input image

    Returns:
        tuple(np.array, list, list) : the accumulator, theta values, and radius values
    """
    # Theta in range from -90 to 90 degrees
    thetas = np.deg2rad(np.arange(-90, 90))

    # Get image dimensions
    width = image.shape[0]
    hight = image.shape[1]

    # Max diatance is diagonal one
    Maxdist = np.round(np.sqrt(width**2 + hight ** 2))

    # Range of radius
    rs = np.linspace(-Maxdist, Maxdist, 2*Maxdist)
    accumulator = np.zeros((int(2 * Maxdist), len(thetas)))

    for i in range(width):
        for j in range(hight):
            if image[i, j] > 0:
                for k in range(len(thetas)):
                    r = i*np.cos(thetas[k]) + j * np.sin(thetas[k])
                    accumulator[int(r + Maxdist), k] += 1
    return accumulator, thetas, rs


if __name__ == '__main__':
    image = np.zeros((150, 150))
    image[:, :] = np.eye(150)
    accumulator, thetas, rhos = hough_line(image)
    plt.figure('Original Image')
    plt.imshow(image)
    plt.set_cmap('gray')
    plt.figure('Hough Space')
    plt.imshow(np.log10(accumulator+1))
    plt.set_cmap('gray')
    plt.show()
    idx = np.argmax(accumulator)
    rho = int(rhos[int(idx / accumulator.shape[1])])
    theta = thetas[int(idx % accumulator.shape[1])]
    print("rho={0:.0f}, theta={1:.0f}".format(rho, np.rad2deg(theta)))