CODEWITHSUNDEEP
pythonpython-3.x
Rashid
Rashid

Reputation: 11

Calculating Euclidian distance for multiple image histograms

Ok so this is the function calculating the histogram:

def image_histogram():
    from PIL import Image
    import numpy as np
    import glob
    im = Image.open('/Users/Adnan/Desktop/Archive/0.jpg')
    im_vals1 = np.zeros(256)
    im_vals2 = np.zeros(256)
    im_vals3 = np.zeros(256)

    r,g,b = im.split()

    pixels_r = list(r.getdata())
    pixels_g = list(g.getdata())
    pixels_b = list(b.getdata())
    pix_r = np.array(pixels_r)
    pix_g = np.array(pixels_g)
    pix_b = np.array(pixels_b)
    for idx in range (0, len(pix_r)):
        im_vals1[pix_r[idx]] += 1
        im_vals2[pix_g[idx]] += 1
        im_vals3[pix_b[idx]] += 1
    histogram = list(im_vals1) + list(im_vals2) + list(im_vals3)
    return histogram
print(image_histogram())
def euclidean_distance():
    from scipy.spatial import distance
    a = image_histogram()
    b = image_histogram()
    dist = distance.euclidean(a,b)
print(euclidean_distance())

ok so this function now calculates the histogram of 1 image (0.jpg). I would like to know how could i run this same function multiple times with diff images and store each images histogram as a list to then be used by the euclidean distance function. Im guessing some sort of recursion should do the trick but do not know how to go about this since I can not seem to find it anywhere.

Upvotes: 0

Views: 3583

Answers (1)

rmkemker
rmkemker

Reputation: 470

From my computer vision course, I remember that one of the best metrics for calculating the distance between two histograms is the chi-squared distance.

https://stats.stackexchange.com/questions/184101/comparing-two-histograms-using-chi-square-distance

In python, it can be a custom metric for sklearn Nearest Neighbor function:

def chiSquared(p,q):
    return 0.5*np.sum((p-q)**2/(p+q+1e-6))

Upvotes: 4

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