I see a flag. I like flags. Especially the Japanese flags. I don't specifically care for Japan, but the flag is one of my favourites. I prefer flags with low entropy: so I wrote a script once that ranks the nations flags by entropy so I could quantify my preference. Thanks for letting me infodump a bit.
Edit: Due to people aski g for it: here is the top ten of my ranking:
Nations' flag entropy ranking (n=208).
Image source: Wikimedia.
0 white_field -1.439759075204976e-10
1 Indonesia 3.3274441922278752
2 Germany 3.391689777286108
3 South_Ossetia 3.8174437373506778
4 Monaco 3.9718936201427066
5 Poland 3.9719290780440133
6 Austria 4.372592975412404
7 Ukraine 4.405280849871184
8 Hungary 4.4465472496385985
9 Albania 4.6134257669087395
10 Mauritius 4.707109405551959
11 Luxembourg 4.721346585737304
Here's how I defined the entropy value for each flag:
def color_weighted_spectral_entropy(image):
b_channel, g_channel, r_channel = cv2.split(image)
# Calculate spectral entropy for each channel
def channel_spectral_entropy(channel):
f_transform = np.fft.fft2(channel)
f_shifted = np.fft.fftshift(f_transform)
magnitude_spectrum = np.abs(f_shifted)
if np.sum(magnitude_spectrum) > 0:
normalized = magnitude_spectrum / np.sum(magnitude_spectrum)
else:
normalized = magnitude_spectrum
# Entropy calculation with color channel weighting
epsilon = 1e-10
entropy = -np.sum(normalized * np.log2(normalized + epsilon))
return entropy
weighted_entropy = (
0.333 * channel_spectral_entropy(b_channel) +
0.333 * channel_spectral_entropy(g_channel) +
0.333 * channel_spectral_entropy(r_channel)
)
return float(weighted_entropy)
"White_field" is just an array that holds zeroes. I use this as a sanity check. Code is on github. I can send DM to whomever is interested. I guess it can also be searched for.
