Image Analysis for Machine Learning
Last modified: 2023-09-30
Computer Vision
Machine Learning
Investigate images to get sensitive/secret data or sensitive information hidden in the images.
In advance, load an image using Pillow (PIL).
import numpy as np
from PIL import Image
img = Image.open("example.png")
Basic Information
# Filename
img.filename
# Image information
img.info
# Image format (PNG, JPG, etc.)
img.format
# Color mode (RPG, CMYK, etc.)
img.mode
# Image size
img.size
# Bytes
img.tobytes()
# Pixels
np.array(img.getdata())
Plot Images
import matplotlib.pyplot as plt
plt.imshow(img)
plt.axis('off') # Turn off axis and labels
plt.show()
Hidden Information
Find hidden data in the image by slightly changing.
Resize Image & Get Bytes
img1 = img.resize((128, 128))
print(img1.tobytes())
XOR Image Bytes
# Convert image to bytes
bytes = img.tobytes()
key = 2 # specify the XOR key
xored = []
for byte in bytes:
xored.append(byte ^ key)
xored_np = np.array(xored)
print(xored_np)