Extracting valuable information from the resources available is a vital part of digital forensics. Getting access to all the information available is essential for an investigation process as it helps in retrieving appropriate evidence.
Resources that contain data can be either simple data structures such as databases or complex data structures such as a JPEG image. Simple data structures can be easily accessed using simple desktop tools, while extracting information from complex data structures require sophisticated programming tools.
The Python Imaging Library (PIL) adds image processing capabilities to your Python interpreter. This library supports many file formats, and provides powerful image processing and graphics capabilities. You can download the source files of PIL from − http://www.pythonware.com/products/pil/
The following illustration shows the complete flow diagram of extracting data from images (complex data structures) in PIL.
Now, let’s have a programming example to understand how it actually works.
Step 1 − Suppose we have the following image from where we need to extract information.
Step 2 − When we open this image using PIL, it will first note the necessary points required for extracting evidence, which includes various pixel values. Here is the code to open the image and record its pixel values −
from PIL import Image im = Image.open('Capture.jpeg', 'r') pix_val = list(im.getdata()) pix_val_flat = [x for sets in pix_val for x in sets] print pix_val_flat
Step 3 − Our code will produce the following output, after extracting the pixel values of the image.
The output delivered represents the pixel values of RGB combination, which gives a better picture of what data is needed for evidence. The data fetched is represented in the form of an array.
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