MIT 6.100L PS5 Explained: Image Steganography, Watermarking, and Professional Submission Workflow

[Rajeev Bagra]

📌 Context (Initial Code and Purpose)

In MIT 6.100L / MITx Problem Set 5, students work with image filtering and steganography. The assignment requires you to:

• Apply filters to images
• Recover hidden black-and-white and color images
• Add a Kerberos watermark
• Combine outputs into a single PDF
• Submit your work correctly

A simplified example of the recovery code is:

from PIL import Image

def extract_end_bits(num_bits, pixel):
    return pixel % (2 ** num_bits)

def reveal_color_image(filename):
    img = Image.open(filename)
    width, height = img.size
    pixels = img.load()

    secret_img = Image.new("RGB", (width, height))
    secret_pixels = secret_img.load()

    scale = 255 // 7

    for x in range(width):
        for y in range(height):
            r, g, b = pixels[x, y]

            secret_r = extract_end_bits(3, r) * scale
            secret_g = extract_end_bits(3, g) * scale
            secret_b = extract_end_bits(3, b) * scale

            secret_pixels[x, y] = (secret_r, secret_g, secret_b)

    return secret_img

This code extracts hidden color information and rebuilds a secret image.

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✅ Q&A: Purpose and Complete Process of the Exercise

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❓ Q1: What is the main purpose of this exercise?

✅ Answer:
The main purpose is to verify that you understand:

• image representation
• bit manipulation
• steganography
• RGB processing
• professional submission practices

It is designed to test both technical and practical skills, not just to collect files.

---

❓ Q2: Is this exercise only about steganography?

✅ Answer:
No. It integrates multiple core concepts:

• digital signal processing
• binary data handling
• image reconstruction
• software testing
• documentation and packaging

Steganography is used as the main applied topic.

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❓ Q3: What is the complete step-by-step process for this assignment?

✅ Answer:
The full workflow consists of six main steps:

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▶ Step 1: Create the Filtered Image

You apply an image filter and generate:

filtered_image_15.png

This confirms your understanding of convolution and neighborhood processing.

---

▶ Step 2: Recover the Black-and-White Hidden Image

You extract 1 LSB from each pixel of hidden1.bmp and rebuild:

hidden1_unhidden.bmp

This tests basic steganography.

---

▶ Step 3: Recover the Color Hidden Image

You extract 3 LSBs from each RGB channel of hidden2.bmp and rebuild:

hidden2_unhidden.bmp

This tests advanced multi-channel steganography.

---

▶ Step 4: Add Your Kerberos Watermark

You watermark each image using:

draw_kerb(filename, kerberos)

Example:

draw_kerb("filtered_image_15.png", "your_kerberos")

This generates files ending with _kerb.

---

▶ Step 5: Combine All Images into One PDF

After watermarking, you will have three files like:

filtered_image_15_kerb.png
hidden1_unhidden_kerb.bmp
hidden2_unhidden_kerb.bmp

These must be combined into one PDF.

---

✅ Method A: Using Python (Recommended)

from PIL import Image

images = [
    Image.open("filtered_image_15_kerb.png").convert("RGB"),
    Image.open("hidden1_unhidden_kerb.bmp").convert("RGB"),
    Image.open("hidden2_unhidden_kerb.bmp").convert("RGB")
]

images[0].save(
    "submission.pdf",
    save_all=True,
    append_images=images[1:]
)

This creates:

submission.pdf

---

✅ Method B: Using an Online PDF Combiner

You may also use tools like:

• SmallPDF
• iLovePDF
• Adobe PDF tools

Upload the three _kerb images and download the combined PDF.

---

▶ Step 6: Prepare for Autograder Submission

Before submitting, comment out watermark calls:

# draw_kerb("filtered_image_15.png", "your_kerberos")
# draw_kerb("hidden1_unhidden.bmp", "your_kerberos")
# draw_kerb("hidden2_unhidden.bmp", "your_kerberos")

Then submit:

• ps5.py
• submission.pdf

---

❓ Q4: Why is combining images into a PDF important?

✅ Answer:
Combining images into one PDF:

• ensures completeness
• standardizes format
• simplifies grading
• prevents missing files

It also reflects professional reporting standards.

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❓ Q5: What real-world skills does this workflow teach?

✅ Answer:
This assignment builds skills in:

• computer vision
• cybersecurity
• digital forensics
• data engineering
• technical documentation

It trains students to deliver not just code, but complete, verified results.

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🌐 Official MITx / Course Reference

You can find the official course material and Problem Set 5 here:

👉 MIT OpenCourseWare – 6.100L (Fall 2022)
https://ocw.mit.edu/courses/6-100l-introduction-to-cs-and-programming-using-python-fall-2022/

👉 Problem Set 5 PDF
https://ocw.mit.edu/courses/6-100l-introduction-to-cs-and-programming-using-python-fall-2022/resources/mit6_100l_f22_ps5/

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✅ Final Takeaway

This exercise trains you to work with digital images at the bit and pixel level, verify authorship through watermarking, and package technical results into a professional submission format. It reflects real-world software and data-engineering workflows, not just academic grading requirements.

 

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