codes/10_least-significant-bit-steganography.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "# Dependencies"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {},
      "outputs": [],
      "source": [
        "import matplotlib.pyplot as plt\n",
        "\n",
        "# local dependencies\n",
        "from utils.quality_assessment import mse\n",
        "from utils.steganography import Steganography"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "# Load an image"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 4,
      "metadata": {},
      "outputs": [],
      "source": [
        "lenna = plt.imread(fname='../assets/images/dip_3rd/CH06_Fig0638(a)(lenna_RGB).tif')"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "# Least Significant Bit (LSB) steganography\n",
        "   - Steganography involves hiding data within other data (digital media like images, audio files, or video files)\n",
        "   - LSB technique only works with `lossless` encodings like `PNG` images"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 5,
      "metadata": {},
      "outputs": [],
      "source": [
        "message = \"This is called Least Significant Bit (LSB) steganography\""
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 6,
      "metadata": {},
      "outputs": [],
      "source": [
        "steganography = Steganography(encoding='ascii', n_lowest_bits=3)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 7,
      "metadata": {},
      "outputs": [],
      "source": [
        "message_length, encoded_image = steganography.encode(message=message, image=lenna)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 8,
      "metadata": {},
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "This is called Least Significant Bit (LSB) steganography\n"
          ]
        }
      ],
      "source": [
        "deocded_text = steganography.decode(image=encoded_image, length=message_length)\n",
        "print(deocded_text)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Experiment 1"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 9,
      "metadata": {},
      "outputs": [],
      "source": [
        "message = \"This is called Least Significant Bit (LSB) steganography\" * 3000"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 10,
      "metadata": {},
      "outputs": [],
      "source": [
        "n_lowest_bits_1 = 2\n",
        "steganography = Steganography(encoding='ascii', n_lowest_bits=n_lowest_bits_1)\n",
        "message_length, encoded_image_1 = steganography.encode(message=message, image=lenna)\n",
        "deocded_text_1 = steganography.decode(image=encoded_image_1, length=message_length)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Experiment 2"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 11,
      "metadata": {},
      "outputs": [],
      "source": [
        "n_lowest_bits_2 = 6\n",
        "steganography = Steganography(encoding='ascii', n_lowest_bits=n_lowest_bits_2)\n",
        "message_length, encoded_image_2 = steganography.encode(message=message, image=lenna)\n",
        "deocded_text_2 = steganography.decode(image=encoded_image_2, length=message_length)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Experiment 3"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 12,
      "metadata": {},
      "outputs": [],
      "source": [
        "n_lowest_bits_3 = 7\n",
        "steganography = Steganography(encoding='ascii', n_lowest_bits=n_lowest_bits_3)\n",
        "message_length, encoded_image_3 = steganography.encode(message=message, image=lenna)\n",
        "deocded_text_3 = steganography.decode(image=encoded_image_3, length=message_length)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Experiment 4"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 13,
      "metadata": {},
      "outputs": [],
      "source": [
        "n_lowest_bits_4 = 8\n",
        "steganography = Steganography(encoding='ascii', n_lowest_bits=n_lowest_bits_4)\n",
        "message_length, encoded_image_4 = steganography.encode(message=message, image=lenna)\n",
        "deocded_text_4 = steganography.decode(image=encoded_image_3, length=message_length)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Results"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {},
      "outputs": [],
      "source": [
        "# plot\n",
        "fig, axs = plt.subplots(nrows=1, ncols=5, figsize=(16, 4), layout='compressed')\n",
        "\n",
        "axs[0].imshow(lenna)\n",
        "axs[0].set_title(\"Original\")\n",
        "axs[0].axis('off')\n",
        "\n",
        "axs[1].imshow(encoded_image_1)\n",
        "axs[1].set_title(f\"lsb: {n_lowest_bits_1}bits  -  mse: {mse(lenna, encoded_image_1):.2f}\")\n",
        "axs[1].axis('off')\n",
        "\n",
        "axs[2].imshow(encoded_image_2)\n",
        "axs[2].set_title(f\"lsb: {n_lowest_bits_2}bits  -  mse: {mse(lenna, encoded_image_2):.2f}\")\n",
        "axs[2].axis('off')\n",
        "\n",
        "axs[3].imshow(encoded_image_3)\n",
        "axs[3].set_title(f\"lsb: {n_lowest_bits_3}bits  -  mse: {mse(lenna, encoded_image_3):.2f}\")\n",
        "axs[3].axis('off')\n",
        "\n",
        "axs[4].imshow(encoded_image_4)\n",
        "axs[4].set_title(f\"lsb: {n_lowest_bits_4}bits  -  mse: {mse(lenna, encoded_image_4):.2f}\")\n",
        "axs[4].axis('off')\n",
        "\n",
        "plt.show()"
      ]
    }
  ],
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      "display_name": "Python 3",
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    },
    "author_name": "Amirhossein Heydari",
    "author_email": "AmirhosseinHeydari78@gmail.com",
    "author_github": "https://github.com/mr-pylin",
    "origin_repo": "https://github.com/mr-pylin/media-processing-workshop"
  },
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