WEEK 10 FYP 1

Title: 

Method 2: Masking and Filtering

Objective:

To research and gain information about Masking and Filtering

Content/Result:

• Which can be used on 24 bit per pixel images.

• The technique can be used on both color and gray-scale images. Masking and filtering is similar to placing watermarks on a printed image. 

• There are 2 types 
• Non-detectable e-watermarks
•  e-watermarks of different grade of visibility 

• More robust than LSB insertion with respect to compression, cropping, and some image processing. 

• The carrier medium is modified a suitable way by the information to be the watermark and the colors of the pixels below the mask are modified. 

• The visibility depends upon the amount of modification.

Before Masking and Filtering

After Masking and Filtering

Conclusion:

Masking and filtering can be used on both color and gray-scale images which similar to placing watermarks on a printed image. It is more robust than LSB insertion with respect to compression, cropping, and some image processing.

WEEK 9 FYP 1

Title:
Method 1: Least significant Bit (LSB)

Objective:
To research and gain information about Least significant Bit (LSB)

Content/Result:

• 24-bit color: every pixel can have one in 2^24 colors, and these are represented as different quantities of three basic colors: red (R), green (G), blue (B), given by 8 bits (256 values) each.

• 8-bit color: every pixel can have one in 256 (2^8) colors, chosen from a palette, or a table of colors.

• 8-bit gray-scale: every pixel can have one in 256 (2^8) shades of gray.  

• LSB insertion modifies the LSBs of each color in 24-bit images, or the LSBs of the 8-bit value for 8-bit images.

• Given the following 8 carrier bytes 

                            10010101 00001101 11001001 10010110

                            00001111 11001011 10011111 00010000

         Example: Insert some payload - the letter ‘G’, in ASCII: 01000111.The resulting bytes are

                            10010100 00001101 11001000 10010110

                            00001110 11001011 10011111 00010001

         Only half of the available bytes were affected by our insertion. Change is relatively undetectable.

Original Image 

Embedded Image that contains 4826 letter

Conclusion:

Least significant Bit (LSB) is the most common technique used. It is very simple and works with both color and grayscales images.

WEEK 8 FYP 1

Title:
Grapic User Interface (GUI)

Objective:
To learn and explore about GUI in MATLAB

Content/Result:
The MATLAB GUI design system allows you to create applications consisting of one or more ‘dialogs’ containing typical ‘controls’ such as buttons, edit boxes, lists and pictures.

The most common controls are:

q       Menu options: Selection calls up an operation by name

q       Push buttons: Clicking calls up some operation

q       Edit boxes: User can enter some text or numerical value

q       List boxes: User can choose among list of items

q       Figures: Program can display graphical results

q       Text: Program can display textual result

Some of the example that I've built:

Conclusion:

Throughout this, I know how to build a simple single-figure dialog to control my application, know how to add menus, figures, text, buttons and edit boxes to my dialog and know how to associate MATLAB code to events generated by the dialog controls.

WEEK 7 FYP 1

Title:
Image Read

Objective:
To learn about Image read and write in MATLAB

Content/Result:

The continuing tutorial and exercise from previous week. I referred to http://www.mathworks.com/help/images/. This week I learn about:

1) Image Enhancement

    Contrast Adjustment, morphological filtering, deblurring and other image enhancement tools.

2) Image Analysis

    Region analysis, texture analysis, pixel and statistics

3) Color

    Color transform, support for International Color Consortium (ICC) profiles

4) Code Generation

    Generate C/C++ code and MEX functions for toolbox functions

Conclusion:

The continuing MATLAB toolbox tools from previous week, but with different function. 

WEEK 6 FYP 1

Title: 
Image Read

Objective:
To learn about Image read and write in MATLAB

Content/Result:
As my project is Image Steganography, I learn how to load an image by using MATLAB coding. There are many categories for Image Processing Toolbox in MATLAB. I refer to this link: http://www.mathworks.com/help/images/ for information and tutorial. Below are some example that I have learn.

1) Import, Export and Conversion
    Image data import and export, conversion of images types and classes

2) Display and Exploration
    Interactive tools for image display and exploration

3) Geometric Transformation and Image Restoration
    Scaling and rotation, image alignment using automatic or control point registration


Conclusion:
For this week, I'll able to load image and read it by using MATLAB. Those image can be alter depending on the task that we want to used.