BLOCK-BASED DISCRETE WAVELET TRANSFORM SINGULAR VALUE DECOMPOSITION IMAGE WATERMARKING SCHEME USING HUMAN VISUAL SYSTEM CHARACTERISTICS AND FIREFLY ALGORITHM

Abstract

Digital image watermarking has gained a great interest in last decade among researchers. Having such a great community which provide a continuously growing list of proposed algorithms, it is rapidly finding solutions to its problems. However, still we are far away from being successful. Therefore, more and more people are entering the field to make the watermarking idea useful and reliable for digital world. Of these various watermarking algorithms, some outperform others in terms of basic watermarking requirements like robustness, invisibility, processing cost, etc.

In this thesis, we study a new hybrid block-based image watermarking scheme which when combined with firefly algorithm provides us better results. Following illustrative points are made to describe the thesis in a nutshell which will later on be discussed in detail.

• Firstly we divide our watermark in 32x32 blocks. This needs to be done because we need top 1024 blocks of our host image with lowest human value system characteristics i.e lowest entropy values and lowest edge entropy values.

• Our host image is divided into 8x8 blocks. Total 64 rows and 64 columns are there of 8x8 blocks. In total 64x64x8 blocks of host image i.e the size of host image is 512x512.

• Now we generate a random threshold. This threshold is used in embedding and extraction algorithm. Using Human Value System characterstics, i.e choosing best 1024 lowest entropy blocks, we perform embedding and extraction on host image.

• This embedding and extraction is done using Discrete Wavelet Transform and Singular Value Decomposition algorithm, which is explained in later chapters.

• Now using this embedded image we find PSNR value and using the extracted watermark image we find correlation values.

• Firefly Algorithm is performed using these PSNR and Correlation values i.e a fitness function is found for each threshold we generated previously. This fitness value defines the best value of threshold which we require for best embedding and extraction procedure. This algorithm is explained later on in detail.

(v) • We find best value of threshold using this Firefly Algorithm. Also we get the best extracted watermark image using this algorithm.

• In a nutshell, this project has combined four major algorithms to generate best results possible. These adopted criteria significantly contributed to establishing a scheme with high robustness against attacks without affecting the visual quality of the image.

To describe it briefly the project consists of following four subsections-

1. Discrete Wavelet Transformation (DWT)

2. Singular Value Decomposition (SVD)

3. Firefly Algorithm (FA)

4. Human Value System Characterstics (HVS