Detail Study on Watermarking Techniques Proposed Wavelet based Watermarking and Prototype Development for Protecting Digital Images

Dr. Dheyaa Shaheed Al-Azzawi, Dr. Sinan Adnan Diwan, Muslem Muhamed Mahdi Al-Saidi and Jamal Kh-Madhloom

In today’s technology enabled world, digital images, audio, video are frequently distributed on the internet. Rapid growing of digital media have brought a new challenge in duplication and manipulation of multimedia digital content. There is a necessity to have an intellectual property rights protection for multimedia contents to overcome duplication in the digital world. Digital watermarking technology plays a significant role in securing multimedia contents by embedding with imperceptible marks to identify the real owner, track the illegal users and detect malicious tampering in the multimedia documents. In this research paper, detail technical study on watermarking techniques for protecting digital images with the main focus on authentication, robustness for security communication and verification has been described in detail. To determine the content users from illegal distribution of data, digital logo based watermarking is applied in the proposed study, i.e. multimedia content is embedded with legitimate logo by owner and carried out by applying frequency domain approach, which is known as wavelet transformation which can understand more on human visual system compared to other transformation techniques applied in digital watermarking. The proposed watermark design in this paper is based on wavelet based coding which has sub-band coding which includes approximate sub-bands(LL) and detailed sub-bands (HH, HL and LH), which are used for embedding and extracting the watermarks. The proposed design is at initial stage with the pilot prototype implemented in matlab which undergoes various experimental attacks such as Gaussian noise, median filtering, resizing, histogram equalization and JPEG compression. Experimental results have shown that wavelet watermark is robust to several signal processing techniques and image processing operation. To check the proposed study with existing methods, different quality measures have been evaluated such as Mean Square Error, Average Absolute Difference and Peak Signal to Noise Ratio.

Volume 12 | 03-Special Issue

Pages: 284-296

DOI: 10.5373/JARDCS/V12SP3/20201264