Image Watermarking In DCT, DWT and Their Hybridization Using SVD: A Survey Ramandeep Kaur 1 and Harpal Singh 2 1 Research Scholar, Department of Electronics and Communication Engineering 2 Faculty, Department of Electronics and Communication Engineering 1,2 Rayat Bahra Institute of Engineering & Bio-Technology, Kharar, Punjab, India Abstract- Digital watermarking is one of the vital solution for protecting the intellectual property rights, copy control and content verification. It involves lot of human efforts, cost and time for their protection. Digital watermarking by hybridizing the various transforms along with singular value decomposition (SVD) has gained substantial attention due to development of efficient techniques which increases the performance. In this paper, an exhaustive survey has been done on digital image watermarking based on Discrete Cosine Transform (DCT) and Discrete Wavelet Transform (DWT) hybridization with SVD. Although there are standard algorithms for watermarking which proves their robustness but still a lot of things like principal component analysis, redundant and feature extraction based hybridization of transform in place of SVD need to be explored in order to enhance the performance. Keywords – Digital Watermarking, DCT, DWT, SVD, Hybrid Watermarking I. INTRODUCTION The internet technology has made the access of digital data very simple for communication and distribution. Digital multimedia contents like video, audio and images are conveniently available on internet which increases the unlawful operations like copyright violation, forgery, modification and duplication. Digital watermarking as one of the solution comes to our salvage for protecting these operations. In this technique, message such as image, audio, video or text can be embedded within the digital media in such a manner that it should not cause degradation to the original digital media. According to domain, watermarking techniques are distinguished into two classes: Spatial domain method and the Frequency domain method. In Spatial domain, the watermark is embedded into the host image by directly modifying the pixels value i.e. to embed the watermark into Least Significant bit (LSBs) of the host image. Spatial domain watermarking is easy to implement but it often fails under the attacks of signal processing such as filtering, cropping, compression, rescaling and having low bit capacity. In Frequency domain method, the watermark that embedded is more effective and is more robust to different attacks as compared to spatial domain method. The watermark is embedded into transform coefficients of host image after applying DFT, DCT and DWT transform. The rest of the paper is organized as follows. An exhaustive Literature survey image watermarking are explained in section II. Based upon the literature survey, conclusions are given in section III. II.LITERATURE SURVEY In this section, work done in area of Digital Watermarking and also its techniques is reviewed. According to A. Abdulfetah et. al in [1], a robust quantization based digital image watermarking for copy right protection in DCT-SVD domain works well. They proposed watermarking algorithm which combines both merits of the algorithm based on DCT and algorithm based on SVD. The watermark was embedded by applying a quantization index modulation process on largest singular values of image blocks in the DCT domain. Navas K A et. al discusses in [2] that about a method of non-blind transform domain watermarking based on DWT-DCT-SVD. In this method, the DCT coefficients of the DWT coefficients were used to embed the watermarking information. This method of watermarking was found to be robust and the visual watermark was recoverable without only reasonable amount of distortion even in the case of attacks. Thus the method can be used to embed copyright information in the form of a visual watermark or simple text. Deepa Mathew describes in [3] regarding the Singular Value Decomposition (SVD) based image watermarking scheme. She claims that the output result of SVD is more secure and robust. In this scheme, D and U components are used for embedding the watermark. Unlike other transforms which uses fixed orthogonal bases, SVD uses non fixed orthogonal bases. The result of SVD gives good accuracy, good robustness and good imperceptibility in resolving rightful ownership of watermarked image. International Journal of Innovations in Engineering and Technology (IJIET) Volume 4 Issue 4 December 2014 376 ISSN: 2319 – 1058