An Analysis on Digital Watermarking Techniques for Several Applications
A.Jaikumar, K.Sathishkumar, W.Mesiyastalin
Department of Electronics and Communication Engineering
Dhanalakshmi Srinivasan Institute of Technology, Samayapuram, Tamil Nadu, India
Abstract: Digital watermarking plays very important position in multimedia for various applications such as copyright protection, possession safety and identification, facts authentication, broadcast monitoring etc. The goal of each and every utility is to supply protection to the digital information. Digital watermarking is a technique of embedding some facts with unique picture in the structure of text, picture etc. Digital watermarking is a very growing area and widely used in a number applications. This paper affords a assessment on extraordinary digital watermarking techniques. The watermarking methods is basically two kind e.g. spatial area or frequency area or on the groundwork of wavelets.
Keywords – Digital watermarking, Frequency domain, Discrete cosine Transform (DCT), Discrete Wavelet Transform (DWT).
I. INTRODUCTION
Digital watermarking is a method of embedding digital data called watermark into a multimedia object in such a way that watermark can be easily detected to make a decision about the objects.
It may be labeled as seen or non-visible. Example of seen watermarking is the text seen in the heritage of any document. On the other hand, non-visible watermark is hidden in the object, which can be detected by means of an licensed person. Such watermarks can use for authentication and preventing unauthorized copying. The digital photograph watermarking is the high-quality technique for multimedia copyright safety problems [1, 2]. Digital watermarking will have a number of useful applications such as digital cameras, medical imaging, image databases, and video on demand systems, and many others. Recently, lot of digital watermarking strategies has been proposed, which is based on spatial area approach and frequency area technique. These strategies are used in watermark embedding algorithm and watermark extracting algorithm [3]. Figure 1 indicates the fundamental digital watermarking system.
Fig.1 : Basic Digital Watermarking System
II. LITERATURE REVIEW
This area provides the techniques currently handy in the area of digital watermarking. It provides a review of some necessary work in the subject of digital watermarking technique. A survey of the modern-day research is introduced as well as an evaluation of the modern techniques and strategies handy for digital image watermarking are additionally presented. In 2009, J. Mei et al. [4] proposed a DWT digital watermarking algorithm primarily based on human vision characters. In this technique, all watermark pix are changed by means of the use of DCT transformation. Then this watermark picture is inserting into the HF band of the wavelet transformation domain. In 2010, C. C. Lai et al. [5] introduce a method in which the watermark is no longer inserted without delay on the wavelet coefficients but it is on the factors of singular values of the cowl image’s DWT. In 2012, N. Chaturvedi et al. [8] have compared watermarking using DWT & DWT-DCT method’s performance analysis on groundwork of PSNR.
III. WATERMARKING TECHNIQUES
Digital watermarking techniques may be categorized in spatial domain-based watermarking, frequency area primarily based watermarking and feature-based watermarking. In this paper spatial domain-based watermarking and frequency area primarily based watermarking has described.
A. Spatial domain based technique
In spatial domain based technique watermarking gadget without delay adjustments the main data elements, for example, pixels in an image. Most extensively used approach for this purpose is the LSB technique [3]. The picture is as a matrix MxN the place M and N are the dimensions of the photo and the price of the pixel in the role (i,j) is a binary number. This binary quantity can be divided into a most great bit (MSB) which contains a lot of records and a least significant bit (LSB) which includes very much less information. In LSB technique LSB of Original picture pixels are changed through MSB of watermark photo pixels. Figure 2 shows the kinds of watermarking techniques.
Fig. 2: Types of Watermarking Techniques
Following steps are used to perform LSB technique.
1. Select the authentic picture and watermark image.
2. Select the range of bits of the authentic photograph so that it can preserve the nice of the image. Image fantastic relies upon on a range of bits. If a quantity of bits are chosen then it will reduce the high-quality of the image.
3. Insert the MSB of watermark picture in LSB of the authentic image.
For instance (1111 1111 1010)
When a range a hundred and one is embedded into the least sizeable bits of this part of the image, the resulting grid is as follows:
(1111 1110 1011)
Spatial domain techniques such as LSB are simpler to implement, but they are constrained in robustness, which is no longer expected in any watermarking applications. It can be utilized in simple operation such as cropping or addition of noise.
B. Frequency area primarily based Techniques
Frequency transform area watermarking approach observe the special transformations on an image like DFT, DCT, DWT etc. and embed the watermark into coefficients through altering coefficients values. Thus strategies in this domain embed a watermark into coefficients rather than in pixel values. Fig. 3 shows the frequency based and spatial domain watermarking techniques.
Fig. 3: Frequency based and Spatial Domain Watermarking Techniques
Techniques in frequency transform domain are as follows:
Fig. 4: The proposed framework for watermark
Fig. 4 suggests the proposed watermark method in embedded form. Discrete Cosine Transformation (DCT) primarily based picture watermarking [9] is a type of seriously change whose kernel is in cosine function. It works for complicated numbers. It converts an picture from the spatial area to transform area and vice versa. When an picture is changed using DCT it divides given image into 8*8 blocks. Then it finds low and high-frequency factors by means of zigzag scanning. And then embeds a watermark in low-frequency components. This technique provides excessive robustness in opposition to JPEG compression. DCT strategies lack resistance to robust geometric attacks. Discrete Wavelet Transformation (DWT) primarily based image watermarking [10] is a decomposition technique that decomposes given photograph into
a set of primary wavelets. It provides spatial and transforms illustration of an image. DWT is a appropriate approach to discover the location in the photo that consists of the secret image.
DWT decompose given photograph into low and high-frequency elements and finds high- frequency elements and embeds an picture into high-frequency components. In DWT based totally approach frequency decision depends on frequency so when the frequency is corrupted it decreases robustness. DWT multi-resolution method decomposes given picture into 4 sub-bands –LL(High scale low-frequency components), LH (Vertical low scale high-frequency components), HL (Horizontal low scale high-frequency components), HH (Diagonal low scale high-frequency components) [10]. It embeds the watermark into LH and HL bands. This approach does no longer furnish sturdy robustness towards special types of geometric and photograph processing attacks. Discrete Wavelet Transform-Discrete Cosine Transform based totally hybrid watermarking (DWT-DCT) is hybrid watermarking approach is used that combines DWT and DCT. In this approach first DWT is applied to the host photo up to special tiers followed through DCT and then applies extraordinary sorts of attacks. As the wide variety of stage will increase the size of watermark decreases and PSNR will increase [10].In this method, mark photograph is elevated with a deviation of host picture so high-quality degrades very slowly. This approach gives excessive PSNR and can extract high great and massive marks. It does not change the view of the host image. This method satisfies the necessities of robustness. Combined Discrete Wavelet Transform (DWT)-Discrete Cosine Transform (DCT)- Singular Value Decomposition (SVD) primarily based watermarking [9] is a combined approach of DWT, DCT, and SVD. It mixed in a zigzag way to satisfy the requirement of robustness. First DWT is utilized on host image which decomposes the given image into four bands. And then DCT is utilized on HH band and map the DCT coefficient the usage of zigzag scanning and then applies SVD to get singular cost coefficients. The equal procedure is then applied on watermark image. Extraction is the equal as embedding however works in a reverse manner. This technique affords desirable robustness. But complexity increases as the procedure of software of DWT, DCT, SVD and IDWT, IDCT, and inverse SVD.
IV. CONCLUSION
Watermark embedding and extraction algorithms are required for presenting copyright safety and ownership identification and other security purpose. This paper presents a quick survey on more than a few digital watermarking strategies in distinct domains and their requirements. In this paper, unique watermarking techniques are categorized with their requirements, advantages and limitations. It has been concluded that to reduce distortions and to make bigger capability, methods in frequency or seriously change area must be combined with different techniques.
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