Novel Multiple Spatial Watermarking Technique in Color Images

Watermarking has established itself as a promising solution in the context of digital image copyright protection. Frequency domain watermarking is mainly preferred due to associated robustness and perceptual issues but requires a large amount of computation. On the other hand spatial domain watermarking is much faster but lacks when robustness is concerned. In this paper a block based spatial domain watermarking technique for color images is proposed that is fast and robust. Two-way embedding introduced in the paper provides capability to previously estimate perceptual degradation in host image due to watermark embedding. Multiple watermarking in two component images is used to achieve better imperceptibility and better robustness. Self-encryption introduced aims to remove dependency over external secret key however optional encryption with random secret keys is proposed for providing better security. Proposed embedding technique is an effort to achieve proper balance between robustness and quality degradation of image. Experiments suggest proposed method is robust against processing attacks such as spatial filtering transformations image enhancement and loss compression.

Zernike Moments (ZMs) are used in many image processing applications, due to their resistance against various signal processing and geometric attacks. Digital image watermarking is one of those application areas, where ZMs are widely used to insert and extract the watermark bits for digital media authentication. In all the existing ZM based watermarking techniques, magnitude of moments is used to insert and extract the watermark. In this paper, the authors’ have proposed a semi blind watermarking technique in which phase of ZMs is used for watermark insertion and extraction. Due to the use of phase of ZMs, 100% detection ratio is achieved against any geometric and other signal processing attacks. To make the proposed technique fast, q-recursive method is used to compute the Zernike polynomials. The use of q-recursive method has also increased the transparency of watermark due to its better reconstruction ability as compared to traditional moment computation method. Through detailed experimentation, it has been confirmed that the proposed watermarking technique is fast, has more imperceptibility, less Bit Error Rate (BER) and more capacity as compared to traditional ZMs magnitude based watermarking technique.

We propose in this paper a discrete wavelet transform (DWT) based digital image watermarking technique. For embedding process, we consider the watermark signal as a binary sequence which is embedded to the high (HL and HH) frequency band of the blue channel. For detecting process, the correlation between the high frequency band DWT coefficients of the watermarked image and the watermark signal is compared with the predefined threshold to determine whether the watermark is present or not. The experimental results show that the method is comparatively robust to several attacks such as rotation, scaling, JPEG compression, cropping, and multiple watermarking.

Medical images are now almost all gathered and stored in a digital representation for easy transmission and archiving. High resolution is mandatory for a detailed diagnosis, which requires accurately known location and density information regarding the important features of the image called the regions of interest (ROI). Such features may include non-displaced fractures or small tumors that can often be difficult to identify. A reduction in size by using compression is necessary for efficient transmission over a wireless link where remote diagnosis may be an only option in many cases. Despite rapid advances in lossy compression, most research in the compression of medical imagery specifies that the ROI must be conserved as much as possible or compressed with a lossless or near-lossless algorithm. To ensure diagnostic integrity of these crucial regions after transmission, a multiple watermarking technique has been developed which can be used to verify the integrity of the ROI prior to diagnosis. This has the benefit of assuring that incidental degradation has not affected any of the crucial regions. A strong focus is placed on the robustness of the watermarking technique to JPEG compression as well as the issue image file size and quality tradeoff. The most useful contribution in our work is assurance of ROI image content integrity after image files are subject to incidental degradation in these environments. This is made possible with extraction of DCT signature coefficients from the ROI and embedding multiply in the Region of Backgrounds (ROB).

We present a new image watermarking technique for color images. Tradeoff between imperceptibility, robustness, and security is achieved by this technique. This technique is based on discrete wavelet transform (DWT) and singular valued decomposition (SVD). Advantage of both DWT and SVD has been utilized to achieve more robustness. Differential evolution (DE) is used for optimization of scaling factors. DE is incorporated to find optimal scaling factors to scale down the watermark and increase the visual quality and robustness of watermarked image. Color cover image is split into three color channels using RGB color space. To improve the security, watermark is scrambled before embedding using random Bit-Plane and XOR operation. Experimental results show that the watermarked image is imperceptible and resistant to various geometric attacks and image processing.

Watermarking technique is a method to protect ownership of digital multimedia. Most existing watermarking techniques achieve a good level of imperceptibility and robustness. The challenges to achieve higher invisibility and resistance with lower computational time motivate researchers to work on new watermarking schemes. Robustness against noise attacks and JPEG2000 compression needs to be improved to acquire a better resistance capability of the watermark. In this paper, we present a block-based Tchebichef watermarking technique for protecting copyrights. In this technique, the host image is first divided into non-overlapping blocks and Tchebichef moments are calculated for each block. The watermarks are embedded into the blocks with lower visual entropies. The watermark image is scrambled by Arnold transform before embedding into the Tchebichef moments of the selected image blocks. The proposed watermarking scheme was tested under noise additions, filtering, cropping and compressing attacks. Our scheme was verified and compared to the existing watermarking techniques under image geometric and processing attacks. Furthermore, the proposed scheme demonstrated a superior performance in robustness under noise attacks and JPEG2000.

Prior research studies have shown that the peak signal to noise ratio (PSNR) is the most frequent watermarked image quality metric that is used for determining the levels of strength and weakness of watermarking algorithms. Conversely, normalised cross correlation (NCC) is the most common metric used after attacks were applied to a watermarked image to verify the strength of the algorithm used. Many researchers have used these approaches to evaluate their algorithms. These strategies have been used for a long time, however, which unfortunately limits the value of PSNR and NCC in reflecting the strength and weakness of the watermarking algorithms. This paper considers this issue to determine the threshold values of these two parameters in reflecting the amount of strength and weakness of the watermarking algorithms. We used our novel watermarking technique for embedding four watermarks in intermediate significant bits (ISB) of six image files one-by-one through replacing the image pixels with new pixels and, at the same time, keeping the new pixels very close to the original pixels. This approach gains an improved robustness based on the PSNR and NCC values that were gathered. A neural network model was built that uses the image quality metrics (PSNR and NCC) values obtained from the watermarking of six grey-scale images that use ISB as the desired output and that are trained for each watermarked image’s PSNR and NCC. The neural network predicts the watermarked image’s PSNR together with NCC after the attacks when a portion of the output of the same or different types of image quality metrics (PSNR and NCC) are obtained. The results indicate that the NCC metric fluctuates before the PSNR values deteriorate.

A novel secure and robust image watermarking technique for color images is presented in this paper. Besides robustness and imperceptibility (which are the most important requisites of any watermarking scheme), there are two other challenges a good watermarking scheme must meet: security and capacity. Therefore, in devising the presented scheme, special consideration is also given to above-mentioned requirements. In order to do so, principal component analysis is involved to enhance imperceptibility and the unique utilization of singular value decomposition is done to achieve better performance in regard to capacity and robustness. Finally, a novel method is proposed to select constituents of an image for watermark embedding, which further improves the security. As a consequence, four essential requisites of a good watermarking scheme are achieved as visible from experimental results. To measure the behavior of presented watermarking scheme, a number of experiments were conducted by utilizing several color images as host images and as watermarks. The presented technique is compared with the latest available watermarking techniques and attained better results than them.

With advances in machine learning and development of neural networks that are efficient and accurate, this paper explores the use of kernel extreme learning machine (KELM) to develop a semi-blind watermarking technique for grey-scale images in discrete cosine transform domain. Fuzzy entropy is employed for selection of the blocks where the watermark bits are to be embedded. A dataset formed from these blocks is used to train KELM. The nonlinear regression property of KELM predicts the values where watermark bits are embedded. Self-adjustive differential evolution (SeAdDE) controls the strength of the scaling factors finds their optimal values. The adaptiveness of differential evolution (DE) helps in self-adjustment and varies the DE parameters to explore best solutions. This saves time as the manual hit and trial method for finding the appropriate parameter values is avoided. The scheme presented shows robustness against various attacks like histogram equalisation, resizing, JPEG compression, Weiner filtering, etc. and still also retains the quality of the watermarked image. Thus, the proposed technique can be used as a solution to ensure authenticity via watermarking.

Multiple watermarking technique for securing online social network contents using Back Propagation Neural Network

In the current digital era, patient data in the form of digital medical images in several hospitals are widely used. There are two important thin to use of digital medical images namely the ownership authority (integrity control) and the authenticity of the image (authentication), because digital medical images are very easily manipulated. To maintain the authority of ownership, it needs robust watermarking techniques in which the embedded data is not easily damaged if the image has been manipulated. Meanwhile, to detect the authenticity of the image, it needs fragile watermarking technique in which the embedded data is easily damaged if the image has been manipulated. In this paper, we implement Reed-Solomon code for robust watermark in wavelet domain and SHA-256 for fragile watermark in Hash Block Chaining. The proposed multiple watermarks can be implemented simultaneously on an image so that the integrity control and authenticity of the image detection can be applied at once.

This paper presents an improved watermarking detected algorithm for color image based on a block probability in spatial domain. A binary watermark image is permutated using sequence numbers generated by a secret key and Gray code, and then embedded four times in different positions by a secret key. Each bit of the binary encoded watermark is embedded by modifying the intensities of a non-overlapping block of 8*8 of the blue component of the host image. In watermarking extract scheme, the scale invariant features of images are extracted, and the match points between the watermarking image and the reference image are found. Then the watermarking image is corrected by affine transform of these match points. The improved extraction method of the watermark is by comparing the intensities of a block of 8*8 of all components of the watermarked and the original images and calculating the probability of detecting binary watermark. Tested by benchmark Stirmark 4.0, the experimental results show that the algorithm is robust against various kinds of attacks such as Affine, Rotating, Cropping, Scaling, JPEG compression, Mean filtering and so on.

Generally, existing watermarking techniques are fragile in geometric distortion and have difficulty in detecting artificial manipulation of digital data. In this paper, we propose a robust watermarking technique in geometric distortion of digital images. The proposed watermarking technique embeds the watermark by modifying phase information in the complex wavelet domain about an original image. A watermark is extracted with a hierarchical from a watermarked image, and a correlation is compared. The watermarking technique using the Complex Wavelet Transform is compared with the watermarking technique which uses the existing wavelet transformation was used for performance evaluation, and proposed techniques showing a robust on a geometric distortion.

This chapter presents an improved robust and imperceptible hybrid watermarking technique for medical images using fusion of DWT, DCT and SVD instead of applying DWT, DCT and SVD individually or combination of DWT-DCT, DWT-SVD, and DCT-SVD. In the embedding process, the host image is decomposed into first level discrete wavelet transforms where the low frequency band (LL) is transformed by DCT and SVD. The watermark image is also transformed by DCT and SVD. The ‘S’ vector of watermark information is embedded in the ‘S’ component of the host image. The watermarked image is generated by inverse SVD on modified ‘S’ vector and original U, V vectors followed by inverse DCT and inverse DWT. The watermark is extracted using an extraction algorithm. The performance of proposed technique is also tested by using the benchmark software 'Checkmark' and the technique is found to be robust against the 'Checkmark' attacks. Moreover, the performance of proposed algorithm has also been evaluated for multiple watermarking. The proposed multiple watermarking method preventing the problem of patient identity theft and health data management issues in the healthcare applications.

This research presents contextual digital watermarking techniques using face and demographic text data as multiple watermarks for protecting the evidentiary integrity of fingerprint image. The proposed techniques embed the watermarks into selected regions of fingerprint image in MDCT and DWT domains. A general image watermarking algorithm is developed to investigate the application of MDCT in the elimination of blocking artifacts. The application of MDCT has improved the performance of the watermarking technique compared to DCT. Experimental results show that modifications to fingerprint image are visually imperceptible and maintain the minutiae detail. The integrity of the fingerprint image is verified through high matching score obtained from the AFIS system. There is also a high degree of correlation between the embedded and extracted watermarks. The degree of similarity is computed using pixel-based metrics and human visual system metrics. It is useful for personal identification and establishing digital chain of custody. The results also show that the proposed watermarking technique is resilient to common image modifications that occur during electronic fingerprint transmission.