The Internet as a whole does not use secure links, thus information in transit may be vulnerable to interruption as well. The important of reducing a chance ofthe information being detected during the transmission is being an issue in the real world now days. TheDigitalwatermarking method provides for the quick and inexpensive distribution ofdigital information over the Internet. This method provides new ways of ensuring the sufficient protectionofcopyright holders in the intellectual property dispersion process. The property ofdigitalwatermarkingimages allows insertion of additional data in theimage without altering the value oftheimage. This message is hidden in unused visual space in theimageand stays below the human visible threshold for theimage. Both seek to embed information inside a cover message with little or no degradation ofthe cover-object. In this paper investigate the following relevant concepts and terminology, history of watermarks andthe properties of a watermarking system as well as a type ofwatermarkingand applications. We are proposing edge detection using Gabor Filters. In this paper we are proposed least significant bit (LSB) substitution method to encrypt the message in the watermark image file. The benefits ofthe LSB are its simplicity to embed the bits ofthe message directly into the LSB plane of cover-imageand many techniques using these methods. The LSB does not result in a human perceptible difference because the amplitude ofthe change is little therefore the human eye the resulting stego image will look identical to the cover imageand this allows high perceptual transparency ofthe LSB. The spatial domain technique LSB substitution it would be able to use a pseudo-random number generator to determine the pixels to be used for embedding based on a given key. We are using DCT transform watermark algorithms based on robustness. Thewatermarking robustness have been calculated by the Peak Signal to Noise Ratio (PSNR) and Normalized cross correlation (NC) is used to quantify by the similarity between the real watermark and after extracting watermark.
Sudeb  describes about a non-blind imperceptible and highly robust hybrid Medical ImageWatermarking (MIW) technique for a range of medical data management issues. He used CLT followed by DCT to achieve higher robustness and imperceptibility. The drawback of this work is degradation ofimageand extraction accuracy. Mohamed Ali Hajjaji  proposed an approach for Watermarkingimage based on the techniques of Code Division Multiple Access (CDMA), Discrete Wavelet transform (DWT) and Error Correcting Code (ECC) in order to contribute to security sharing and transmission of medical images. This approach improves the quantity of data integration with the conservation oftheimage visual quality and permits the user, to correct the any alterations if it exists. In this work, the hash function MD5 is used to improve the message integrity andthe CDMA to increase the number of bits to insert & BCH code is used as an Error Correcting Code in order to correct the eventual errors that may occur due to various attacks. The disadvantage of this approach is that, in the case of Gaussian noise attack the received message undergoes different alterations and also the major inconvenient of this method is the use of different layers, key, and this becomes binding when dealing with a large number ofimages.
In this paper a new robust watermarkingtechnique for copyrightprotection has been proposed. We applied the singular value decomposition along with the Discrete Wavelet Transform. Since thetechnique utilizes the properties of both DWT and SVD the proposed technique is more robust against different attacks. The innovation of this paper is that the security ofthe algorithm is increased with the help of visual cryptography on the watermark image. If the second share ofthe watermark which acts as the key is not present then it is not possible to extract the exact watermark information. It is very difficult to change or remove the watermark without knowing the secret key share as the watermark is split into two shares with random patterns. The robustness ofthetechnique is justified by giving analysis ofthe effect of attacks and still we are able to get good visual quality ofthe embedded watermark.
, andcopyrightprotection. Robustness, invisibility and security are the three most important properties that need to be satisfied for such applications .When watermarking is done by digital means we refer to digitalwatermarking .Thedigitalwatermarking is a new developed former technology of information security. There have been many applications for digitalwatermarking in many fields such as digitalimages, video, audio and so on. For vector geo-spatial data there were a few studies on thedigitalwatermarking . Imagewatermarking, video watermarkingand audio watermarking are enlisted as categories ofDigitalwatermarking in accordance to the range of application . An important aspect of any Watermarking scheme is its robustness against attacks. The notion of robustness is intuitively clear. Robustness is the capacity of tolerance of attacks on the watermarked data. A watermark is robust if it cannot be impaired after rendering the attack on the data. Based on robustness, watermarking scheme can be divided into fragile, semi-fragile and robust . Some ofthe applications where digitalwatermarking can be effectively utilized are Digitalcopyrightprotection, Transaction tracing and fingerprinting, Digital content management, Digital content authentication and verification, Lyric sync services .
The Discrete Wavelet Transform (DWT) is currently used in a wide variety of signal processing applications, such as in audio and video compression, removal of noise in audio, andthe simulation of wireless antenna distribution. Wavelets have their energy concentrated in time and are well suited for the analysis of transient, time- varying signals. Since most ofthe real life signals encountered are time varying in nature, the Wavelet Transform suits many applications very well . We use the DWT to implement a simple watermarking scheme. The 2-D discrete wavelet transforms (DWT) decomposes theimage into sub-images, 3 details and 1 approximation. The approximation looks just like the original; only on 1/4 the scale. The 2-D DWT is an application ofthe 1-D DWT in both the horizontal andthe vertical directions. The DWT separates animage into a lower resolution approximation image (LL) as well as horizontal (HL), vertical (LH) and diagonal (HH) detail components. The low-pass and high- pass filters ofthe wavelet transform naturally break a signal into similar (low pass) and discontinuous/rapidly- changing (high-pass) sub-signals. The slow changing aspects of a signal are preserved in the channel with the low- pass filter andthe quickly changing parts are kept in the high-pass filter’s channel. Therefore we can embed high- energy watermarks in the regions that human vision is less sensitive to, such as the high-resolution detail bands (LH, HL, and HH). Embedding watermarks in these regions allow us to increase the robustness of our watermark, at little to no additional impact on image quality . The fact that the DWT is a multi-scale analysis can be used to thewatermarking algorithm’s benefit.
Abstract: The proliferation of digitized media due to the rapid growth of networked multimedia systems, has created an urgent need for copyright enforcement technologies that can protect copyright ownership of multimedia objects. Digitalimagewatermarking is one such technology that has been developed to protect digitalimages from illegal manipulations. In particular, digitalimagewatermarking algorithms which are based on the discrete wavelet transform have been widely recognized to be more prevalent than others. This is due to the wavelets' excellent spatial localization, frequency spread, and multi-resolution characteristics, which are similar to the theoretical models of
This paper introduces the concept ofimage fusion technique for impulse noise reduction in digitalimages. Image fusion is the process of combining two or more images into a single image while retaining the important features of each image. Multiple image fusion is an important technique used in military, remote sensing and medical applications. Theimages captured by two different sensors undergo filtering using vector median or spatial median filter based on the noise density in theimage. The filtered images are fused into a single image, which combines the uncorrupted pixels from each one ofthe filtered image. The fusion algorithm is based on Bi- dimensional Empirical Mode Decomposition (BEMD), which decomposes animage into residue and IMF components. Different fusion rules are used to combine IMFs and Residual components. Finally, theimage is recovered using inverse BEMD. The performance evaluation ofthe fusion algorithm is evaluated using structural similarity index (SSIM) between original and fused image. Experimental results show that this fusion algorithm produce a high quality image than individually filtered image.
In recent years, data protection is one of important aspect because of cases like piracy, copyrightand ownership issues. Digital watermark seems to be solution to the problem. In our paper, we proposed a method of invisible watermark to medical image using Biorthogonal wavelet filter and transformed domain watermark embedding. Generally watermark is embedded in original image either directly or in transform of original image. In our method, we transformed both original imageand watermark using discrete wavelet transform and Biorthogonal wavelet filter coefficients. We specifically follow this method considering the case of medical images. As medical images are low contrast imagesand are taken at high precision with special equipment, so it is not expected that any one will claim for its ownership. Hence we tried to develop a method which will recover watermark through medical image considering any kind of attacks. We tested our method on multiple medical imagesand listed down results and comparison is made on basis of PSNR and normalised correlation (NC). From the values of NC, we concluded that our method gives better recovery of watermark from watermarked image.
Abstract – Neural Networks offer the potential for providing a novel solution to the problem of data compression by its ability to generate an internal data representation. This network, which is an application of back propagation network, accepts a large amount ofimage data, compresses it for storage or transmission, and subsequently restores it when desired. A new approach for reducing training time by reconstructing representative vectors has also been proposed. Performance ofthe network has been evaluated using some standard real world images. Neural networks can be trained to represent certain sets of data. After decomposing animage using the Discrete Cosine Transform (DCT), a two stage neural network may be able to represent the DCT coefficients in less space than the coefficients themselves. After splitting theimageandthe decomposition using several methods, neural networks were trained to represent theimage blocks. By saving the weights and bias of each neuron, by using the Inverse DCT (IDCT) coefficient mechanism animage segment can be approximately recreated. Compression can be achieved using neural networks. Current results have been promising except for the amount of time needed to train a neural network. One method of speeding up code execution is discussed. However, plenty of future research work is available in this area it is shown that the development architecture and training algorithm provide high compression ratio and low distortion while maintaining the ability to generalize and is very robust as well.
In the last decade, a non-contacting optical technique, digitalimage correlation, has been developed by Sutton et al. (1983, 1986, 1988, 1991) and Bruck, et al. (1989). It was applied to measurement of displacements and strains. The applications include microscopic strain measurements in electronic packaging (Lu, 1998), strain fields in polyurethane foam plastic materials and evaluation of their mechanical properties (Zhang, Zhang and Cheng, 1999), and evaluation of thermal strain in the solder joints (Lu, Yeh and Wyatt, 1998). This methodology was even used for in situ evaluation ofthe state of conservation of mural frescoes (Spagnolo, et al., 1997). This computer vision technique has the advantages of a simple system and direct sensing and thus avoids the laborious interpretation of interferometric fringes. Thetechnique utilizes two similarly speckled images, which were captured by a solid state video camera, to represent the states ofthe object before and after deformation. By utilizing the concept of digitalization, one can characterize theimage by the patterns of different levels of light intensity. Both ofthe digitized images are then correlated by an algorithm, based on their mutual correlation coefficient or other statistical functions, to find out the subtle differences between them. The core ofdigitalimage correlation in this application depends on the ability to recognize two nearly similar, yet different, image patterns. Nevertheless, one could always use brute force (blanket method) to correlate both images grid by grid to their desired accuracy (Cardenas-Garcia, Yao and Zheng, 1993), but the consumption of CPU time would be enormous and impractical. Therefore, an efficient method to optimize the algorithm is needed
A novel technique for detecting defects in fabric image based on the features extracted using a new multi resolution analysis tool called digital curvelet transform is proposed in . The extracted features are direction features of curvelet coefficients and texture features based on GLCM of curvelet coefficients. K-nearest neighbor is used as a classifier for detecting the surface. A new method to detect the defect of texture images by using curvelet transform is presented in . The curvelet transform can easily detect defects in texture, like one-dimensional discontinuities or in two dimensional signal or function ofimage. The extracted features are energy and standard deviation of division sub-bands.
In the scheme, the host image is converted into YUV channels; then, the Y channel is decomposed into wavelet coefficients. For more security of watermark, the watermark W is converted to a sequence and then a random binary sequence R of size n is adopted to encrypt the watermark, where n is the size ofthe watermark using a pseudo-random number generator to determine the pixel to be used on a given key. The selected details subbands coefficients for embedding are quantized and then their most significant coefficients are replaced by the adopted watermark using the correlation properties of additive pseudo-random noise patterns. To embed the watermark coefficients for completely controlling the imperceptibility andthe robustness of watermarks, anadaptive casting technique is utilized using a gain factor k. Also, the CDMA watermark scheme has no need to original Image in extracting process. The observations regarding the proposed watermarking scheme are summarized as follows: (1) Increasing gain factor k increases the PSNR and NC. In a result, it decreases the percentage of error bit and increases the robustness ofthe watermark against JPEG compression and different noise attacks such as Gaussian and salt & pepper. In opposite, increasing gain factor k, decreases the transparency property.(2) The robustness ofthe proposed scheme to JPEG compression
Targeting Techniques  i.e. how relay characteristics can be segmented on memory. The paper by Girgis  et al described theadaptive scheme for digital differential protectionof power transformer by Kalman filtering taking account theadaptive percentage differential characteristics. Anadaptive setting concept for two and three terminal lines, which can respond to changes in the network conditions, was proposed by Xia et a1 [4,5]. Sometimes the distance relay measure incorrect impedance to the fault for remote end infeed. Paper by Moore et al  & by Jamali  described theadaptivetechnique for measuring the correct impedance during fault. Papers by Sachdev et al  described the techniques ofadaptive data windows. A recent paper by Hu et al  introduced thetechnique for graphical representation ofdigital relay.
multimedia he wants to use  . This will no degrade the quality due to loss of frames but also there is a loss of important information. This attack tests the efficiency ofwatermarking such that how watermarked can be removed from animage such that no quality is lost. Her if the watermarked is removed easily that means thetechnique is not robust. It is given by following example
In this paper we will focus on a technique that will protect a video from illegal access by embedding both visible and invisible watermarks into it. An invisible watermark protects a video from being copied and manipulated from the internet, but if someone takes a copy of that video using a camera then he will be able to claim it as his own video. To protect the video from this type of attacks, a visible watermark will be incorporated in the video which will appear in the video frames randomly depending upon the system and will be partially visible. DWT is used to embed the watermark in the video frames imperceptibly. The visible watermark is embedded depending on the user’s choice or randomly. As the video contain both invisible and visible watermarks so this algorithm will provide more security to the owner's video.
The algorithm in this paper, not only objective BCR value of watermark could be enhanced, but also subjective identification capability for watermark could be enhanced. The transparency of watermark was improved through embedding in the low frequency part of wavelet transformation. Besides, the key of watermark made by Toral Automorphism can reduce the demand of original image size in extraction. Therefore, it is robust to compete against compression, resize, blurring and sharpening attacks after experiments. The mixed techniqueof DWT and DCT with Toral Automorphism can enhance the robustness ofwatermarking for digitalimages.
There are some built-in applications in some ofthedigital cameras. Each application allows the user to embed a fragile watermark into the photos produced by thedigital camera. If anyone changes the photos by modifying the pixel values, then this fragile watermark is broken. However, the robust watermark is used very often for copyright marks because it is not easily being attacked. For example, if we embed a robust watermark throughout a picture, the ownership ofthe picture can be secured by this copyright mark, Perter (2002) and Petitcolas et al (1999). Watermarks can also be divided into informed and blind watermarks by using different detection techniques. Informed watermark can only be detected by comparing watermarked imageandthe original image. Blind watermark does not depend on original image. Therefore, blind watermarking is a technique that the original image is not needed in watermark extraction process. Internet digital information protection is achieved through blind watermarking because with watermarked information, message can be detected successfully without original data.
In this paper we propose a DWT based dual watermarkingtechnique wherein both blind and non-blind algorithms are used for thecopyrightprotectionofthe cover/host imageandthe watermark respectively. We use the concept of embedding two watermarks into the cover image by actually embedding only one, to authenticate the source imageand protect the watermark simultaneously. Here the DWT coefficients ofthe primary watermark (logo) are modified using another smaller secondary binary image (sign) andthe mid- frequency coefficients ofthe cover/host image. Since the watermark has some features of host image embedded in it, the security is increased two-fold and it also protects the watermark from any misuse or copy attack. For this purpose a new pseudorandom generator based on the mathematical constant π has been developed and used successfully in various stages ofthe algorithm. We have also proposed a new approach of applying pseudo-randomness in selecting the watermark pixel values for embedding in the cover image. In all the existing techniques the randomness is incorporated in selecting the location to embed the watermark. This makes the embedding process more unpredictable. The cover image which is watermarked with the signed-logo is subjected to various attacks like cropping, rotation, JPEG compression, scaling and noising. From the results it has been found that it is very robust and has good invisibility as well.
Digitalwatermarking is a technique for protecting intellectual property ofdigital information. A signature, called a watermark, is embedded into a protected image. When piracy happens, the author can extract the watermark to prove his ownership. However, when a work is created by multiple authors, digitalwatermarking may suffer some problems. If each author embeds his/her watermark, it is highly probable that the latter watermark will compromise the former one. Some papers proposed different copyrightprotection schemes from watermarking, which is suitable for a co-authored work and without the drawback mentioned above –, . In those papers, anyone who participates in the creation can prove the ownership ofthe work by oneself. However, it is reasonable that none ofthe authors is allowed to prove the ownership alone since all authors own the work jointly. Therefore, when dealing with a co-authored work, we may need an appropriate copyrightprotection scheme to avoid such problems.
GSD, which used for spatial resolution of satellite images, indicates topographic distance per each pixel but it is not sufficiently to describe image interpretability. On the other hands, GRD and NIIRS are representative parameters for image interpretability. GRD means the smallest size ofthe object that should be able to discern within imagesand NIIRS is defined the type of object that should be able to identify. Therefore, in this study, we will consider these parameters for analysis ofthe effects ofimage quality on digital map generation from satellite images.