Essay On Image Annotation

Steganography in the context of digital content piracy serves primarily as a method to track where digital assets are moving or who is receiving them. It can be a good solution for distribution of a small number of copies but becomes less effective when distributing on a wide basis. In order for it to be effective a content provider needs to recover the content by means of the unauthorized channel and examine the indicator marked on the copy. This is cumbersome for wide distribution but can be used on a broad basis such as by region. Region coding is used with many DVD releases for example but can also be considered a type of DRM (Andrew,

Goal of coding theory is different to data hiding method even though both methods use the error correction codes [23]. In coding theory, syndrome equation in the first stage of decoder block is used to detect and correct error which is not expected in advance at the encoder block, whereas in data hiding, syndrome is used to choose proper coefficients to insert a watermark signal and decrease distortion. In the embedding process, by choosing proper e(x), some of the host image bits are modified intentionally.

Images that have been photoshopped using software such as Adobes photoshop program should carry watermarks. Many of the image photoshopped are just for practical jokes, but some are for more spurious reasons. Most of the photoshopping occurs on magazines or in hollywood to make actors or models to look close to perfect.

Information security is a major concept in today’s industrial and computer era, so security must be higher to protect the confidential data. Information security plays major role in computer and network security with the use of different cryptography algorithms that includes the encryption and decryption of data with the uses of the algorithm and the key. By means of text or numerical key for the encryption can be dangerous because with the several hack attacks that a key can be broken. So I have proposed a new mechanism that will replace the text key with the image pixels and can gain high security which cannot be easy to break without prior knowledge.

Three levels of rotations have been implemented. First the original watermarked image is being rotated by 90o , then 180o and at last the image is being rotated by 270o in clock wise direction.

Cheddad et al. [3] have presented that Steganography is the science that involves communicating mystery information in the suitable multimedia carrier, e.G., photo, audio, and video files. It comes beneath the idea that if the function is visible, the point of assault is obvious, hence the goal here is constantly to conceal the very lifestyles of the embedded statistics. This paper provides a today's review and evaluation of the unique current strategies of Steganography along with some common standards and tips drawn from the literature. This paper concludes with some recommendations and advocates for the item-oriented embedding mechanism. The emerging strategies together with DCT, DWT and Adaptive Steganography aren't too liable to assaults, specifically while the hidden message is small. This is because they alter coefficients within the transform domain, hence photo distortion is saved to a minimum. Generally those techniques have a tendency to have a lower payload compared to spatial area algorithms. There are one-of-a-kind approaches to lessen the bits had to encode a hidden message.

Image steganography has gotten more popular press in recent years than other kinds of steganography, possibly because of the massive use of electronic image information available with the advent of digital cameras and high-speed Internet distribution. Image steganography often involves hiding information in the naturally occurring noise within the image and provides a good artwork for such techniques. Most kinds of information contain some kind of noise. Noise can be described as unwanted distortion of information within the signal. Within an audio signal, the concept of noise is obvious. For images, however, noise generally refers to the imperfections inherent in the process of rendering an analog picture as a digital image. For example, the values of colors in the palette for a digital image will not only be the exact colors in the real image and the distribution of these colors will be also be imperfect. The greater the number of bits used to

Since from the earlier times, people are bothered about how to securely transmit secret messages. Both Cryptographic techniques and steganographic techniques are used to achieve this aim. In cryptography, the existence of the encrypted message is visible to the world, whereas in Steganography, only the sender and the receiver know the existence of the message. Darrel Hankerson, Alfred Menezes, and Scott Vanstone explained the various arithmetic behind elliptic curves and addresses some issues that arise in ECC implementation in detail [1]. Lawrence C. Washington provides an introduction to both the number theoretic and the cryptographic sides of elliptic curves. To securely transfer text and image through the network, various techniques have been developed in recent years using Elliptic Curve Cryptography [2]. S. Maria Celestin Vigila and K. Muneeswaran proposed an image encryption algorithm using ECC. They generated the values of k and nB by a random number generator, Comparative Linear Congruential Generator (CLCG) to give credibility [3]. Ali Soleymani, Md Jan Nordin, and Zulkarnain Md Ali creates a mapping table which has the intensity values ranging from 0 to 255 along the row and the corresponding columns of each row contain the elliptic curve coordinates. All the pixels of an image are mapped to related points on the elliptic curve using the table and encryption is done using receiver’s public key. To view the cipher image, we refer to the mapping table and find the

Multimedia data mining is a popular research domain which helps to extractinteresting knowledge from multimedia data sets such as audio, video, images, graphics, speech, text and combination of several types of data sets. Normally, multimedia data are categorized into unstructured and semi-structured data. These data are stored in multimedia databases and multimedia mining is used to find useful information from large multimedia database system by using various multimedia techniques and powerful tools.This paper provides the basic concepts of multimedia mining and its essential characteristics.Multimedia mining architectures for structured and unstructured data, research issues in multimedia mining, data mining models used for multimedia mining and applications are also discussed in this paper. It helps the researchers to get the knowledge about how to do their research in the field of multimedia mining.

Image masking is now a recognized profession. Many people specially in developing countries get employment in image standardization studios or companies. Day by day its application is growing as people tend to keep their photographs intact and retain their past memory fresh from the album pages.

Compare to the first group of neural networks, the image segmentation applications, especially for Biomedical dataset, usually spend more time on inference phase than classification applications. For example, Unet [20] will spend 3 to 4 seconds on a single image of ISBI cell tracking dataset on NVIDIA Tesla P100 GPU while AlexNet [11] can test hundreds of ImageNet [6] images within 0.1 second on the same machine. There are basically two reasons caused this phenomena. The first is the image output from electron microscopy contains about one million pixels, which is much larger than the images for the classification applications.

D. Vaishnavi, et.al [26], introduces two methods for invisible and robust watermarking proposed in RGB color space. In the first strategies, grey scale watermark is embedded at the blue coloration channel and in 2nd technique, blue colour watermark is embedded at the blue colour channel factors and then SVD applied on the blue channel of HI to retrieve singular values. They concluded that first method gives a good robustness for median filtering attacks, for motion blur etc. and second method gives good robustness for Gaussian noise (GN), salt-pepper noise (SPN) etc.

The main goal of using the Image encryption is to avoid drawing attention to the transmission of hidden information. Storing the critical data in its original format is subjective to many risks. The embedding algorithm is used to embed the secret information in the image selected. Hashing is used to secure the sensitive information.

A remarkable feature of this technique is the high robustness to any kind of distortion, since both image areas are distorted in a similar way, which means that the watermark recovery by autocorrelation still works [23].

Alongside watermarking, perceptual image hashing has emerged as an attractive way to verify the authenticity of digital images [1], [5], [6]. Also, image hashing and watermarking could be complementary in that the watermark has to depend on both a secret key and image content to eliminate any possibility of estimating the watermark based on watermarked image observations; hence, the need for image hashes [7], [8]. Indeed, a secure hash can be used in watermarking to solve the problem of multiple ownership claims.