A Literature Study Of Watermarking Techniques On Contrast Enhancement Of Color Images

Suppose that v(x)= v1x + v2x 2+ … + vn-1xn-1 is host image and modify in the host image bits after insert watermark image results in the following watermarked image:

Multimedia content is also in collaboration with Encryption & Decryption standards (CBR).The below paper is the general

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.

Image Steganography: In today’s digital world secret messages get embedded in to the digital image which is called as Image Steganography where cover object used is Image . Because of the limited power of the Human vision system this method is most commonly used [5].

Abstract: With the increasing usage of digital multimedia, the protection of intellectual property rights problem has become a very important issue. Digital watermarking is now drawing attention as a new method of protecting multimedia content from unauthorized copying. Over the past two decades, many digital watermarking algorithms have been developed, each with its own advantages and disadvantages. The main aim of this paper is to present a survey report of recently done work in audio watermarking fields.

Abstract- The utilization of PC systems for information transmissions has made the need of security. The security of this intuitive media data should be possible with encryption or information concealing calculations. To diminish the transmission time, the information pressure is necessary. Since couple of years, an issue is to attempt to join pressure, encryption and information covering up in a solitary stride. Picture security turns out to be progressively critical for some applications, e.g., secret transmission, video reconnaissance, military and therapeutic applications. These days, the transmission of pictures is an every day routine and it is important to locate a proficient approach to transmit them over systems. They send Secret message over channel utilizing Cryptography and Steganography calculations by AES (Advanced Encryption Standard). It is utilized to scramble the information from plain content to figure content the other way around. There are two sorts of keys accessible in the cryptography, symmetric and asymmetric. There are utilizing symmetric key which is separated into two key, for example, private and open key. Open key is utilized for encryption and private key is utilized for decoding. The reversible information concealing method is utilized to recover the information and picture

For the purpose of this paper, I will be focusing on Steganography, which I believe is the most efficient part of steganography. Unlike other Information hiding methods where the encryption is usually detectable, steganography takes it further by hiding the message within mediums like images, main it almost impossible to detect. The purpose of this paper is to explain Steganography, how it works compared to other methods and show methods of application and types of steganography.

[24] Vinayak S. Dhole (2015) et al present that FW is discovered for authentication and content integrity verification. This paper introduces a changed FW technique for picture restoration. Here we can detect as well as recovered the tampered image with its tampered region. This modified approach enables us to produce resistance on diverse attacks like

Globally, people are increasingly accessing content as easier access to information continues to explode rapidly. People not only access content (be it text, audio, still images, animation, video or interactivity content forms) but are themselves the producers of more and more digital data and with this comes a host of problems like content management, content reuse based on consumer and device capabilities, protection of rights and from unauthorised access or modification, privacy protection of both providers and consumers, etc [1] [2].

The reason this scheme was considered remarkable was due to the fact that the secret message could be decoded directly by the human visual system; hence it can be called the visual cryptography scheme. The Decoding process involves printing the shares onto transparencies and superimposing them, the shares of a qualified set will reveal the secret image without any cryptographic computation. In this paper we analyze the basic model of visual cryptography for black and white images and the k out of n scheme. The basic scheme of visual cryptography is called the (2, 2) model otherwise known as the 2 out of 2 model. This model involves using 2 shares; a printed page of cipher text and a printed page of transparency (which serves as the secret key). Both layers appear indistinguishable from random noise. The clear text is revealed by superimposing both shares [2]. The basic model can be extended into the k out of n secret sharing problem which states; given a written message, we can generate n transparencies (shares) such that the original message is visible if any k (or more) are stacked together, but totally invisible if fewer than k transparencies are stacked together. A Visual Cryptographic Scheme is mainly applied to a binary image, which contains a collection of black and white pixels. Each pixel is handled separately and is encoded into p black and white sub pixels, which are printed in close proximity to each other so that the human

Document images are acquired by scanning journal, printed document, degraded document images, handwritten historical document, and book cover etc. The text may appear in a virtually unlimited number of fonts, style, alignment, size, shapes, colors, etc. Extraction of text from text document images and from complex color background is difficult due to complexity of the background and mix up of colors of fore-ground text with colors of background. In this section, we present the main ideas and details of the proposed algorithm.

1.1.1. Image processing: Image processing is a methodology to perform some operations on an image, so as to urge an enhanced image or to extract some helpful data from it. It is treated as an area of signal processing where both the input and output signals are images. Images are portrayed as two dimensional matrix, and we are applying already having signal processing strategies to input matrix. Images processing finds applications in several fields like photography, satellite imaging, medical imaging, and image compression, just to name a few. Basically Image processing includes the following steps:  Reading the image via image acquisition tools like cameras, caners etc.  Analysing and manipulating the acquired image to have enhanced quality and locate the data of interest;  Output in which result can be altered image or report that is based on image analysis. Originally image processing is proposed for space exploration and biomedical field. But later on with the increase in use of digital images in everybody’s lives it considered as powerful tool for arbitrarily manipulating images to gain useful information. It defined as the means of conversion between human visual system and digital imaging devices.The main purpose of image processing are listed below: 1. Visualization - Observe the objects which are not visible. 2. Image sharpening and restoration - To increase quality of image. 3. Image retrieval –

Over several past years, contrast image enhancement has generated across many applications like robot sensing, electronic products, fault detection, medical image analysis, etc. Thus, increasing in popularity of contrast enhancement of images has forces researchers to study their enhancement techniques and their effectiveness for the interpretability or perception of human viewers. Contrast enhancement is a

Over several past years, contrast image enhancement has generated across many applications like robot sensing, electronic products, fault detection, medical image analysis, etc. Thus, increasing in popularity of contrast enhancement of images has forces researchers to study their enhancement techniques and their effectiveness for the interpretability or perception of human viewers. Contrast enhancement is a vital part of various fields, such as X-ray image analysis, biomedical image analysis, machine vision where pixel