Image Processing:

Image processing is a method to convert an image into digital form and perform some operations on it, in order to get an enhanced image or to extract some useful information from it. It is a type of signal dispensation in which input is image, like video frame or photograph and output may be image or characteristics associated with that image. Usually Image Processing system includes treating images as two dimensional signals while applying already set signal processing methods to them.

Image processing refers to quantitative analyses and/or algorithms applied to digital image data. It allows generation of 3D parametric maps and implies calculation of values that should be ultimately replicable and rater-independent. Image processing methods are becoming increasingly sophisticated and the tendency is to develop as much automation as possible. A common goal of image processing techniques applied to neureoiagings to improve detection of abnormal brain tissue, including abnormalities that may not be readily recognizable by visual analysis alone.

It is important to bear in mind that the clinical input is determinant in deciding which image analysis method might be most useful to investigate specific brain pathologies. This can be done, for example, by modeling features described qualitatively during visual analysis of imaging data by expert observers. Also, there are some important aspects of image processing that should not be overlooked. Image quality is the most important factor in determining the reliability of the data produced by the image post-processing.

The reproducibility of findings is another central issue. The following aspects of image processing of 3D MRI will be discussed in this chapter: image pre-processing, tissue classification, shape analysis, voxel-based morphometr, cortical thickness measurements and texture analysis.

Two types of image processing:

1. Analog image processing

A typical example of analog image processing is a television. In a TV we see pictures due to the controlling of electrical signals ie, using a cathode ray tube. This method of manipulation of images by physical factors like electricity, light etc is called analog image processing.

2. Digital image processing

In digital image processing, digital images are processed. digitally, Photoshop is a good example, Instagram is another.Image processing is analysis and manipulation of a digitised image, in order to improve its quality using mathematical operations by using any form of signal processing for which input is an image, such as photograph or video frame; the output of image processing may be either an image or set of characteristics or parameters related to the image. Most image processing techniques involve treating the image as a 2-D signal and applying standard signal processing techniques to it.

Matlab Software:

In MATLAB, the IPT is a collection of functions that extends the capability of the MATLAB numeric computing environment. It provides a comprehensive set of reference-standard algorithms and workflow applications for image processing, analysis, visualisation and algorithm development.MATLAB is a scientific programming language and provides strong mathematical and numerical support for the implementation of advanced algorithms. It is for this reason that MATLAB is widely used by the image processing and computer vision community.MATLAB, an abbreviation for ‘matrix laboratory,’ is a platform for solving mathematical and scientific problems. It is a proprietary programming language developed by mathworks, allowing matrix manipulations, functions and data plotting, algorithm implementation, user interface creation and interfacing with programs written in programming languages like C, C++, Java and so on.

In MATLAB, the IPT is a collection of functions that extends the capability of the MATLAB numeric computing environment. It provides a comprehensive set of reference-standard algorithms and workflow applications for image processing, analysis, visualisation and algorithm development.It can be used to perform image segmentation, image enhancement, noise reduction, geometric transformations, image registration and 3D image processing operations. Many of the IPT functions support C/C++ code generation for desktop prototyping and embedded vision system deployment.

Steganography:

Steganography is the art of hiding data in a seemingly innocuous cover medium. For example – any sensitive data can be hidden inside a digital image.Steganographic messages are often first encrypted by some traditional means and then a cover image is modified in some way to contain the encrypted message.Image steganography refers to hiding information i.e. text, images or audio files in another image or video files.Steganography is the process of hiding a secret message within a larger one in such a way that someone cannot know the presence or contents of the hidden message. Although related, Steganography is not to be confused with Encryption, which is the process of making a message unintelligible—Steganography attempts to hide the existence of communication.

The article aims to use steganography for animage with another image using spatial domain technique. This hidden information can be retrieved only through proper decoding technique.Data hiding is of importance in many applications. For hobbyists, secretive data transmission,for privacy of users etc. the basic methods are: Steganography andCryptography.Steganography is a simple security method. Generally there are three different methods usedfor hiding information: steganography, cryptography, watermarking.In cryptography, the information to be hidden is encoded using certain techniques; thisinformation is generally understood to be coded as the data appears nonsensical.

Steganography is hiding information; this generally cannot be identified because the codedinformation doesn’t appear to be abnormal i.e. its presence is undetectable by sight.Detection of steganography is called Steganalysis. Steganography is of different types:

             1. Text steganography

             2. Image steganography

             3. Audio steganography

             4. Video steganography

             5.Protocol steganography

In all of these methods, the basic principle of steganography is that a secret message is to be embedded in another cover object which may not be of any significance in such a way that the encrypted data would finally display only the cover data. So it cannot be detected easily to be containing hidden information unless proper decryption is used.

Text Steganograpgy:

Hiding information in text file is method of steganography. The method was to hide a secret message into a text message. Text stenography using digital files is not used very often because the text files have a very small amount of excess data.

Image Steganography:

Images are used as cover medium for steganography. A message is embedded in a digital image using algorithm and the secret key. The stego-image is send to the receiver. On the other side, it is processed by the extraction algorithm using the same key. During the transmission of stego-image unauthenticated persons can only notice the transmission of an image but can’t see the existence of the hidden message.

Audio Steganography:

It is used to embedding data in cover speech in a secure and robust manner. An audible, sound can be inaudible in the presence of another louder audible sound .This property allows to select the channel in which to hide information. Existing audio steganography software can embed messages in WAV and MP3 sound files.

Vedio Steganography:

Video Steganography is a technique to hide any kind of files in any extension into a carrrying Video file.

Protocal Steganography:

It is used to embedding data within network protocols such as TCP/IP in the header of a TCP/IP packet in fields that can be either optional or never used.

Steganography use: Advantages and Disadvantages:

Steganography is beneficial for securely storing sensitive data, such as hiding system passwords or keys within other files. However, it can also pose serious problems because it's difficult to detect. Network surveillance and monitoring systems will not flag messages or files that contain steganographic data. Therefore, if someone attempted to steal confidential data, they could conceal it within another file and send it in an innocent looking email.

Detecting steganography misuse:

There are two methods for detecting steganographically-encoded data: visual steganalysis and statistical steganalysis. The visual method compares a copy of the source file with the suspect file by running a hash against the source file and checking that it matches the hash on the suspect copy. Statistical steganalysis compares theoretically expected frequency distributions of message content with the frequency distribution of the suspected file. Because the covertext has to be modified to store the hidden data, there are usually detectable signs within the covertext's normal characteristics that can be used to reveal the hidden message. For example, when running a histogram on an image, there should be random spikes, but if the histogram is flat or has one large spike, it's likely the image contains hidden information.

There are tools available, such as stegdetect, that analyze content for hidden information. Stegdetect is capable of detecting several different steganographic methods used to embed hidden information in JPEG images.