Digital Steganalysis: Review on Recent Approaches

Abstract:Steganography is the art and science of secret communication, aiming to conceal the existence of a communication, which has been used in military, and perhaps terrorists. Steganography in the modern day sense of the word usually refers to information or a file that has been concealed inside a digital Picture, Video or Audio file. In steganography, the actual information is not maintained in its original format and thereby it is converted into an alternative equivalent multimedia file like image, video or audio, which in turn is being hidden within another object. Information Security is becoming an inseparable part of Data Communication. In order to address this Information Security, Steganography plays an important role. The digital media steganalysis is divided into three domains, which are image steganalysis, audio steganalysis, and video steganalysis. DNA sequences possess some interesting properties, which can be utilized to hide data. This paper is a review of the recent steganography techniques and utilization of DNA sequence appeared in the literature

Bandyopadhyay,” Finding Bilateral Symmetry of the Human Brain from MRI”,Journal of

Abstract: Various subjects that are paired usually are not identically the same, asymmetry is perfectly normal but sometimes asymmetry can be noticeable too much. Structural and functional asymmetry in the human brain and nervous system is reviewed in a historical perspective. Brain asymmetry is one of such examples, which is a difference in size or shape, or both. Asymmetry analysis of brain has great importance because it is not only indicator for brain cancer but also predict future potential risk for the same. In our work, we have concentrated to segment the anatomical regions of brain, isolate the two halves of brain and to investigate each half for the presence of asymmetry of anatomical regions in MRI

Detection of Brain Tumor-A Proposed Method

Abstract: The segmentation of brain tumors in magnetic resonance images (MRI) is a challenging and difficult task because of the variety of their possible shapes, locations, image intensities. In this Review paper, it is intended to summarize and compare the methods of automatic detection of brain tumor through Magnetic Resonance Image (MRI) used in different stages of Computer Aided Detection System (CAD). Brain Image classification techniques are studied. Existing methods are classically divided into region based and contour based methods. These are usually dedicated to full enhanced tumors or specific types of tumors. The amount of resources required to describe large set of data is simplified and selected in for tissue segmentation