Reliable and Adaptive Steganalysis Method for Binary Image Using CRMST Algorithm (International Journal of Engineering and Computer Science, 2017)
Data security is one of the most vigorous fields of study in Informatics and Computer Forensic. Author right for intellectual stuff is a real challenge, particularly when information is processed and transmitted. One of the electronic methods of digital data is images. They are widely used in organizations, research institutions, and in environments where speedy, secured and minimized distortion is needed. In the proposed using the Complement, Rotate, and Mirrored with respect to Local Texture Using Syndrome Trellis Code (CRMST) algorithm. Entrenching the data in binary image is potential by flipping the pixels. The flip ability decision of a pixel depends on three transitions from the pixels to its eight neighbors in a Local window. Flipping a pixel does not abolish the connectivity among pixel, to safeguard the good visual quality of an image. The steganography scheme engenders the cover vector by dividing the scrambled image into super pixels. By testing on both simple binary images and the constructed image data set, show that the proposed measurement can well describe the distortions on both visual quality and statistics. A spatial domain-based binary image steganography scheme is proposed. The scheme minimizes a unique flipping distortion measurement which considers both HVS and statistics. This measurement employs the weighted sum of CRMST changes to measure the flip ability of a pixel. It is used for military purposes and provide high security.