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Image of a tree with a steganographically hidden image. The hidden image is revealed by removing all but the two least significant bits of each color component and a subsequent normalization. The hidden image is shown below. Image of a cat extracted from the tree image above. Concealing messages within the lowest bits of noisy images or sound ...
The same image viewed by white, blue, green, and red lights reveals different hidden numbers. Steganography (/ ˌ s t ɛ ɡ ə ˈ n ɒ ɡ r ə f i / ⓘ STEG-ə-NOG-rə-fee) is the practice of representing information within another message or physical object, in such a manner that the presence of the concealed information would not be evident to an unsuspecting person's examination.
Steganography architecture example - OpenPuff. A steganography software tool allows a user to embed hidden data inside a carrier file, such as an image or video, and later extract that data. It is not necessary to conceal the message in the original file at all.
The problem is generally handled with statistical analysis. A set of unmodified files of the same type, and ideally from the same source (for example, the same model of digital camera, or if possible, the same digital camera; digital audio from a CD MP3 files have been "ripped" from; etc.) as the set being inspected, are analyzed for various statistics.
Image of Lena Forsén used in many image processing experiments. (Click on the image to access the actual 512×512px standard test version.) Lenna (or Lena ) is a standard test image used in the field of digital image processing , starting in 1973. [ 1 ]
In this example, the binary image has been split into two component images. Each component image has a pair of pixels for every pixel in the original image. These pixel pairs are shaded black or white according to the following rule: if the original image pixel was black, the pixel pairs in the component images must be complementary; randomly ...
An algorithm estimates the capacity for hidden data without the distortions of the decoy data becoming apparent. OutGuess determines bits in the decoy data that it considers most expendable and then distributes secret bits based on a shared secret in a pseudorandom pattern across these redundant bits, flipping some of them according to the secret data.
In comparison to simple image based steganography which uses solely the least important bit of data, and thus (for a 24-bit color image) can only embed data equivalent to 1/8 of the total size, BPCS-steganography uses multiple bit-planes, and so can embed a much higher amount of data, though this is dependent on the individual image. For a ...