spatial least significant-bit (LSB) replacement.
In this data hiding scheme a subset of all the LSB of the cover image is modified
spatial least significant-bit (LSB) replacement.
In this data hiding scheme a subset of all the LSB of the cover image is modified
This well studied steganographic approach never decreases (resp. increases)
pixel with even value (resp. odd value) and may break structural symmetry.
These structural modification can be detected by statistical approaches
This well studied steganographic approach never decreases (resp. increases)
pixel with even value (resp. odd value) and may break structural symmetry.
These structural modification can be detected by statistical approaches
We argue that modifying edge pixels is an acceptable compromise.
Edges form the outline of an object: they are the boundary between overlapping objects or between an object
and the background. A small modification of pixel value in the stego image should not be harmful to the image quality:
We argue that modifying edge pixels is an acceptable compromise.
Edges form the outline of an object: they are the boundary between overlapping objects or between an object
and the background. A small modification of pixel value in the stego image should not be harmful to the image quality:
pixels. In other words, minor changes in regular area are more dramatic than larger modifications in edge ones.
Our proposal is thus to embed message bits into edge shapes while preserving other smooth regions.
pixels. In other words, minor changes in regular area are more dramatic than larger modifications in edge ones.
Our proposal is thus to embed message bits into edge shapes while preserving other smooth regions.
Then the data hiding algorithm is achieved by applying LSBMR on pixels of this region.
The authors show that this method is more efficient than all the LSB, LSBM, LSBMR approaches
thanks to extensive experiments.
Then the data hiding algorithm is achieved by applying LSBMR on pixels of this region.
The authors show that this method is more efficient than all the LSB, LSBM, LSBMR approaches
thanks to extensive experiments.
produce stego content
with only considering the payload, not the type of image signal: the higher the payload is,
the better the approach is said to be.
produce stego content
with only considering the payload, not the type of image signal: the higher the payload is,
the better the approach is said to be.
Consider for instance a uniformly black image: a very tiny modification of its pixels can be easily detectable.
The approach we propose is thus to provide a self adaptive algorithm with a high payload, which depends on the
Consider for instance a uniformly black image: a very tiny modification of its pixels can be easily detectable.
The approach we propose is thus to provide a self adaptive algorithm with a high payload, which depends on the
