Improving High Embedding Capacity Using Artificial Immune System: A Novel Approach for Data Hiding - Proceedings of All India Seminar on Biomedical Engineering 2012 (AISOBE-2012) - page 207

As a result, loud sounds tend to mask out quiet sounds. Additionally, the HAS is
unable to perceive absolute phase, only relative phase. Finally, there are some
environmental distortions so common as to be ignored by the listener in most
cases. We exploit many of these traits in the methods.
Data Hiding in Text
Soft-copy text is in many ways the most difficult place to hide data [ 14 , 15 ]. (Hard-
copy text can be treated as a highly structured image and is readily amenable to a
variety of techniques such as slight variations in letter forms, kerning, baseline,
etc.) This is due largely to the relative lack of redundant information in a text file
as compared with a picture or a sound bite. While it is often possible to make
imperceptible modifications to a picture, even an extra letter or period in text may
be noticed by a casual reader. Data Hiding [ 16 - 19 ] in text is an exercise in the
discovery of modifications that are not noticed by readers. We considered three
major methods of encoding data: open space methods that encode through
manipulation of white space (unused space on the printed page), syntactic methods
that utilize punctuation, and semantic methods that encode using manipulation of
the words themselves.
Data Hiding in Video
A video data embedding scheme in which the embedded signature data is
reconstructed without knowing the original host video [ 20 , 21 ]. The proposed
method enables high rate of data embedding [ 22 ] and is robust to motion com-
pensated coding, such as MPEG-2. Embedding is based on texture masking and
utilizes a multidimensional lattice structure for encoding signature information.
Signature data is embedded in individual video frames using the block DCT. The
embedded frames are then MPEG-2 coded. At the receiver, both the host and
signature images are recovered from the embedded bit stream [ 23 , 24 ].
Tradition Method Used in Data Hiding
Least Significant Bit (LSB) Method
In computing, the least significant bit (LSB) [ 25 - 28 ] is the bit position in a binary
integer giving the units value, that is, determining whether the number is even or
odd. The lsb is sometimes referred to as the right-most bit, due to the convention in