JOURNAL OF COMPUTING, VOLUME 3, ISSUE 4, APRIL 2011, ISSN 2151-9617
reference image by modifying the singular values of
reference image using the singular values of the
Hao Luo et al , proposed a self-embedding
watermarking scheme for digital images. In their
proposed algorithm they used the cover image as a
watermark. It generates the watermark by halftoning the
host image into a halftone image. Then, the watermark is
permuted and embedded in the LSB of the host image.
The watermark is retrieved from the LSB of the suspicious
image and inverse permuted.
Wen-Chao Yang et al  used the PKI (Public-Key
Infrastructure), Public-Key Cryptography and watermark
techniques to design a novel testing and verifying method
of digital images. The main idea of their paper is to
embed encryption watermarks in the least significant bit
(LSB) of cover images.
Hong Jie He et al , proposed a wavelet-based
fragile watermarking scheme for secure image
authentication. In their proposed scheme, they generated
the embedded watermark using the discrete wavelet
transform (DWT), and then they elaborated security
watermark by scrambling encryption is embedded into
the least significant bit (LSB) of the host image.
Sung-Cheal Byun et al , proposed a fragile
watermarking scheme for authentication of images. They
used singular values of singular value decomposition
(SVD) of images to check the integrity of images. In order
to make authentication data, the singular values are
changed to the binary bits using modular arithmetic.
Then, they inserted the binary bits into the least
significant bits (LSBs) of the original image. The pixels to
be changed are randomly selected in the original image.
Gil-Je Lee et al  presented a new LSB digital
watermarking scheme by using random mapping
function. The idea of their proposed algorithm is
embedding watermark randomly in the coordinates of the
image by using random function to be more robust than
the traditional LSB technique.
Saeid Fazli et al  presented trade-off between
imperceptibility and robustness of LSB watermarking
using SSIM Quality Metrics. In their algorithm, they put
significant bit-planes of the watermark image instead of
lower bit-planes of the asset picture.
Debjyoti Basu et al  proposed Bit Plane Index
Modulation (BPIM) based fragile watermarking scheme
for authenticating RGB color image. By embedding R, G,
B component of watermarking image in the R, G, B
component of original image, embedding distortion is
minimized by adopting least significant bit (LSB)
alteration scheme. Their proposed method consists of
encoding and decoding methods that can provide public
detection capabilities in the absences of original host
image and watermark image.
To overcome the drawback of existing techniques, we
would like to introduce a new alternative technique by
inserting watermark text in grayscale images by using
EVIEW OF LSB
In a digital image, information can be inserted directly
into every bit of image information or the more busy
areas of an image can be calculated so as to hide such
messages in less perceptible parts of an image ,.
Tirkel et al  were one of the first used techniques
for image watermarking. Two techniques were presented
to hide data in the spatial domain of images by them.
These methods were based on the pixel value’s Least
Significant Bit (LSB) modifications. The algorithm
proposed by Kurah and McHughes  to embed in the
LSB and it was known as image downgrading .
An example of the less predictable or less perceptible
is Least Significant Bit insertion. This section explains
how this works for an 8-bit grayscale image and the
possible effects of altering such an image. The principle
of embedding is fairly simple and effective. If we use a
grayscale bitmap image, which is 8- bit, we would need to
read in the file and then add data to the least significant
bits of each pixel, in every 8-bit pixel.
In a grayscale image each pixel is represented by 1
byte consist of 8 bits. It can represent 256 gray colors
between the black which is 0 to the white which is 255.
The principle of encoding uses the Least Significant Bit of
each of these bytes, the bit on the far right side.
If data is encoded to only the last two significant bits
(which are the first and second LSB) of each color
component it is most likely not going to be detectable; the
human retina becomes the limiting factor in viewing
For the sake of this example only the least significant
bit of each pixel will be used for embedding information.
If the pixel value is 138 which is the value 10000110 in
binary and the watermark bit is 1, the value of the pixel
will be 10000111 in binary which is 139 in decimal. In this
example we change the underline pixel.
Based on LSB technique, we propose a new watermarking
algorithm. Most of researchers have proposed the first
LSB but our proposed watermarking algorithm is
inversing the watermark text and embedding it in
different order in the traditional LSB. This is because of
the security reason. So, no one will expect that the hidden
watermark text in different order and it is inversed.
Figure 1 shows the framework of the proposed method.
First, we select the image which is a grayscale image and
we will transfer the watermark to binary value after
typing it. Then, we embed the watermark in the image
using the proposed algorithm. Figure 2 shows the