@Article{cmc.2023.033536,
AUTHOR = {Sachin Sharma, Meena Malik, Chander Prabha, Amal Al-Rasheed, Mona Alduailij, Sultan Almakdi},
TITLE = {Robust Image Watermarking Using LWT and Stochastic Gradient Firefly Algorithm},
JOURNAL = {Computers, Materials \& Continua},
VOLUME = {75},
YEAR = {2023},
NUMBER = {1},
PAGES = {393--407},
URL = {http://www.techscience.com/cmc/v75n1/51543},
ISSN = {1546-2226},
ABSTRACT = {Watermarking of digital images is required in diversified applications ranging from medical imaging to commercial images used over the web.
Usually, the copyright information is embossed over the image in the form of
a logo at the corner or diagonal text in the background. However, this form
of visible watermarking is not suitable for a large class of applications. In all
such cases, a hidden watermark is embedded inside the original image as proof
of ownership. A large number of techniques and algorithms are proposed
by researchers for invisible watermarking. In this paper, we focus on issues
that are critical for security aspects in the most common domains like digital
photography copyrighting, online image stores, etc. The requirements of this
class of application include robustness (resistance to attack), blindness (direct
extraction without original image), high embedding capacity, high Peak Signal
to Noise Ratio (PSNR), and high Structural Similarity Matrix (SSIM). Most
of these requirements are conflicting, which means that an attempt to maximize one requirement harms the other. In this paper, a <i>blind</i> type of image
watermarking scheme is proposed using Lifting Wavelet Transform (LWT)
as the baseline. Using this technique, custom binary watermarks in the form
of a binary string can be embedded. Hu’s Invariant moments’ coefficients
are used as a key to extract the watermark. A Stochastic variant of the
Firefly algorithm (FA) is used for the optimization of the technique. Under
a prespecified size of embedding data, high PSNR and SSIM are obtained
using the Stochastic Gradient variant of the Firefly technique. The simulation
is done using Matrix Laboratory (MATLAB) tool and it is shown that the
proposed technique outperforms the benchmark techniques of watermarking
considering PSNR and SSIM as quality metrics.},
DOI = {10.32604/cmc.2023.033536}
}