Abstract: In this paper, we proposed an efficient data
compression strategy exploiting the multi-resolution characteristic of
the wavelet transform. We have developed a sensor node called
“Smart Sensor Node; SSN". The main goals of the SSN design are
lightweight, minimal power consumption, modular design and robust
circuitry. The SSN is made up of four basic components which are a
sensing unit, a processing unit, a transceiver unit and a power unit.
FiOStd evaluation board is chosen as the main controller of the SSN
for its low costs and high performance. The software coding of the
implementation was done using Simulink model and MATLAB
programming language. The experimental results show that the
proposed data compression technique yields recover signal with good
quality. This technique can be applied to compress the collected data
to reduce the data communication as well as the energy consumption
of the sensor and so the lifetime of sensor node can be extended.
Abstract: In this paper, an artificial intelligent technique for
robust digital image watermarking in multiwavelet domain is
proposed. The embedding technique is based on the quantization
index modulation technique and the watermark extraction process
does not require the original image. We have developed an
optimization technique using the genetic algorithms to search for
optimal quantization steps to improve the quality of watermarked
image and robustness of the watermark. In addition, we construct a
prediction model based on image moments and back propagation
neural network to correct an attacked image geometrically before the
watermark extraction process begins. The experimental results show
that the proposed watermarking algorithm yields watermarked image
with good imperceptibility and very robust watermark against various
image processing attacks.