Watermarking ( data hiding ) is the process of embedding data into a multimedia element such as image, audio or video. This
embedded data can later be extracted from, or detected in, the multimedia for security purposes . A watermarking algorithm
consists of the watermark structure, an embedding algorithm, and an extraction, or a detection, algorithm. Watermarks can be
embedded in the pixel domain or a transform domain. In multimedia applications, embedded watermarks should be invisible,
robust, and have a high capacity .Robustness is the resistance of an embedded watermark against intentional attacks, and
normal A/V processes such as noise, filtering ( blurring , sharpening, etc. ) , resampling, scaling, rotation, cropping, and lossy
compression. Capacity is the amount of data that can be represented by an embedded watermark. The approaches used in
watermarking still images include least-significant bit encoding, basic M-sequence, transform techniques,and image-adaptive
techniques. An important criterion for classifying watermarking schemes is the type of information needed by the detector:
• Non-blind schemes: Both the original image and the secret key(s) for watermark embedding.
• Semi-blind schemes: The secret key(s) and the watermark bit sequence.
• Blind schemes: Only the secret key(s).
Typical uses of watermarks include copyright protection,the cost of a watermarking system will depend on the intended use,and
may vary considerably . Two widely used image compression standards are JPEG and JPEG2000. The former is based on the
Discrete Cosine Transform (DCT), and the latter the Discrete Wavelet Transform (DWT).
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AN FPGA-BASED ARCHITECTURE FOR REAL TIME IMAGE FEATURE EXTRACTION
Realtime image pattern recognition is a challenging task which involves image processing, feature extraction and pattern
classification . It applies to a wide range of applications including multimedia , military and medical ones. Its high computational
requirements force systems to use very expensive clusters, custom VLSI designs or even both. These approaches suffer from various
disadvantages, such as high cost and long development times. Recent advances in fabrication technology allow the manufacturing of
high density and high performance Field Programmable Gate Arrays ( FPGAs ) capable of performing many complex computations in
parallel while hosted by conventional computer hardware. A variety of architecture designs capable of supporting real-time pattern
recognition have been proposed in the recent literature , such as implementations of algorithms for image and video processing,
classification and image feature extraction algorithms.Texture plays a significant role in image analysis & pattern recognition only a few
architectures implement on-board textural feature extraction.Most prominent approaches include the extraction of Gabor wavelet features
for face/object recognition and the computation of mean and contrast Gray Level Cooccurrence Matrix (GLCM) features.
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CORDIC ALGORITHM
Radar works by bouncing electromagentic energy off a target, recording the echo and making some useful observation
from the data. A fundamental problem in radar is that the vast majority of the reflected energy does not make it back to
the receiver . Much of the processing in a radar system is to improve the signal to noise ratio of the received signal
and maximizing range accuracy to determine the position of the target with less error . Various techniques are available
to the radar engineer for the design of high range solution system .These techniques may be categorized as simple
pulse and pulse compression techniques.
NEED FOR CORDIC
Digital Signal Processing is dominated by microprocessors with enhancements , single cycle multiply-accumulate
instruction and special addressing modes . Microprocessors are not fast enough for truly demanding DSP tasks.
Algorithms optimized for these microprocessors based system do not map well into hardware.
The advent of reconfigurable logic computers permits the higher speeds of dedicated hardware solution at costs that
are competitive with the traditional software approach . Among these hardware-efficient algorithms is a class of iterative
solutions for trigonometric and other transcendental functions that use only shifts & adds to perform.This trigonometric
algorithm is called CORDIC.The trigonometric CORDIC algorithms were originally developed as a digital solution for real
-time navigation problems
CORDIC Theory :Analgorithm for vector rotation
CORDIC is an acronym for Coordinate Rotation Digital Computer . It is a hardware efficient algorithm, which belong to a
class of iterative solutions that use only shifts & adds to perform a wide range of functions including certain trigonometric,
hyperbolic,linear and logarithmic functions.CORDIC revolves around the idea of "rotating" the phase of a complex number,
by multiplying it by a succession of constant values. however, the "multiplies" can all be powers of 2,so in binary arithmetic
they can be done using just shifts and adds; no actual "multiplier" is needed.
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