177 research outputs found
Orbital Angular Momentum Waves: Generation, Detection and Emerging Applications
Orbital angular momentum (OAM) has aroused a widespread interest in many
fields, especially in telecommunications due to its potential for unleashing
new capacity in the severely congested spectrum of commercial communication
systems. Beams carrying OAM have a helical phase front and a field strength
with a singularity along the axial center, which can be used for information
transmission, imaging and particle manipulation. The number of orthogonal OAM
modes in a single beam is theoretically infinite and each mode is an element of
a complete orthogonal basis that can be employed for multiplexing different
signals, thus greatly improving the spectrum efficiency. In this paper, we
comprehensively summarize and compare the methods for generation and detection
of optical OAM, radio OAM and acoustic OAM. Then, we represent the applications
and technical challenges of OAM in communications, including free-space optical
communications, optical fiber communications, radio communications and acoustic
communications. To complete our survey, we also discuss the state of art of
particle manipulation and target imaging with OAM beams
STV-based Video Feature Processing for Action Recognition
In comparison to still image-based processes, video features can provide rich and intuitive information about dynamic events occurred over a period of time, such as human actions, crowd behaviours, and other subject pattern changes. Although substantial progresses have been made in the last decade on image processing and seen its successful applications in face matching and object recognition, video-based event detection still remains one of the most difficult challenges in computer vision research due to its complex continuous or discrete input signals, arbitrary dynamic feature definitions, and the often ambiguous analytical methods. In this paper, a Spatio-Temporal Volume (STV) and region intersection (RI) based 3D shape-matching method has been proposed to facilitate the definition and recognition of human actions recorded in videos. The distinctive characteristics and the performance gain of the devised approach stemmed from a coefficient factor-boosted 3D region intersection and matching mechanism developed in this research. This paper also reported the investigation into techniques for efficient STV data filtering to reduce the amount of voxels (volumetric-pixels) that need to be processed in each operational cycle in the implemented system. The encouraging features and improvements on the operational performance registered in the experiments have been discussed at the end
Introduction to Facial Micro Expressions Analysis Using Color and Depth Images: A Matlab Coding Approach (Second Edition, 2023)
The book attempts to introduce a gentle introduction to the field of Facial
Micro Expressions Recognition (FMER) using Color and Depth images, with the aid
of MATLAB programming environment. FMER is a subset of image processing and it
is a multidisciplinary topic to analysis. So, it requires familiarity with
other topics of Artifactual Intelligence (AI) such as machine learning, digital
image processing, psychology and more. So, it is a great opportunity to write a
book which covers all of these topics for beginner to professional readers in
the field of AI and even without having background of AI. Our goal is to
provide a standalone introduction in the field of MFER analysis in the form of
theorical descriptions for readers with no background in image processing with
reproducible Matlab practical examples. Also, we describe any basic definitions
for FMER analysis and MATLAB library which is used in the text, that helps
final reader to apply the experiments in the real-world applications. We
believe that this book is suitable for students, researchers, and professionals
alike, who need to develop practical skills, along with a basic understanding
of the field. We expect that, after reading this book, the reader feels
comfortable with different key stages such as color and depth image processing,
color and depth image representation, classification, machine learning, facial
micro-expressions recognition, feature extraction and dimensionality reduction.
The book attempts to introduce a gentle introduction to the field of Facial
Micro Expressions Recognition (FMER) using Color and Depth images, with the aid
of MATLAB programming environment.Comment: This is the second edition of the boo
VLSI Design
This book provides some recent advances in design nanometer VLSI chips. The selected topics try to present some open problems and challenges with important topics ranging from design tools, new post-silicon devices, GPU-based parallel computing, emerging 3D integration, and antenna design. The book consists of two parts, with chapters such as: VLSI design for multi-sensor smart systems on a chip, Three-dimensional integrated circuits design for thousand-core processors, Parallel symbolic analysis of large analog circuits on GPU platforms, Algorithms for CAD tools VLSI design, A multilevel memetic algorithm for large SAT-encoded problems, etc
Digital image compression.
Due to the rapid growth in information handling
and transmission, there is a serious demand for more
efficient data compression schemes.
compression schemes address themselves to speech,
visual and alphanumeric coded data. This thesis is
concerned with the compression of visual data given in
the form of still or moving pictures. such data is highly
correlated spatially and in the context domain.
A detailed study of some existing data
compression systems is presented, in particular, the
performance of DPCM was analysed by computer simulation,
and the results examined both subjectively and
objectively. The adaptive form of the prediction encoder
is discussed and two new algorithms proposed, which
increase the definition of the compressed image and
reduce the overall mean square error.
Two novel systems are proposed for image
compression. The first is a bit plane image coding system
based on a hierarchic quadtree structure in a
transmission domain, using the Hadamard transform as a
kernel. Good compression has been achieved from this
scheme, particularly for images with low detail.
The second scheme uses a learning automata to
predict the probability distribution of the grey levels
of an image related to its spatial context and position.
An optimal reward/punishment function is proposed such
that the automata converges to its steady state within
4000 iterations • such a high speed of convergence
together with Huffman coding results in efficient
compression for images and is shown to be applicable to
other types of data. .
The performance and evaluation of all the
proposed .'systems have been tested by computer simulation
and the results presented both quantitatively and
qualitatively."The advantages and disadvantages of each
system are discussed and suggestions for improvement.
given
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