Abstract: This paper presents the development of a 2D visual marker, derived from a recent patented work in the field of numbering systems. The proposed fiducial uses a group of projective invariant straight-line patterns, easily detectable and remotely recognizable. Based on an efficient data coding scheme, the developed marker enables producing a large panel of unique real time identifiers with highly distinguishable patterns. The proposed marker Incorporates simultaneously decimal and binary information, making it readable by both humans and machines. This important feature opens up new opportunities for the development of efficient visual human-machine communication and monitoring protocols. Extensive experiment tests validate the robustness of the marker against acquisition and geometric distortions.
Abstract: The present work focuses on the investigation of the effect of non-Newtonian behavior on the oil-water stratified flow in a horizontal channel using ANSYS Fluent. Coupled level set and volume of fluid (CLSVOF) has been used to capture the evolving interface assuming unsteady, coaxial flow with constant fluid properties. The diametric variation of oil volume fraction, mixture velocity, total pressure and pressure gradient has been studied. Non-Newtonian behavior of oil has been represented by the power law model in order to investigate the effect of flow behavior index. Stratified flow pattern tends to assume dispersed flow pattern with the change in the behavior of oil to non-Newtonian. The pressure gradient is found to be very much sensitive to the flow behavior index. The findings could be useful in designing the transportation pipe line in petroleum industries.
Abstract: Due to the acquisition of huge amounts of brain tumor magnetic resonance images (MRI) in clinics, it is very difficult for radiologists to manually interpret and segment these images within a reasonable span of time. Computer-aided diagnosis (CAD) systems can enhance the diagnostic capabilities of radiologists and reduce the time required for accurate diagnosis. An intelligent computer-aided technique for automatic detection of a brain tumor through MRI is presented in this paper. The technique uses the following computational methods; the Level Set for segmentation of a brain tumor from other brain parts, extraction of features from this segmented tumor portion using gray level co-occurrence Matrix (GLCM), and the Artificial Neural Network (ANN) to classify brain tumor images according to their respective types. The entire work is carried out on 50 images having five types of brain tumor. The overall classification accuracy using this method is found to be 98% which is significantly good.
Abstract: The present study investigates the effect of inclusions on the shape and size of crack tip plastic zones in engineering materials subjected to static loads by employing the element free Galerkin method (EFGM). The modeling of the discontinuities produced by cracks and inclusions becomes independent of the grid chosen for analysis. The standard displacement approximation is modified by adding additional enrichment functions, which introduce the effects of different discontinuities into the formulation. The level set method has been used to represent different discontinuities present in the domain. The effect of inclusions on the extent of crack tip plastic zones is investigated by solving some numerical problems by the EFGM.
Abstract: We present in this paper a fully implicit finite element
method tailored for the numerical modeling of inextensible fluidic
membranes in a surrounding Newtonian fluid. We consider a highly
simplified version of the Canham-Helfrich model for phospholipid
membranes, in which the bending force and spontaneous curvature
are disregarded. The coupled problem is formulated in a fully
Eulerian framework and the membrane motion is tracked using
the level set method. The resulting nonlinear problem is solved
by a Newton-Raphson strategy, featuring a quadratic convergence
behavior. A monolithic solver is implemented, and we report several
numerical experiments aimed at model validation and illustrating
the accuracy of the proposed method. We show that stability is
maintained for significantly larger time steps with respect to an
explicit decoupling method.
Abstract: This paper is concerned with the development of a
fully implicit and purely Eulerian fluid-structure interaction method
tailored for the modeling of the large deformations of elastic
membranes in a surrounding Newtonian fluid. We consider a
simplified model for the mechanical properties of the membrane, in
which the surface strain energy depends on the membrane stretching.
The fully Eulerian description is based on the advection of a modified
surface tension tensor, and the deformations of the membrane are
tracked using a level set strategy. The resulting nonlinear problem
is solved by a Newton-Raphson method, featuring a quadratic
convergence behavior. A monolithic solver is implemented, and we
report several numerical experiments aimed at model validation and
illustrating the accuracy of the presented method. We show that
stability is maintained for significantly larger time steps.
Abstract: Liver segmentation from medical images poses more
challenges than analogous segmentations of other organs. This
contribution introduces a liver segmentation method from a series of
computer tomography images. Overall, we present a novel method for
segmenting liver by coupling density matching with shape priors.
Density matching signifies a tracking method which operates via
maximizing the Bhattacharyya similarity measure between the
photometric distribution from an estimated image region and a model
photometric distribution. Density matching controls the direction of
the evolution process and slows down the evolving contour in regions
with weak edges. The shape prior improves the robustness of density
matching and discourages the evolving contour from exceeding liver’s
boundaries at regions with weak boundaries. The model is
implemented using a modified distance regularized level set (DRLS)
model. The experimental results show that the method achieves a
satisfactory result. By comparing with the original DRLS model, it is
evident that the proposed model herein is more effective in addressing
the over segmentation problem. Finally, we gauge our performance of
our model against matrices comprising of accuracy, sensitivity, and
specificity.
Abstract: When neck pain is associated with pain, numbness, or
weakness in the arm, shoulder, or hand, further investigation is
needed as these are symptoms indicating pressure on one or more
nerve roots. Evaluation necessitates a neurologic examination and
imaging using an MRI/CT scan. A degenerating disc loses some
thickness and is less flexible, causing inter-vertebrae space to narrow.
A radiologist diagnoses an Intervertebral Disc Degeneration (IDD) by
localizing every inter-vertebral disc and identifying the pathology in
a disc based on its geometry and appearance. Accurate localizing is
necessary to diagnose IDD pathology. But, the underlying image
signal is ambiguous: a disc’s intensity overlaps the spinal nerve
fibres. Even the structure changes from case to case, with possible
spinal column bending (scoliosis). The inter-vertebral disc
pathology’s quantitative assessment needs accurate localization of the
cervical region discs. In this work, the efficacy of multilevel set
segmentation model, to segment cervical discs is investigated. The
segmented images are annotated using a simple distance matrix.
Abstract: Medical image analysis is one of the great effects of computer image processing. There are several processes to analysis the medical images which the segmentation process is one of the challenging and most important step. In this paper the segmentation method proposed in order to segment the dental radiograph images. Thresholding method has been applied to simplify the images and to morphologically open binary image technique performed to eliminate the unnecessary regions on images. Furthermore, horizontal and vertical integral projection techniques used to extract the each individual tooth from radiograph images. Segmentation process has been done by applying the level set method on each extracted images. Nevertheless, the experiments results by 90% accuracy demonstrate that proposed method achieves high accuracy and promising result.
Abstract: This paper presents a customized deformable model
for the segmentation of abdominal and thoracic aortic aneurysms in
CTA datasets. An important challenge in reliably detecting aortic
aneurysm is the need to overcome problems associated with intensity
inhomogeneities and image noise. Level sets are part of an important
class of methods that utilize partial differential equations (PDEs) and
have been extensively applied in image segmentation. A Gaussian
kernel function in the level set formulation, which extracts the local
intensity information, aids the suppression of noise in the extracted
regions of interest and then guides the motion of the evolving contour
for the detection of weak boundaries. The speed of curve evolution
has been significantly improved with a resulting decrease in
segmentation time compared with previous implementations of level
sets. The results indicate the method is more effective than other
approaches in coping with intensity inhomogeneities.
Abstract: This paper is devoted to present and discuss a model that allows a local segmentation by using statistical information of a given image. It is based on Chan-Vese model, curve evolution, partial differential equations and binary level sets method. The proposed model uses the piecewise constant approximation of Chan-Vese model to compute Signed Pressure Force (SPF) function, this one attracts the curve to the true object(s)-s boundaries. The implemented model is used to extract weld defects from weld radiographic images in the aim to calculate the perimeter and surfaces of those weld defects; encouraged resultants are obtained on synthetic and real radiographic images.
Abstract: Various intelligences and inspirations have been
adopted into the iterative searching process called as meta-heuristics.
They intelligently perform the exploration and exploitation in the
solution domain space aiming to efficiently seek near optimal
solutions. In this work, the bee algorithm, inspired by the natural
foraging behaviour of honey bees, was adapted to find the near
optimal solutions of the transportation management system, dynamic
multi-zone dispatching. This problem prepares for an uncertainty and
changing customers- demand. In striving to remain competitive,
transportation system should therefore be flexible in order to cope
with the changes of customers- demand in terms of in-bound and outbound
goods and technological innovations. To remain higher service
level but lower cost management via the minimal imbalance scenario,
the rearrangement penalty of the area, in each zone, including time
periods are also included. However, the performance of the algorithm
depends on the appropriate parameters- setting and need to be
determined and analysed before its implementation. BEE parameters
are determined through the linear constrained response surface
optimisation or LCRSOM and weighted centroid modified simplex
methods or WCMSM. Experimental results were analysed in terms
of best solutions found so far, mean and standard deviation on the
imbalance values including the convergence of the solutions
obtained. It was found that the results obtained from the LCRSOM
were better than those using the WCMSM. However, the average
execution time of experimental run using the LCRSOM was longer
than those using the WCMSM. Finally a recommendation of proper
level settings of BEE parameters for some selected problem sizes is
given as a guideline for future applications.
Abstract: Computerized lip reading has been one of the most
actively researched areas of computer vision in recent past because
of its crime fighting potential and invariance to acoustic environment.
However, several factors like fast speech, bad pronunciation,
poor illumination, movement of face, moustaches and beards make
lip reading difficult. In present work, we propose a solution for
automatic lip contour tracking and recognizing letters of English
language spoken by speakers using the information available from
lip movements. Level set method is used for tracking lip contour
using a contour velocity model and a feature vector of lip movements
is then obtained. Character recognition is performed using modified
k nearest neighbor algorithm which assigns more weight to nearer
neighbors. The proposed system has been found to have accuracy
of 73.3% for character recognition with speaker lip movements as
the only input and without using any speech recognition system in
parallel. The approach used in this work is found to significantly
solve the purpose of lip reading when size of database is small.
Abstract: There are two common types of operational research techniques, optimisation and metaheuristic methods. The latter may be defined as a sequential process that intelligently performs the exploration and exploitation adopted by natural intelligence and strong inspiration to form several iterative searches. An aim is to effectively determine near optimal solutions in a solution space. In this work, a type of metaheuristics called Ant Colonies Optimisation, ACO, inspired by a foraging behaviour of ants was adapted to find optimal solutions of eight non-linear continuous mathematical models. Under a consideration of a solution space in a specified region on each model, sub-solutions may contain global or multiple local optimum. Moreover, the algorithm has several common parameters; number of ants, moves, and iterations, which act as the algorithm-s driver. A series of computational experiments for initialising parameters were conducted through methods of Rigid Simplex, RS, and Modified Simplex, MSM. Experimental results were analysed in terms of the best so far solutions, mean and standard deviation. Finally, they stated a recommendation of proper level settings of ACO parameters for all eight functions. These parameter settings can be applied as a guideline for future uses of ACO. This is to promote an ease of use of ACO in real industrial processes. It was found that the results obtained from MSM were pretty similar to those gained from RS. However, if these results with noise standard deviations of 1 and 3 are compared, MSM will reach optimal solutions more efficiently than RS, in terms of speed of convergence.
Abstract: Topology Optimization is a defined as the method of
determining optimal distribution of material for the assumed design
space with functionality, loads and boundary conditions [1].
Topology optimization can be used to optimize shape for the
purposes of weight reduction, minimizing material requirements or
selecting cost effective materials [2]. Topology optimization has been
implemented through the use of finite element methods for the
analysis, and optimization techniques based on the method of moving
asymptotes, genetic algorithms, optimality criteria method, level sets
and topological derivatives. Case study of Typical “Fuselage design"
is considered for this paper to explain the benefits of Topology
Optimization in the design cycle. A cylindrical shell is assumed as
the design space and aerospace standard pay loads were applied on
the fuselage with wing attachments as constraints. Then topological
optimization is done using Finite Element (FE) based software. This
optimization results in the structural concept design which satisfies
all the design constraints using minimum material.
Abstract: The class of geometric deformable models, so-called
level sets, has brought tremendous impact to medical imagery. In
this paper we present yet another application of level sets to medical
imaging. The method we give here will in a way modify the speed
term in the standard level sets equation of motion. To do so we
build a potential based on the distance and the gradient of the
image we study. In turn the potential gives rise to the force field:
F~F(x, y) = P
∀(p,q)∈I
((x, y) - (p, q)) |ÔêçI(p,q)|
|(x,y)-(p,q)|
2 . The direction
and intensity of the force field at each point will determine the
direction of the contour-s evolution. The images we used to test
our method were produced by the Univesit'e de Sherbrooke-s PET
scanners.
Abstract: The two-phase flow field and the motion of the free
surface in an oscillating channel are simulated numerically to assess
the methodology for simulating nuclear reacotr thermal hydraulics
under seismic conditions. Two numerical methods are compared: one
is to model the oscillating channel directly using the moving grid of
the Arbitrary Lagrangian-Eulerian method, and the other is to simulate
the effect of channel motion using the oscillating acceleration acting
on the fluid in the stationary channel. The two-phase flow field in the
oscillating channel is simulated using the level set method in both
cases. The calculated results using the oscillating acceleration are
found to coinside with those using the moving grid, and the theoretical
back ground and the limitation of oscillating acceleration are discussed.
It is shown that the change in the interfacial area between liquid and
gas phases under seismic conditions is important for nuclear reactor
thermal hydraulics.
Abstract: The flow field and the motion of the free surface in an
oscillating container are simulated numerically to assess the numerical
approach for studying two-phase flows under oscillating conditions.
Two numerical methods are compared: one is to model the oscillating
container directly using the moving grid of the ALE method, and the
other is to simulate the effect of container motion using the oscillating
body force acting on the fluid in the stationary container. The
two-phase flow field in the container is simulated using the level set
method in both cases. It is found that the calculated results by the body
force method coinsides with those by the moving grid method and the
sloshing behavior is predicted well by both the methods. Theoretical
back ground and limitation of the body force method are discussed,
and the effects of oscillation amplitude and frequency are shown.
Abstract: Transient shape variation of a rotating liquid dropletis
simulated numerically. The three dimensional Navier-Stokes
equations were solved by using the level set method. The shape
variation from the sphere to the rotating ellipsoid, and to the two-robed
shapeare simulated, and the elongation of the two-robed droplet is
discussed. The two-robed shape after the initial transient is found to be
stable and the elongation is almost the same for the cases with different
initial rotation rate. The relationship between the elongation and the
rotation rate is obtained by averaging the transient shape variation. It is
shown that the elongation of two-robed shape is in good agreement
with the existing experimental data. It is found that the transient
numerical simulation is necessary for analyzing the largely elongated
two-robed shape of rotating droplet.