Abstract: Red blood cells (RBC) are the most common types of
blood cells and are the most intensively studied in cell biology. The
lack of RBCs is a condition in which the amount of hemoglobin level
is lower than normal and is referred to as “anemia”. Abnormalities in
RBCs will affect the exchange of oxygen. This paper presents a
comparative study for various techniques for classifying the RBCs as
normal or abnormal (anemic) using WEKA. WEKA is an open
source consists of different machine learning algorithms for data
mining applications. The algorithms tested are Radial Basis Function
neural network, Support vector machine, and K-Nearest Neighbors
algorithm. Two sets of combined features were utilized for
classification of blood cells images. The first set, exclusively consist
of geometrical features, was used to identify whether the tested blood
cell has a spherical shape or non-spherical cells. While the second
set, consist mainly of textural features was used to recognize the
types of the spherical cells. We have provided an evaluation based on
applying these classification methods to our RBCs image dataset
which were obtained from Serdang Hospital - Malaysia, and
measuring the accuracy of test results. The best achieved
classification rates are 97%, 98%, and 79% for Support vector
machines, Radial Basis Function neural network, and K-Nearest
Neighbors algorithm respectively.
Abstract: In this study, epoxy composite specimens reinforced
with multi-walled carbon nanotube filler were fabricated using shear
mixer and ultra-sonication processor. The mechanical and thermal
properties of the fabricated specimens were measured and evaluated.
From the electron microscope images and the results from the
measurements of tensile strengths, the specimens having 0.6 wt%
nanotube content show better dispersion and higher strength than those
of the other specimens. The Young’s moduli of the specimens
increased as the contents of the nanotube filler in the matrix were
increased. The specimen having a 0.6 wt% nanotube filler content
showed higher thermal conductivity than that of the other specimens.
While, in the measurement of thermal expansion, specimens having
0.4 and 0.6 wt% filler contents showed a lower value of thermal
expansion than that of the other specimens. On the basis of the
measured and evaluated properties of the composites, we believe that
the simple and time-saving fabrication process used in this study was
sufficient to obtain improved properties of the specimens.
Abstract: Floods play a key role in landform evolution of an
area. This process is likely to alter the topography of the earth’s
surface. The present study area, Kota Bharu is very prone to floods
extends from upstream of Kelantan River near Kemubu to the
downstream area near Kuala Besar. These flood events which occur
every year in the study area exhibit a strong bearing on river
morphological set-up. In the present study, three satellite imageries of
different time periods have been used to manifest the post-flood
landform changes. The pre-processing of the images such as subset,
geometric corrections and atmospheric corrections were carried-out
using ENVI 4.5 followed by the analysis processes. Twenty sets of
cross sections were plotted using software Erdas 9.2, ERDAS and
ArcGis 10 for the all three images. The results show a significant
change in the length of the cross section which suggest that the
geomorphological processes play a key role in carving and shaping
the river banks during the floods.
Abstract: The fuzzy composition of objects depicted in images
acquired through MR imaging or the use of bio-scanners has often
been a point of controversy for field experts attempting to effectively
delineate between the visualized objects. Modern approaches in
medical image segmentation tend to consider fuzziness as a
characteristic and inherent feature of the depicted object, instead of
an undesirable trait. In this paper, a novel technique for efficient
image retrieval in the context of images in which segmented objects
are either crisp or fuzzily bounded is presented. Moreover, the
proposed method is applied in the case of multiple, even conflicting,
segmentations from field experts. Experimental results demonstrate
the efficiency of the suggested method in retrieving similar objects
from the aforementioned categories while taking into account the
fuzzy nature of the depicted data.
Abstract: Images are important source of information used as
evidence during any investigation process. Their clarity and accuracy
is essential and of the utmost importance for any investigation.
Images are vulnerable to losing blocks and having noise added to
them either after alteration or when the image was taken initially,
therefore, having a high performance image processing system and it
is implementation is very important in a forensic point of view. This
paper focuses on improving the quality of the forensic images.
For different reasons packets that store data can be affected,
harmed or even lost because of noise. For example, sending the
image through a wireless channel can cause loss of bits. These types
of errors might give difficulties generally for the visual display
quality of the forensic images.
Two of the images problems: noise and losing blocks are covered.
However, information which gets transmitted through any way of
communication may suffer alteration from its original state or even
lose important data due to the channel noise. Therefore, a developed
system is introduced to improve the quality and clarity of the forensic
images.
Abstract: Tumor is an uncontrolled growth of tissues in any part
of the body. Tumors are of different types and they have different
characteristics and treatments. Brain tumor is inherently serious and
life-threatening because of its character in the limited space of the
intracranial cavity (space formed inside the skull). Locating the tumor
within MR (magnetic resonance) image of brain is integral part of the
treatment of brain tumor. This segmentation task requires
classification of each voxel as either tumor or non-tumor, based on
the description of the voxel under consideration. Many studies are
going on in the medical field using Markov Random Fields (MRF) in
segmentation of MR images. Even though the segmentation process
is better, computing the probability and estimation of parameters is
difficult. In order to overcome the aforementioned issues, Conditional
Random Field (CRF) is used in this paper for segmentation, along
with the modified artificial bee colony optimization and modified
fuzzy possibility c-means (MFPCM) algorithm. This work is mainly
focused to reduce the computational complexities, which are found in
existing methods and aimed at getting higher accuracy. The
efficiency of this work is evaluated using the parameters such as
region non-uniformity, correlation and computation time. The
experimental results are compared with the existing methods such as
MRF with improved Genetic Algorithm (GA) and MRF-Artificial
Bee Colony (MRF-ABC) algorithm.
Abstract: Oases are complex and fragile agro-ecosystems. They
have always existed in environments characterized by an arid climate,
scarcity of rainfall, high temperatures and high evaporation. These
palms have grown up despite the severity of the physical
characteristics thanks to the water's existence and irrigation practice.
The oases are generally spread along non-perennial rivers (wadis),
shallow water table or deep artesian groundwater. However, the
sustainability of oasis system is threatened by water scarcity and
declining of water table levels particularly in arid areas. Located in
the southern east area of Morocco, Tafilalet plain encompasses one of
the largest palm groves in the kingdom. In recent years, this area has
become increasingly threatened by water shortage and has seen a
sharp deterioration under the effect of several combined
anthropogenic and climatic factors. The Bayoud disease, successive
years of drought, Hassan Addakhil dam construction etc are all
factors that have affected both water and phoenicicole heritage of the
area. The objective of this study is to understand the interaction
between qualitative and quantitative degradation of groundwater
resources, and the palm grove dynamics, while reviewing the
assumption that groundwater resources contribute in a direct way to
the conservation of this oasis agroecosystem. A historical analysis
tracing both the oasis dynamics and the groundwater evolution has
been established. Data were collected from satellite images, surveys
with different actors (farmers, Regional Office for Agricultural
Development, Basin agency...). They were complemented by a
synthesis of numerous technical reports in the area. The results
showed that within 40 years, the thickness of the groundwater table
has dropped in 50 %. Along with this, there has been a downsizing of
date palm by 50 %. Areas with higher groundwater level were the
least affected by the downsizing. So we can say that the shallow
groundwater contribute significantly and directly to the water supply
of date palm through its root system, and largely ensures the oasis
ecosystem sustainability.
Abstract: Augmented Reality is a technology that involves the
overlay of virtual content, which is context or environment sensitive,
on images of the physical world in real time. This paper presents the
development of a catalog system that facilitates and allows the
creation, publishing, management and exploitation of augmented
multimedia contents and Augmented Reality applications, creating an
own space for anyone that wants to provide information to real
objects in order to edit and share it then online with others. These
spaces would be built for different domains without the initial need of
expert users. Its operation focuses on the context of Web 2.0 or
Social Web, with its various applications, developing contents to
enrich the real context in which human beings act permitting the
evolution of catalog’s contents in an emerging way.
Abstract: Sports games conducted as a group are a form of
therapeutic exercise for aged people with decreased strength and for
people suffering from permanent damage of stroke and other
conditions. However, it is difficult for patients with different athletic
abilities to play a game on an equal footing. This study specifically
examines a computer video game designed for therapeutic exercise,
and a game system with support given depending on athletic ability.
Thereby, anyone playing the game can participate equally. This
video-game, to be specific, is a popular variant of balloon volleyball,
in which players hit a balloon by hand before it falls to the floor. In this
game system, each player plays the game watching a monitor on which
the system displays tailor-made video-game images adjusted to the
person’s athletic ability, providing players with player-adaptive assist
support. We have developed a multiplayer game system with an image
generation technique for the tailor-made video-game and conducted
tests to evaluate it.
Abstract: Skin detection is an important task for computer
vision systems. A good method of skin detection means a good and
successful result of the system.
The colour is a good descriptor for image segmentation and
classification; it allows detecting skin colour in the images. The
lighting changes and the objects that have a colour similar than skin
colour make the operation of skin detection difficult.
In this paper, we proposed a method using the YCbCr colour space
for skin detection and lighting effects elimination, then we use the
information of texture to eliminate the false regions detected by the
YCbCr skin model.
Abstract: The Quad Tree Decomposition based performance
analysis of compressed image data communication for lossy and
lossless through wireless sensor network is presented. Images have
considerably higher storage requirement than text. While transmitting
a multimedia content there is chance of the packets being dropped
due to noise and interference. At the receiver end the packets that
carry valuable information might be damaged or lost due to noise,
interference and congestion. In order to avoid the valuable
information from being dropped various retransmission schemes have
been proposed. In this proposed scheme QTD is used. QTD is an
image segmentation method that divides the image into homogeneous
areas. In this proposed scheme involves analysis of parameters such
as compression ratio, peak signal to noise ratio, mean square error,
bits per pixel in compressed image and analysis of difficulties during
data packet communication in Wireless Sensor Networks. By
considering the above, this paper is to use the QTD to improve the
compression ratio as well as visual quality and the algorithm in
MATLAB 7.1 and NS2 Simulator software tool.
Abstract: Nowadays, the Web has become one of the most
pervasive platforms for information change and retrieval. It collects
the suitable and perfectly fitting information from websites that one
requires. Data mining is the form of extracting data’s available in the
internet. Web mining is one of the elements of data mining
Technique, which relates to various research communities such as
information recovery, folder managing system and simulated
intellects. In this Paper we have discussed the concepts of Web
mining. We contain generally focused on one of the categories of
Web mining, specifically the Web Content Mining and its various
farm duties. The mining tools are imperative to scanning the many
images, text, and HTML documents and then, the result is used by
the various search engines. We conclude by presenting a comparative
table of these tools based on some pertinent criteria.
Abstract: Medical imaging produces human body pictures in
digital form. Since these imaging techniques produce prohibitive
amounts of data, compression is necessary for storage and
communication purposes. Many current compression schemes
provide a very high compression rate but with considerable loss of
quality. On the other hand, in some areas in medicine, it may be
sufficient to maintain high image quality only in region of interest
(ROI). This paper discusses a contribution to the lossless
compression in the region of interest of Scintigraphic images based
on SPIHT algorithm and global transform thresholding using
Huffman coding.
Abstract: The purpose of this study was to investigate graduate
students’ visual attention and perceptions of a Prezi presentation. Ten
postgraduate master students were presented with a Prezi presentation
at the Centre for Instructional Technology and Multimedia, Universiti
Sains Malaysia (USM). The eye movement indicators such as dwell
time, average fixation on the areas of interests, heat maps and focus
maps were abstracted to indicate the students’ visual attention.
Descriptive statistics was employed to analyze the students’
perception of the Prezi presentation in terms of text, slide design,
images, layout and overall presentation. The result revealed that the
students paid more attention to the text followed by the images and
sub heading presented through the Prezi presentation.
Abstract: The phased-array ultrasound transducer types are
utilities for medical ultrasonography as well as optical imaging.
However, their discontinuity characteristic limits the applications due
to the artifacts contaminated into the reconstructed images. Because
of the effects of the ultrasound pressure field pattern to the echo
ultrasonic waves as well as the optical modulated signal, the side
lobes of the focused ultrasound beam induced by discontinuity of the
phased-array ultrasound transducer might the reason of the artifacts.
In this paper, a simple method in approach of numerical simulation
was used to investigate the limitation of discontinuity of the elements
in phased-array ultrasound transducer and their effects to the
ultrasound pressure field. Take into account the change of ultrasound
pressure field patterns in the conditions of variation of the pitches
between elements of the phased-array ultrasound transducer, the
appropriated parameters for phased-array ultrasound transducer
design were asserted quantitatively.
Abstract: Medical imaging technology has experienced a
dramatic change in the last few years. Medical imaging refers to the
techniques and processes used to create images of the human body
(or parts thereof) for various clinical purposes such as medical
procedures and diagnosis or medical science including the study of
normal anatomy and function. With the growth of computers and
image technology, medical imaging has greatly influenced the
medical field. The diagnosis of a health problem is now highly
dependent on the quality and the credibility of the image analysis.
This paper deals with the various aspects and types of medical
imaging.
Abstract: Different strategies and tools are available at the oil
and gas industry for detecting and analyzing tension and possible
fractures in borehole walls. Most of these techniques are based on
manual observation of the captured borehole images. While this
strategy may be possible and convenient with small images and few
data, it may become difficult and suitable to errors when big
databases of images must be treated. While the patterns may differ
among the image area, depending on many characteristics (drilling
strategy, rock components, rock strength, etc.). In this work we
propose the inclusion of data-mining classification strategies in order
to create a knowledge database of the segmented curves. These
classifiers allow that, after some time using and manually pointing
parts of borehole images that correspond to tension regions and
breakout areas, the system will indicate and suggest automatically
new candidate regions, with higher accuracy. We suggest the use of
different classifiers methods, in order to achieve different knowledge
dataset configurations.
Abstract: Advances technology in the field of photogrammetry
replaces analog cameras with reflection on aircraft GPS/IMU system
with a digital aerial camera. In this system, when determining the
position of the camera with the GPS, camera rotations are also
determined by the IMU systems. All around the world, digital aerial
cameras have been used for the photogrammetry applications in the
last ten years. In this way, in terms of the work done in
photogrammetry it is possible to use time effectively, costs to be
reduced to a minimum level, the opportunity to make fast and
accurate.
Geo-referencing techniques that are the cornerstone of the GPS /
INS systems, photogrammetric triangulation of images required for
balancing (interior and exterior orientation) brings flexibility to the
process. Also geo-referencing process; needed in the application of
photogrammetry targets to help to reduce the number of ground
control points. In this study, the use of direct and indirect georeferencing
techniques on the accuracy of the points was investigated
in the production of photogrammetric mapping.
Abstract: The system is designed to show images which are
related to the query image. Extracting color, texture, and shape
features from an image plays a vital role in content-based image
retrieval (CBIR). Initially RGB image is converted into HSV color
space due to its perceptual uniformity. From the HSV image, Color
features are extracted using block color histogram, texture features
using Haar transform and shape feature using Fuzzy C-means
Algorithm. Then, the characteristics of the global and local color
histogram, texture features through co-occurrence matrix and Haar
wavelet transform and shape are compared and analyzed for CBIR.
Finally, the best method of each feature is fused during similarity
measure to improve image retrieval effectiveness and accuracy.
Abstract: Color Histogram is considered as the oldest method
used by CBIR systems for indexing images. In turn, the global
histograms do not include the spatial information; this is why the
other techniques coming later have attempted to encounter this
limitation by involving the segmentation task as a preprocessing step.
The weak segmentation is employed by the local histograms while
other methods as CCV (Color Coherent Vector) are based on strong
segmentation. The indexation based on local histograms consists of
splitting the image into N overlapping blocks or sub-regions, and
then the histogram of each block is computed. The dissimilarity
between two images is reduced, as consequence, to compute the
distance between the N local histograms of the both images resulting
then in N*N values; generally, the lowest value is taken into account
to rank images, that means that the lowest value is that which helps to
designate which sub-region utilized to index images of the collection
being asked. In this paper, we make under light the local histogram
indexation method in the hope to compare the results obtained against
those given by the global histogram. We address also another
noteworthy issue when Relying on local histograms namely which
value, among N*N values, to trust on when comparing images, in
other words, which sub-region among the N*N sub-regions on which
we base to index images. Based on the results achieved here, it seems
that relying on the local histograms, which needs to pose an extra
overhead on the system by involving another preprocessing step
naming segmentation, does not necessary mean that it produces better
results. In addition to that, we have proposed here some ideas to
select the local histogram on which we rely on to encode the image
rather than relying on the local histogram having lowest distance with
the query histograms.