Abstract: Remote sensing plays a vital role in mapping of
resources and monitoring of environments of the earth. In the present
research study, mapping and monitoring of clay siltations occurred in
the Alkhod Dam of Muscat, Sultanate of Oman are carried out using
low-cost multispectral Landsat and ASTER data. The dam is
constructed across the Wadi Samail catchment for ground water
recharge. The occurrence and spatial distribution of siltations in the
dam are studied with five years of interval from the year 1987 of
construction to 2014. The deposits are mainly due to the clay, sand
and silt occurrences derived from the weathering rocks of ophiolite
sequences occurred in the Wadi Samail catchment. The occurrences
of clays are confirmed by minerals identification using ASTER
VNIR-SWIR spectral bands and Spectral Angle Mapper supervised
image processing method. The presence of clays and their spatial
distribution are verified in the field. The study recommends the
technique and the low-cost satellite data to similar region of the
world.
Abstract: This article is trying to determine the status of flue gas
that is entering the KWH heat exchanger from combustion chamber
in order to calculate the heat transfer ratio of the heat exchanger.
Combination of measurement, calculation and computer simulation
was used to create a useful way to approximate the heat transfer rate.
The measurements were taken by a number of sensors that are
mounted on the experimental device and by a thermal imaging
camera. The results of the numerical calculation are in a good
correspondence with the real power output of the experimental
device. That result shows that the research has a good direction and
can be used to propose changes in the construction of the heat
exchanger, but still needs enhancements.
Abstract: This paper presents an efficient fusion algorithm for
iris images to generate stable feature for recognition in unconstrained
environment. Recently, iris recognition systems are focused on real
scenarios in our daily life without the subject’s cooperation. Under
large variation in the environment, the objective of this paper is to
combine information from multiple images of the same iris. The
result of image fusion is a new image which is more stable for further
iris recognition than each original noise iris image. A wavelet-based
approach for multi-resolution image fusion is applied in the fusion
process. The detection of the iris image is based on Adaboost
algorithm and then local binary pattern (LBP) histogram is then
applied to texture classification with the weighting scheme.
Experiment showed that the generated features from the proposed
fusion algorithm can improve the performance for verification system
through iris recognition.
Abstract: Generally the natural environment is made up of air,
water and soil. The release of emission of industrial waste into
anyone of the components of the environment causes pollution.
Industrial pollution significantly threatens the inherent right of
people, to the enjoyment of a safe and secure environment. The aim
of this paper is to assess the effect of environmental pollution and
health risks of residents living near Ewekoro cement factory. The
research made use of IKONOS imagery for Geographical
Information System (GIS) to buffer and extract buildings that are less
than 1km to the factory, within 1km to 5km and above 5km to the
factory. Also questionnaire was used to elicit information on the
socio-economic factors, effect of environmental pollution on
residents and measures adopted to control industrial pollution on the
residents. Findings show that most buildings that fall between less
than 1km and 1km to 5km to the factory have high health risk in the
study area. The study recommended total relocation for the residents
of the study area to reduce health risk problems.
Abstract: Modelling of the earth's surface and evaluation of
urban environment, with 3D models, is an important research topic.
New stereo capabilities of high resolution optical satellites images,
such as the tri-stereo mode of Pleiades, combined with new image
matching algorithms, are now available and can be applied in urban
area analysis. In addition, photogrammetry software packages gained
new, more efficient matching algorithms, such as SGM, as well as
improved filters to deal with shadow areas, can achieve more dense
and more precise results.
This paper describes a comparison between 3D data extracted
from tri-stereo and dual stereo satellite images, combined with pixel
based matching and Wallis filter. The aim was to improve the
accuracy of 3D models especially in urban areas, in order to assess if
satellite images are appropriate for a rapid evaluation of urban
environments.
The results showed that 3D models achieved by Pleiades tri-stereo
outperformed, both in terms of accuracy and detail, the result
obtained from a Geo-eye pair. The assessment was made with
reference digital surface models derived from high resolution aerial
photography. This could mean that tri-stereo images can be
successfully used for the proposed urban change analyses.
Abstract: One image is worth more than thousand words.
Images if analyzed can reveal useful information. Low level image
processing deals with the extraction of specific feature from a single
image. Now the question arises: What technique should be used to
extract patterns of very large and detailed image database? The
answer of the question is: “Image Mining”. Image Mining deals with
the extraction of image data relationship, implicit knowledge, and
another pattern from the collection of images or image database. It is
nothing but the extension of Data Mining. In the following paper, not
only we are going to scrutinize the current techniques of image
mining but also present a new technique for mining images using
Genetic Algorithm.
Abstract: The aim of this study is to develop an anterior lumbar
interbody fusion (ALIF) PEEK cage suitable for Korean people. In this
study, CT images were obtained from Korean male (173cm, 71kg) and
3D Korean lumbar models were reconstructed based on the CT images
to investigate anatomical characteristics. Major design parameters of
anterior lumbar interbody fusion (ALIF) PEEK Cage were selected
using the morphological measurement information of the Korean
Lumbar models. Through finite element analysis and mechanical tests,
the developed ALIFPEEK Cage prototype was compared with the
Fidji Cage (Zimmer. Inc, USA) and it was found that the ALIF
prototype showed similar and/or superior mechanical performance
compared to the FidJi Cage. Also, clinical validation for the ALIF
PEEK Cage prototype was carried out to check predictable troubles in
surgical operations. Finally, it is considered that the convenience and
stability of the prototype was clinically verified.
Abstract: The present paper summarizes the analysis of the
request for consultation of information and data on industrial
emissions made publicly available on the web site of the Ministry of
Environment, Land and Sea on integrated pollution prevention and
control from large industrial installations, the so called “AIA Portal”.
As a matter of fact, a huge amount of information on national
industrial plants is already available on internet, although it is usually
proposed as textual documentation or images.
Thus, it is not possible to access all the relevant information
through interoperability systems and also to retrieval relevant
information for decision making purposes as well as rising of
awareness on environmental issue.
Moreover, since in Italy the number of institutional and private
subjects involved in the management of the public information on
industrial emissions is substantial, the access to the information is
provided on internet web sites according to different criteria; thus, at
present it is not structurally homogeneous and comparable.
To overcome the mentioned difficulties in the case of the
Coordinating Committee for the implementation of the Agreement
for the industrial area in Taranto and Statte, operating before the
IPPC permit granting procedures of the relevant installation located
in the area, a big effort was devoted to elaborate and to validate data
and information on characterization of soil, ground water aquifer and
coastal sea at disposal of different subjects to derive a global
perspective for decision making purposes. Thus, the present paper
also focuses on main outcomes matured during such experience.
Abstract: The increasing demand of gallium, indium and
rare-earth elements for the production of electronics, e.g. solid
state-lighting, photovoltaics, integrated circuits, and liquid crystal
displays, will exceed the world-wide supply according to current
forecasts. Recycling systems to reclaim these materials are not yet in
place, which challenges the sustainability of these technologies. This
paper proposes a multispectral imaging system as a basis for a vision
based recognition system for valuable components of electronics
waste. Multispectral images intend to enhance the contrast of images
of printed circuit boards (single components, as well as labels) for
further analysis, such as optical character recognition and entire
printed circuit board recognition. The results show, that a higher
contrast is achieved in the near infrared compared to ultraviolett and
visible light.
Abstract: Image search engines rely on the surrounding textual
keywords for the retrieval of images. It is a tedious work for the
search engines like Google and Bing to interpret the user’s search
intention and to provide the desired results. The recent researches
also state that the Google image search engines do not work well on
all the images. Consequently, this leads to the emergence of efficient
image retrieval technique, which interprets the user’s search intention
and shows the desired results. In order to accomplish this task, an
efficient image re-ranking framework is required. Sequentially, to
provide best image retrieval, the new image re-ranking framework is
experimented in this paper. The implemented new image re-ranking
framework provides best image retrieval from the image dataset by
making use of re-ranking of retrieved images that is based on the
user’s desired images. This is experimented in two sections. One is
offline section and other is online section. In offline section, the reranking
framework studies differently (reference classes or Semantic
Spaces) for diverse user query keywords. The semantic signatures get
generated by combining the textual and visual features of the images.
In the online section, images are re-ranked by comparing the
semantic signatures that are obtained from the reference classes with
the user specified image query keywords. This re-ranking
methodology will increases the retrieval image efficiency and the
result will be effective to the user.
Abstract: Image or document encryption is needed through egovernment
data base. Really in this paper we introduce two matrices
images, one is the public, and the second is the secret (original). The
analyses of each matrix is achieved using the transformation of
singular values decomposition. So each matrix is transformed or
analyzed to three matrices say row orthogonal basis, column
orthogonal basis, and spectral diagonal basis. Product of the two row
basis is calculated. Similarly the product of the two column basis is
achieved. Finally we transform or save the files of public, row
product and column product. In decryption stage, the original image
is deduced by mutual method of the three public files.
Abstract: In this article is reported a construction and some
properties of the 5iD viewer, the system recording simultaneously
5 views of a given experimental object. Properties of the system
are demonstrated on the analysis of fish schooling behaviour. It
is demonstrated the method of instrument calibration which allows
inclusion of image distortion and it is proposed and partly tested
also the method of distance assessment in the case that only two
opposite cameras are available. Finally, we demonstrate how the state
trajectory of the behaviour of the fish school may be constructed from
the entropy of the system.
Abstract: In medical imaging, segmentation of different areas of
human body like bones, organs, tissues, etc. is an important issue.
Image segmentation allows isolating the object of interest for further
processing that can lead for example to 3D model reconstruction of
whole organs. Difficulty of this procedure varies from trivial for
bones to quite difficult for organs like liver. The liver is being
considered as one of the most difficult human body organ to segment.
It is mainly for its complexity, shape versatility and proximity of
other organs and tissues. Due to this facts usually substantial user
effort has to be applied to obtain satisfactory results of the image
segmentation. Process of image segmentation then deteriorates from
automatic or semi-automatic to fairly manual one. In this paper,
overview of selected available software applications that can handle
semi-automatic image segmentation with further 3D volume
reconstruction of human liver is presented. The applications are being
evaluated based on the segmentation results of several consecutive
DICOM images covering the abdominal area of the human body.
Abstract: Digital image correlation (DIC) is a contactless fullfield
displacement and strain reconstruction technique commonly
used in the field of experimental mechanics. Comparing with
physical measuring devices, such as strain gauges, which only
provide very restricted coverage and are expensive to deploy widely,
the DIC technique provides the result with full-field coverage and
relative high accuracy using an inexpensive and simple experimental
setup. It is very important to study the natural patterns effect on the
DIC technique because the preparation of the artificial patterns is
time consuming and hectic process. The objective of this research is
to study the effect of using images having natural pattern on the
performance of DIC. A systematical simulation method is used to
build simulated deformed images used in DIC. A parameter (subset
size) used in DIC can have an effect on the processing and accuracy
of DIC and even cause DIC to failure. Regarding to the picture
parameters (correlation coefficient), the higher similarity of two
subset can lead the DIC process to fail and make the result more
inaccurate. The pictures with good and bad quality for DIC methods
have been presented and more importantly, it is a systematic way to
evaluate the quality of the picture with natural patterns before they
install the measurement devices.
Abstract: Leukaemia is a blood cancer disease that contributes
to the increment of mortality rate in Malaysia each year. There are
two main categories for leukaemia, which are acute and chronic
leukaemia. The production and development of acute leukaemia cells
occurs rapidly and uncontrollable. Therefore, if the identification of
acute leukaemia cells could be done fast and effectively, proper
treatment and medicine could be delivered. Due to the requirement of
prompt and accurate diagnosis of leukaemia, the current study has
proposed unsupervised pixel segmentation based on clustering
algorithm in order to obtain a fully segmented abnormal white blood
cell (blast) in acute leukaemia image. In order to obtain the
segmented blast, the current study proposed three clustering
algorithms which are k-means, fuzzy c-means and moving k-means
algorithms have been applied on the saturation component image.
Then, median filter and seeded region growing area extraction
algorithms have been applied, to smooth the region of segmented
blast and to remove the large unwanted regions from the image,
respectively. Comparisons among the three clustering algorithms are
made in order to measure the performance of each clustering
algorithm on segmenting the blast area. Based on the good sensitivity
value that has been obtained, the results indicate that moving kmeans
clustering algorithm has successfully produced the fully
segmented blast region in acute leukaemia image. Hence, indicating
that the resultant images could be helpful to haematologists for
further analysis of acute leukaemia.
Abstract: The problem of psychologist training remains a key
priority in Armenia. During the Soviet period, the notion of a
psychologist was obscure not only in Armenia but also in other
Soviet republics. The breakup of the Soviet Union triggered a gradual
change in this area activating the cooperation with specialists from
other countries. The need for recovery from the psychological trauma
caused by the 1988 earthquake pushed forward the development of
practical psychology in Armenia. This phenomenon led to positive
changes in perception of and interest to a psychologist
profession.Armenian universities started designing special programs
for psychologists’ preparation. Armenian psychologists combined
their efforts in the field of training relevant specialists.
During the recent years, the Bologna educational system was
introduced in Armenia which led to implementation of education
quality improvement programs. Nevertheless, even today the issue of
psychologists’ training is not yet settled in Armenian universities. So
far graduate psychologists haven’t got a clear idea of personal and
professional qualities of a psychologist. Recently, as a result of
educational reforms, the psychology curricula underwent changes,
but so far they have not led to a desired outcome. Almost all curricula
in certain specialties are aimed to form professional competencies
and strengthen practical skills.
A survey conducted in Armenia aimed to identify what are the
ideas of young psychology specialists on the image of a psychologist.
The survey respondents were 45 specialists holding bachelor’s degree
as well as 30 master degree graduates, who have not been working
yet. The research reveals that we need to change the approach of
preparing psychology practitioners in the universities of Armenia.
Such an approach to psychologist training will make it possible to
train qualified specialists for enhancement of modern psychology
theory and practice.
Abstract: Content-based image retrieval (CBIR) uses the
contents of images to characterize and contact the images. This paper
focus on retrieving the image by separating images into its three color
mechanism R, G and B and for that Discrete Wavelet Transformation
is applied. Then Wavelet based Generalized Gaussian Density (GGD)
is practical which is used for modeling the coefficients from the
wavelet transforms. After that it is agreed to Histogram of Oriented
Gradient (HOG) for extracting its characteristic vectors with Relevant
Feedback technique is used. The performance of this approach is
calculated by exactness and it confirms that this method is wellorganized
for image retrieval.
Abstract: The Simulation based VLSI Implementation of
FELICS (Fast Efficient Lossless Image Compression System)
Algorithm is proposed to provide the lossless image compression and
is implemented in simulation oriented VLSI (Very Large Scale
Integrated). To analysis the performance of Lossless image
compression and to reduce the image without losing image quality
and then implemented in VLSI based FELICS algorithm. In FELICS
algorithm, which consists of simplified adjusted binary code for
Image compression and these compression image is converted in
pixel and then implemented in VLSI domain. This parameter is used
to achieve high processing speed and minimize the area and power.
The simplified adjusted binary code reduces the number of arithmetic
operation and achieved high processing speed. The color difference
preprocessing is also proposed to improve coding efficiency with
simple arithmetic operation. Although VLSI based FELICS
Algorithm provides effective solution for hardware architecture
design for regular pipelining data flow parallelism with four stages.
With two level parallelisms, consecutive pixels can be classified into
even and odd samples and the individual hardware engine is
dedicated for each one. This method can be further enhanced by
multilevel parallelisms.
Abstract: In previous study, technique to estimate a self-location by using a lunar image is proposed.We consider the improvement of the conventional method in consideration of FPGA implementationin this paper. Specifically, we introduce Artificial Bee Colony algorithm for reduction of search time.In addition, we use fixed point arithmetic to enable high-speed operation on FPGA.
Abstract: Nowadays social media information, such as news,
links, images, or VDOs, is shared extensively. However, the
effectiveness of disseminating information through social media
lacks in quality: less fact checking, more biases, and several rumors.
Many researchers have investigated about credibility on Twitter, but
there is no the research report about credibility information on
Facebook. This paper proposes features for measuring credibility on
Facebook information. We developed the system for credibility on
Facebook. First, we have developed FB credibility evaluator for
measuring credibility of each post by manual human’s labelling. We
then collected the training data for creating a model using Support
Vector Machine (SVM). Secondly, we developed a chrome extension
of FB credibility for Facebook users to evaluate the credibility of
each post. Based on the usage analysis of our FB credibility chrome
extension, about 81% of users’ responses agree with suggested
credibility automatically computed by the proposed system.