Abstract: Arbitrarily shaped video objects are an important
concept in modern video coding methods. The techniques presently
used are not based on image elements but rather video objects having
an arbitrary shape. In this paper, spatial shape error concealment
techniques to be used for object-based image in error-prone
environments are proposed. We consider a geometric shape
representation consisting of the object boundary, which can be
extracted from the α-plane. Three different approaches are used to
replace a missing boundary segment: Bézier interpolation, Bézier
approximation and NURBS approximation. Experimental results on
object shape with different concealment difficulty demonstrate the
performance of the proposed methods. Comparisons with proposed
methods are also presented.
Abstract: Mammographic images and data analysis to
facilitate modelling or computer aided diagnostic (CAD) software development should best be done using a common database that can handle various mammographic image file
formats and relate these to other patient information.
This would optimize the use of the data as both primary
reporting and enhanced information extraction of research data could be performed from the single dataset. One desired
improvement is the integration of DICOM file header information into the database, as an efficient and reliable source of supplementary patient information intrinsically
available in the images.
The purpose of this paper was to design a suitable database to link and integrate different types of image files and gather common information that can be further used for research
purposes. An interface was developed for accessing, adding,
updating, modifying and extracting data from the common
database, enhancing the future possible application of the data in CAD processing.
Technically, future developments envisaged include the creation of an advanced search function to selects image files
based on descriptor combinations. Results can be further used for specific CAD processing and other research. Design of a
user friendly configuration utility for importing of the required fields from the DICOM files must be done.
Abstract: Marketing is an essential issue to the survival of any
real estate company in Turkey. There are some factors which are
constraining the achievements of the marketing and sales strategies in
the Turkey real estate industry. This study aims to identify and
prioritise the most significant constraints to marketing in real estate
sector and new strategies based on those constraints. This study is
based on survey method, where the respondents such as credit
counsellors, real estate investors, consultants, academicians and
marketing representatives in Turkey were asked to rank forty seven
sub-factors according to their levels of impact. The results of Multiattribute
analytical technique indicated that the main subcomponents
having impact on marketing in real estate sector are interest rates, real
estate credit availability, accessibility, company image and consumer
real income, respectively. The identified constraints are expected to
guide the marketing team in a sales-effective way.
Abstract: The distinction among urban, periurban and rural areas represents a classical example of uncertainty in land classification. Satellite images, geostatistical analysis and all kinds of spatial data are very useful in urban sprawl studies, but it is important to define precise rules in combining great amounts of data to build complex knowledge about territory. Rough Set theory may be a useful method to employ in this field. It represents a different mathematical approach to uncertainty by capturing the indiscernibility. Two different phenomena can be indiscernible in some contexts and classified in the same way when combining available information about them. This approach has been applied in a case of study, comparing the results achieved with both Map Algebra technique and Spatial Rough Set. The study case area, Potenza Province, is particularly suitable for the application of this theory, because it includes 100 municipalities with different number of inhabitants and morphologic features.
Abstract: Classifier fusion may generate more accurate
classification than each of the basic classifiers. Fusion is often based
on fixed combination rules like the product, average etc. This paper
presents decision templates as classifier fusion method for the
recognition of the handwritten English and Farsi numerals (1-9).
The process involves extracting a feature vector on well-known
image databases. The extracted feature vector is fed to multiple
classifier fusion. A set of experiments were conducted to compare
decision templates (DTs) with some combination rules. Results from
decision templates conclude 97.99% and 97.28% for Farsi and
English handwritten digits.
Abstract: This paper presents a new fingerprint coding technique
based on contourlet transform and multistage vector quantization.
Wavelets have shown their ability in representing natural images that
contain smooth areas separated with edges. However, wavelets
cannot efficiently take advantage of the fact that the edges usually
found in fingerprints are smooth curves. This issue is addressed by
directional transforms, known as contourlets, which have the
property of preserving edges. The contourlet transform is a new
extension to the wavelet transform in two dimensions using
nonseparable and directional filter banks. The computation and
storage requirements are the major difficulty in implementing a
vector quantizer. In the full-search algorithm, the computation and
storage complexity is an exponential function of the number of bits
used in quantizing each frame of spectral information. The storage
requirement in multistage vector quantization is less when compared
to full search vector quantization. The coefficients of contourlet
transform are quantized by multistage vector quantization. The
quantized coefficients are encoded by Huffman coding. The results
obtained are tabulated and compared with the existing wavelet based
ones.
Abstract: This research project is developed in order to study
managerial styles of modern Thai executives. The thorough
understanding will lead to continuous improvement and efficient
performance of Thai business organizations. Regarding managerial
skills, Thai executives focus heavily upon human skills. Also, the
negotiator roles are most emphasis in their management. In addition,
Thai executives pay most attention to the fundamental management
principles including Harmony and Unity of Direction of the
organizations. Moreover, the management techniques, consisting of
Team work and Career Planning are of their main concern. Finally,
Thai executives wish to enhance their firms- image and employees-
morale through conducting the ethical and socially responsible
activities. The major tactic deployed to stimulate employees- ethical
behaviors and mindset is Code of Ethics development.
Abstract: This paper presented two new efficient algorithms
for contour approximation. The proposed algorithm is compared
with Ramer (good quality), Triangle (faster) and Trapezoid (fastest)
in this work; which are briefly described. Cartesian co-ordinates of
an input contour are processed in such a manner that finally
contours is presented by a set of selected vertices of the edge of the
contour. In the paper the main idea of the analyzed procedures for
contour compression is performed. For comparison, the mean
square error and signal-to-noise ratio criterions are used.
Computational time of analyzed methods is estimated depending on
a number of numerical operations. Experimental results are
obtained both in terms of image quality, compression ratios, and
speed. The main advantages of the analyzed algorithm is small
numbers of the arithmetic operations compared to the existing
algorithms.
Abstract: This paper describes a new measuring algorithm for
three-dimensional (3-D) braided composite material .Braided angle is
an important parameter of braided composites. The objective of this
paper is to present an automatic measuring system. In the paper, the
algorithm is performed by using vcµ6.0 language on PC. An
advanced filtered algorithm for image of 3-D braided composites
material performs has been developed. The procedure is completely
automatic and relies on the gray scale information content of the
images and their local wavelet transform modulus maxims.
Experimental results show that the proposed method is feasible.
The algorithm was tested on both carbon-fiber and glass-fiber
performs.
Abstract: The design of an active leg orthosis for tumble
protection is proposed in this paper. The orthosis would be applied to
assist elders or invalids in rebalancing while they fall unexpectedly.
We observe the regain balance motion of healthy and youthful people,
and find the difference to elders or invalids. First, the physical model
of leg would be established, and we consider the leg motions are
achieve through four joints (phalanx stem, ankle, knee, and hip joint)
and five links (phalanges, talus, tibia, femur, and hip bone). To
formulate the dynamic equations, the coordinates which can clearly
describe the position in 3D space are first defined accordance with the
human movement of leg, and the kinematics and dynamics of the leg
movement can be formulated based on the robotics. For the purpose,
assisting elders and invalids in avoiding tumble, the posture variation
of unbalance and regaining balance motion are recorded by the
motion-capture image system, and the trajectory is taken as the desire
one. Then we calculate the force and moment of each joint based on
the leg motion model through programming MATLAB code. The
results would be primary information of the active leg orthosis design
for tumble protection.
Abstract: The main purpose of this study is to analyze the
relationship of leisure agriculture park visitors on tourist destination
image, environmental perception, travel experiences and revisiting
willingness. This study used questionnaires to Xinshe leisure
agriculture park visitors- targeted convenience sampling manner total
of 636 valid questionnaires. Valid questionnaires by descriptive
statistics, correlation analysis and multiple regression analysis, the
study found that: 1. The agricultural park visitors- correlations exist
between the destination image, perception of the environment, tourism
experience and revisiting willingness. 2."Excellent facilities and
services", "space atmosphere comfortable" and "the spacious paternity
outdoor space" imagery, of visitors- "revisiting willingness predict. 3.
Visitors- in leisure agriculture park "environmental perception" and
"travel experience, future revisiting willingness predict. According to
the analysis of the results, the study not only operate on the
recommendations of the leisure farm owners also provide follow-up
study direction for future researchers.
Abstract: The general idea behind the filter is to average a pixel
using other pixel values from its neighborhood, but simultaneously to
take care of important image structures such as edges. The main
concern of the proposed filter is to distinguish between any variations
of the captured digital image due to noise and due to image structure.
The edges give the image the appearance depth and sharpness. A
loss of edges makes the image appear blurred or unfocused.
However, noise smoothing and edge enhancement are traditionally
conflicting tasks. Since most noise filtering behaves like a low pass
filter, the blurring of edges and loss of detail seems a natural
consequence. Techniques to remedy this inherent conflict often
encompass generation of new noise due to enhancement.
In this work a new fuzzy filter is presented for the noise reduction
of images corrupted with additive noise. The filter consists of three
stages. (1) Define fuzzy sets in the input space to computes a fuzzy
derivative for eight different directions (2) construct a set of IFTHEN
rules by to perform fuzzy smoothing according to
contributions of neighboring pixel values and (3) define fuzzy sets in
the output space to get the filtered and edged image.
Experimental results are obtained to show the feasibility of the
proposed approach with two dimensional objects.
Abstract: Retinal vascularity assessment plays an important role in diagnosis of ophthalmic pathologies. The employment of digital images for this purpose makes possible a computerized approach and has motivated development of many methods for automated vascular tree segmentation. Metrics based on contingency tables for binary classification have been widely used for evaluating performance of these algorithms and, concretely, the accuracy has been mostly used as measure of global performance in this topic. However, this metric shows very poor matching with human perception as well as other notable deficiencies. Here, a new similarity function for measuring quality of retinal vessel segmentations is proposed. This similarity function is based on characterizing the vascular tree as a connected structure with a measurable area and length. Tests made indicate that this new approach shows better behaviour than the current one does. Generalizing, this concept of measuring descriptive properties may be used for designing functions for measuring more successfully segmentation quality of other complex structures.
Abstract: Image interpolation is a common problem in imaging applications. However, most interpolation algorithms in existence suffer visually the effects of blurred edges and jagged artifacts in the image to some extent. This paper presents an adaptive feature preserving bidirectional flow process, where an inverse diffusion is performed to sharpen edges along the normal directions to the isophote lines (edges), while a normal diffusion is done to remove artifacts (“jaggies") along the tangent directions. In order to preserve image features such as edges, corners and textures, the nonlinear diffusion coefficients are locally adjusted according to the directional derivatives of the image. Experimental results on synthetic images and nature images demonstrate that our interpolation algorithm substantially improves the subjective quality of the interpolated images over conventional interpolations.
Abstract: The capturing of gel electrophoresis image represents
the output of a DNA computing algorithm. Before this image is being
captured, DNA computing involves parallel overlap assembly (POA)
and polymerase chain reaction (PCR) that is the main of this
computing algorithm. However, the design of the DNA
oligonucleotides to represent a problem is quite complicated and is
prone to errors. In order to reduce these errors during the design stage
before the actual in-vitro experiment is carried out; a simulation
software capable of simulating the POA and PCR processes is
developed. This simulation software capability is unlimited where
problem of any size and complexity can be simulated, thus saving
cost due to possible errors during the design process. Information
regarding the DNA sequence during the computing process as well as
the computing output can be extracted at the same time using the
simulation software.
Abstract: This paper presents the application of a signal
intensity independent registration criterion for 2D rigid body
registration of medical images using 1D binary projections. The
criterion is defined as the weighted ratio of two projections. The ratio
is computed on a pixel per pixel basis and weighting is performed by
setting the ratios between one and zero pixels to a standard high
value. The mean squared value of the weighted ratio is computed
over the union of the one areas of the two projections and it is
minimized using the Chebyshev polynomial approximation using
n=5 points. The sum of x and y projections is used for translational
adjustment and a 45deg projection for rotational adjustment. 20 T1-
T2 registration experiments were performed and gave mean errors
1.19deg and 1.78 pixels. The method is suitable for contour/surface
matching. Further research is necessary to determine the robustness
of the method with regards to threshold, shape and missing data.
Abstract: The purpose of this study is to introduce a new
interface program to calculate a dose distribution with Monte Carlo method in complex heterogeneous systems such as organs or tissues
in proton therapy. This interface program was developed under
MATLAB software and includes a friendly graphical user interface
with several tools such as image properties adjustment or results display. Quadtree decomposition technique was used as an image
segmentation algorithm to create optimum geometries from Computed Tomography (CT) images for dose calculations of proton
beam. The result of the mentioned technique is a number of nonoverlapped
squares with different sizes in every image. By this way
the resolution of image segmentation is high enough in and near
heterogeneous areas to preserve the precision of dose calculations
and is low enough in homogeneous areas to reduce the number of
cells directly. Furthermore a cell reduction algorithm can be used to combine neighboring cells with the same material. The validation of this method has been done in two ways; first, in comparison with experimental data obtained with 80 MeV proton beam in Cyclotron
and Radioisotope Center (CYRIC) in Tohoku University and second, in comparison with data based on polybinary tissue calibration method, performed in CYRIC. These results are presented in this paper. This program can read the output file of Monte Carlo code while region of interest is selected manually, and give a plot of dose distribution of proton beam superimposed onto the CT images.
Abstract: In this paper we present a new approach to deal with
image segmentation. The fact that a single segmentation result do not
generally allow a higher level process to take into account all the
elements included in the image has motivated the consideration of
image segmentation as a multiobjective optimization problem. The
proposed algorithm adopts a split/merge strategy that uses the result
of the k-means algorithm as input for a quantum evolutionary
algorithm to establish a set of non-dominated solutions. The
evaluation is made simultaneously according to two distinct features:
intra-region homogeneity and inter-region heterogeneity. The
experimentation of the new approach on natural images has proved
its efficiency and usefulness.
Abstract: Motor imagery classification provides an important basis for designing Brain Machine Interfaces [BMI]. A BMI captures and decodes brain EEG signals and transforms human thought into actions. The ability of an individual to control his EEG through imaginary mental tasks enables him to control devices through the BMI. This paper presents a method to design a four state BMI using EEG signals recorded from the C3 and C4 locations. Principle features extracted through principle component analysis of the segmented EEG are analyzed using two novel classification algorithms using Elman recurrent neural network and functional link neural network. Performance of both classifiers is evaluated using a particle swarm optimization training algorithm; results are also compared with the conventional back propagation training algorithm. EEG motor imagery recorded from two subjects is used in the offline analysis. From overall classification performance it is observed that the BP algorithm has higher average classification of 93.5%, while the PSO algorithm has better training time and maximum classification. The proposed methods promises to provide a useful alternative general procedure for motor imagery classification
Abstract: The normalized difference vegetation index (NDVI)
and normalized difference moisture index (NDMI) derived from the
moderate resolution imaging spectroradiometer (MODIS) have been
widely used to identify spatial information of drought condition. The
relationship between NDVI and NDMI has been analyzed using
Pearson correlation analysis and showed strong positive relationship.
The drought indices have detected drought conditions and identified
spatial extents of drought. A comparison between normal year and
drought year demonstrates that the amplitude analysis considered both
vegetation and moisture condition is an effective method to identify
drought condition. We proposed the amplitude analysis is useful for
quick spatial assessment of drought information at a regional scale.