Abstract: A typical definition of the Computer Aided Diagnosis
(CAD), found in literature, can be: A diagnosis made by a radiologist
using the output of a computerized scheme for automated image
analysis as a diagnostic aid. Often it is possible to find the expression
Computer Aided Detection (CAD or CADe): this definition
emphasizes the intent of CAD to support rather than substitute the
human observer in the analysis of radiographic images. In this article
we will illustrate the application of CAD systems and the aim of
these definitions.
Commercially available CAD systems use computerized
algorithms for identifying suspicious regions of interest. In this paper
are described the general CAD systems as an expert system
constituted of the following components: segmentation / detection,
feature extraction, and classification / decision making.
As example, in this work is shown the realization of a Computer-
Aided Detection system that is able to assist the radiologist in
identifying types of mammary tumor lesions. Furthermore this
prototype of station uses a GRID configuration to work on a large
distributed database of digitized mammographic images.
Abstract: During recent years, the traditional learning
approaches have undergone fundamental changes due to the
emergence of new technologies such as multimedia, hypermedia and
telecommunication. E-learning is a modern world phenomenon that
has come into existence in the information age and in a knowledgebased
society. E-learning has developed significantly within a short
period of time. Thus it is of a great significant to secure information,
allow a confident access and prevent unauthorized accesses. Making
use of individuals- physiologic or behavioral (biometric) properties is
a confident method to make the information secure. Among the
biometrics, fingerprint is more acceptable and most countries use it as
an efficient methods of identification. This article provides a new
method to compare the fingerprint comparison by pattern recognition
and image processing techniques. To verify fingerprint, the shortest
distance method is used together with perceptronic multilayer neural
network functioning based on minutiae. This method is highly
accurate in the extraction of minutiae and it accelerates comparisons
due to elimination of false minutiae and is more reliable compared
with methods that merely use directional images.
Abstract: The use of new technologies such internet (e-mail, chat
rooms) and cell phones has steeply increased in recent years.
Especially among children and young people, use of technological
tools and equipments is widespread. Although many teachers and
administrators now recognize the problem of school bullying, few are
aware that students are being harassed through electronic
communication. Referred to as electronic bullying, cyber bullying, or
online social cruelty, this phenomenon includes bullying through email,
instant messaging, in a chat room, on a website, or through
digital messages or images sent to a cell phone. Cyber bullying is
defined as causing deliberate/intentional harm to others using internet
or other digital technologies. It has a quantitative research design nd
uses relational survey as its method. The participants consisted of
300 secondary school students in the city of Konya, Turkey. 195
(64.8%) participants were female and 105 (35.2%) were male. 39
(13%) students were at grade 1, 187 (62.1%) were at grade 2 and 74
(24.6%) were at grade 3. The “Cyber Bullying Question List"
developed by Ar─▒cak (2009) was given to students. Following
questions about demographics, a functional definition of cyber
bullying was provided. In order to specify students- human values,
“Human Values Scale (HVS)" developed by Dilmaç (2007) for
secondary school students was administered. The scale consists of 42
items in six dimensions. Data analysis was conducted by the primary
investigator of the study using SPSS 14.00 statistical analysis
software. Descriptive statistics were calculated for the analysis of
students- cyber bullying behaviour and simple regression analysis was
conducted in order to test whether each value in the scale could
explain cyber bullying behaviour.
Abstract: In this work, the primary compressive strength
components of human femur trabecular bone are qualitatively
assessed using image processing and wavelet analysis. The Primary
Compressive (PC) component in planar radiographic femur trabecular
images (N=50) is delineated by semi-automatic image processing
procedure. Auto threshold binarization algorithm is employed to
recognize the presence of mineralization in the digitized images. The
qualitative parameters such as apparent mineralization and total area
associated with the PC region are derived for normal and abnormal
images.The two-dimensional discrete wavelet transforms are utilized
to obtain appropriate features that quantify texture changes in medical
images .The normal and abnormal samples of the human femur are
comprehensively analyzed using Harr wavelet.The six statistical
parameters such as mean, median, mode, standard deviation, mean
absolute deviation and median absolute deviation are derived at level
4 decomposition for both approximation and horizontal wavelet
coefficients. The correlation coefficient of various wavelet derived
parameters with normal and abnormal for both approximated and
horizontal coefficients are estimated. It is seen that in almost all cases
the abnormal show higher degree of correlation than normals. Further
the parameters derived from approximation coefficient show more
correlation than those derived from the horizontal coefficients. The
parameters mean and median computed at the output of level 4 Harr
wavelet channel was found to be a useful predictor to delineate the
normal and the abnormal groups.
Abstract: Breast skin-line estimation and breast segmentation is an important pre-process in mammogram image processing and computer-aided diagnosis of breast cancer. Limiting the area to be processed into a specific target region in an image would increase the accuracy and efficiency of processing algorithms. In this paper we are presenting a new algorithm for estimating skin-line and breast segmentation using fast marching algorithm. Fast marching is a partial-differential equation based numerical technique to track evolution of interfaces. We have introduced some modifications to the traditional fast marching method, specifically to improve the accuracy of skin-line estimation and breast tissue segmentation. Proposed modifications ensure that the evolving front stops near the desired boundary. We have evaluated the performance of the algorithm by using 100 mammogram images taken from mini-MIAS database. The results obtained from the experimental evaluation indicate that this algorithm explains 98.6% of the ground truth breast region and accuracy of the segmentation is 99.1%. Also this algorithm is capable of partially-extracting nipple when it is available in the profile.
Abstract: A camera in the building site is exposed to different
weather conditions. Differences between images of the same scene
captured with the same camera arise also due to temperature variations.
The influence of temperature changes on camera parameters
were modelled and integrated into existing analytical camera model.
Modified camera model enables quantitatively assessing the influence
of temperature variations.
Abstract: The purpose of this study is to investigate the effects
of modality principles in instructional software among first grade
pupils- achievements in the learning of Arabic Language. Two modes
of instructional software were systematically designed and
developed, audio with images (AI), and text with images (TI). The
quasi-experimental design was used in the study. The sample
consisted of 123 male and female pupils from IRBED Education
Directorate, Jordan. The pupils were randomly assigned to any one of
the two modes. The independent variable comprised the two modes
of the instructional software, the students- achievement levels in the
Arabic Language class and gender. The dependent variable was the
achievements of the pupils in the Arabic Language test. The
theoretical framework of this study was based on Mayer-s Cognitive
Theory of Multimedia Learning. Four hypotheses were postulated
and tested. Analyses of Variance (ANOVA) showed that pupils using
the (AI) mode performed significantly better than those using (TI)
mode. This study concluded that the audio with images mode was an
important aid to learning as compared to text with images mode.
Abstract: In recent years image watermarking has become an
important research area in data security, confidentiality and image
integrity. Many watermarking techniques were proposed for medical
images. However, medical images, unlike most of images, require
extreme care when embedding additional data within them because
the additional information must not affect the image quality and
readability. Also the medical records, electronic or not, are linked to
the medical secrecy, for that reason, the records must be confidential.
To fulfill those requirements, this paper presents a lossless
watermarking scheme for DICOM images. The proposed a fragile
scheme combines two reversible techniques based on difference
expansion for patient's data hiding and protecting the region of
interest (ROI) with tamper detection and recovery capability.
Patient's data are embedded into ROI, while recovery data are
embedded into region of non-interest (RONI). The experimental
results show that the original image can be exactly extracted from the
watermarked one in case of no tampering. In case of tampered ROI,
tampered area can be localized and recovered with a high quality
version of the original area.
Abstract: Reinforced Concrete (RC) structures strengthened
with fiber reinforced polymer (FRP) lack in thermal resistance under
elevated temperatures in the event of fire. This phenomenon led to
the lining of strengthened concrete with thin high performance
cementitious composites (THPCC) to protect the substrate against
elevated temperature. Elevated temperature effects on THPCC, based
on different cementitious materials have been studied in the past but
high-alumina cement (HAC)-based THPCC have not been well
characterized. This research study will focus on the THPCC based on
HAC replaced by 60%, 70%, 80% and 85% of ground granulated
blast furnace slag (GGBS). Samples were evaluated by the
measurement of their mechanical strength (28 & 56 days of curing)
after exposed to 400°C, 600°C and 28°C of room temperature for
comparison and corroborated by their microstructure study. Results
showed that among all mixtures, the mix containing only HAC
showed the highest compressive strength after exposed to 600°C as
compared to other mixtures. However, the tensile strength of THPCC
made of HAC and 60% GGBS content was comparable to the
THPCC with HAC only after exposed to 600°C. Field emission
scanning electron microscopy (FESEM) images of THPCC
accompanying Energy Dispersive X-ray (EDX) microanalysis
revealed that the microstructure deteriorated considerably after
exposure to elevated temperatures which led to the decrease in
mechanical strength.
Abstract: Traffic management in an urban area is highly facilitated by the knowledge of the traffic conditions in every street or highway involved in the vehicular mobility system. Aim of the paper is to propose a neuro-fuzzy approach able to compute the main parameters of a traffic system, i.e., car density, velocity and flow, by using the images collected by the web-cams located at the crossroads of the traffic network. The performances of this approach encourage its application when the traffic system is far from the saturation. A fuzzy model is also outlined to evaluate when it is suitable to use more accurate, even if more time consuming, algorithms for measuring traffic conditions near to saturation.
Abstract: Evaluation of educational portals is an important
subject area that needs more attention from researchers. A university
that has an educational portal which is difficult to use and interact by
teachers or students or management staff can reduce the position and
reputation of the university. Therefore, it is important to have the
ability to make an evaluation of the quality of e-services the
university provide to improve them over time.
The present study evaluates the usability of the Information
Technology Faculty portal at University of Benghazi. Two evaluation
methods were used: a questionnaire-based method and an online
automated tool-based method. The first method was used to measure
the portal's external attributes of usability (Information, Content and
Organization of the portal, Navigation, Links and Accessibility,
Aesthetic and Visual Appeal, Performance and Effectiveness and
educational purpose) from users' perspectives, while the second
method was used to measure the portal's internal attributes of
usability (number and size of HTML files, number and size of images,
load time, HTML check errors, browsers compatibility problems,
number of bad and broken links), which cannot be perceived by the
users. The study showed that some of the usability aspects have been
found at the acceptable level of performance and quality, and some
others have been found otherwise. In general, it was concluded that
the usability of IT faculty educational portal generally acceptable.
Recommendations and suggestions to improve the weakness and
quality of the portal usability are presented in this study.
Abstract: The paper presents the study of synthetic transmit
aperture method applying the Golay coded transmission for medical
ultrasound imaging. Longer coded excitation allows to increase the
total energy of the transmitted signal without increasing the peak
pressure. Signal-to-noise ratio and penetration depth are improved
maintaining high ultrasound image resolution.
In the work the 128-element linear transducer array with 0.3 mm
inter-element spacing excited by one cycle and the 8 and 16-bit
Golay coded sequences at nominal frequencies 4 MHz was used.
Single element transmission aperture was used to generate a spherical
wave covering the full image region and all the elements received the
echo signals. The comparison of 2D ultrasound images of the wire
phantom as well as of the tissue mimicking phantom is presented to
demonstrate the benefits of the coded transmission. The results were
obtained using the synthetic aperture algorithm with transmit and
receive signals correction based on a single element directivity
function.
Abstract: In this paper, a novel copyright protection scheme for digital images based on Visual Cryptography and Statistics is proposed. In our scheme, the theories and properties of sampling distribution of means and visual cryptography are employed to achieve the requirements of robustness and security. Our method does not need to alter the original image and can identify the ownership without resorting to the original image. Besides, our method allows multiple watermarks to be registered for a single host image without causing any damage to other hidden watermarks. Moreover, it is also possible for our scheme to cast a larger watermark into a smaller host image. Finally, experimental results will show the robustness of our scheme against several common attacks.
Abstract: Agriculture products are being more demanding in
market today. To increase its productivity, automation to produce
these products will be very helpful. The purpose of this work is to
measure and determine the ripeness and quality of watermelon. The
textures on watermelon skin will be captured using digital camera.
These images will be filtered using image processing technique. All
these information gathered will be trained using ANN to determine
the watermelon ripeness accuracy. Initial results showed that the best
model has produced percentage accuracy of 86.51%, when measured
at 32 hidden units with a balanced percentage rate of training dataset.
Abstract: In this research study, an intelligent detection system
to support medical diagnosis and detection of abnormal lesions by
processing endoscopic images is presented. The images used in this
study have been obtained using the M2A Swallowable Imaging
Capsule - a patented, video color-imaging disposable capsule.
Schemes have been developed to extract texture features from the
fuzzy texture spectra in the chromatic and achromatic domains for a
selected region of interest from each color component histogram of
endoscopic images. The implementation of an advanced fuzzy
inference neural network which combines fuzzy systems and
artificial neural networks and the concept of fusion of multiple
classifiers dedicated to specific feature parameters have been also
adopted in this paper. The achieved high detection accuracy of the
proposed system has provided thus an indication that such intelligent
schemes could be used as a supplementary diagnostic tool in
endoscopy.
Abstract: In this paper, we propose a supervised method for
color image classification based on a multilevel sigmoidal neural
network (MSNN) model. In this method, images are classified into
five categories, i.e., “Car", “Building", “Mountain", “Farm" and
“Coast". This classification is performed without any segmentation
processes. To verify the learning capabilities of the proposed method,
we compare our MSNN model with the traditional Sigmoidal Neural
Network (SNN) model. Results of comparison have shown that the
MSNN model performs better than the traditional SNN model in the
context of training run time and classification rate. Both color
moments and multi-level wavelets decomposition technique are used
to extract features from images. The proposed method has been
tested on a variety of real and synthetic images.
Abstract: This paper presents the application of a signal intensity independent registration criterion for non-rigid body registration of medical images. The criterion is defined as the weighted ratio image of two images. The ratio is computed on a voxel per voxel basis and weighting is performed by setting the ratios between signal and background voxels to a standard high value. The mean squared value of the weighted ratio is computed over the union of the signal areas of the two images and it is minimized using the Chebyshev polynomial approximation. The geometric transformation model adopted is a local cubic B-splines based model.
Abstract: This paper introduces a novel approach to estimate the
clique potentials of Gibbs Markov random field (GMRF) models
using the Support Vector Machines (SVM) algorithm and the Mean
Field (MF) theory. The proposed approach is based on modeling the
potential function associated with each clique shape of the GMRF
model as a Gaussian-shaped kernel. In turn, the energy function of
the GMRF will be in the form of a weighted sum of Gaussian
kernels. This formulation of the GMRF model urges the use of the
SVM with the Mean Field theory applied for its learning for
estimating the energy function. The approach has been tested on
synthetic texture images and is shown to provide satisfactory results
in retrieving the synthesizing parameters.
Abstract: This paper presents the results of enhancing images from a left and right stereo pair in order to increase the resolution of a 3D representation of a scene generated from that same pair. A new neural network structure known as a Self Delaying Dynamic Network (SDN) has been used to perform the enhancement. The advantage of SDNs over existing techniques such as bicubic interpolation is their ability to cope with motion and noise effects. SDNs are used to generate two high resolution images, one based on frames taken from the left view of the subject, and one based on the frames from the right. This new high resolution stereo pair is then processed by a disparity map generator. The disparity map generated is compared to two other disparity maps generated from the same scene. The first is a map generated from an original high resolution stereo pair and the second is a map generated using a stereo pair which has been enhanced using bicubic interpolation. The maps generated using the SDN enhanced pairs match more closely the target maps. The addition of extra noise into the input images is less problematic for the SDN system which is still able to out perform bicubic interpolation.
Abstract: This paper proposes new hybrid approaches for face
recognition. Gabor wavelets representation of face images is an
effective approach for both facial action recognition and face
identification. Perform dimensionality reduction and linear
discriminate analysis on the down sampled Gabor wavelet faces can
increase the discriminate ability. Nearest feature space is extended to
various similarity measures. In our experiments, proposed Gabor
wavelet faces combined with extended neural net feature space
classifier shows very good performance, which can achieve 93 %
maximum correct recognition rate on ORL data set without any preprocessing
step.