Accepted papers
- A memetic algorithm for branch coverage testing
Nassima Aleb and Samir Kechid, university of sciences and technolgies ,algeria
ABSTRACT
The use of metaheuristic search techniques for the automatic generation of test data has been a burgeoning interest for many researchers in recent years. Previous attempts to automate the test generation process have been limited, having been constrained by the size and complexity of software, and the basic fact that in general, test data generation is an undecidable problem. Metaheuristic search techniques offer much promise in regard to these problems. Metaheuristic search techniques are high-level frameworks, which utilize heuristics to seek solutions for combinatorial problems at a reasonable computational cost. In this paper, we present a new evolutionary approach for automated test data generation for structural testing. Our method presents several noteworthy features: It uses a newly defined program modeling allowing an easy program manipulation. Furthermore, instead of affecting a unique value for each input variable, we assign to each input an interval. This representation has the advantage of delimiting first the input value and to refine the interval progressively. In this manner, the search space is explored more efficiently. We use an original fitness function, which expresses truthfully the individual quality. Furthermore, we define a crossover operator allowing to effectively improving individuals.
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Automatic Thresholding Techniques for SAR Images
Moumena Al-Bayati and Ali El-Zaart, Beirut Arab University, Beirut, Lebanon.
ABSTRACT
Segmentation of Synthetic Aperture Radar (SAR) images have a great use in observing the global environment, and in analyzing the target detection and recognition . However, segmentation of (SAR) images is known as a very complex task, due to the existence of speckle noise. Therefore, in this paper we present a fast SAR images segmentation based on between class variance. Our choice for used (BCV) method, because it is one of the most effective thresholding techniques for most real world images with regard to uniformity and shape measures. Our experiments will be as a test to determine which technique is effective in thresholding (extraction) the oil spill for numerous SAR images, and in the future these thresholding techniques can be very useful in detection objects in other SAR images.
- MRI images Thresholding For Alzheimer Detection
Ali El-Zaart and Ali A. Ghosn, Beirut Arab University, Beirut, Lebanon.
ABSTRACT
More than 55 illnesses are associated with the
development of dementia and Alzheimer's disease (AD) is the most
prevalent form. Vascular dementia (VD) is the second most
common form of dementia. Current diagnosis of Alzheimer disease
(Alzheimer's disease) is made by clinical, neuropsychological, and
neuroimaging assessments.Magnetic resonance imaging (MRI) can
be considered the preferred neuroimaging examination for
Alzheimer disease because it allows for accurate measurement of
brain structures, especially the size of the hippocampus and related
regions. Image processing techniques has been used for processing
the (MRI) image. Image thresholding is an important concept, both
in the area of objects segmentation and recognition. It has been
widely used due to the simplicity of implementation and speed of
time execution. Many thresholding techniques have been proposed
in the literature. The aim of this paper is to provide formula and
their implementation to threshold images using Between-Class
Variance with a Mixture of Gamma Distributions. The algorithms
will be described by given their steps, and applications.
Experimental results are presented to show good results on
segmentation of (MRI) image.
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Edge Detection In Radar Images
Using Weibull Distribution
Ali El-Zaart and Wafaa Kamel Al-Jibory, Beirut Arab University, Beirut, Lebanon.
ABSTRACT
Radar images can reveal information about the
shape of the surface terrain as well as its physical and
biophysical properties. Radar images have long been used in
geological studies to map structural features that are revealed
by the shape of the landscape. Radar imagery also has
applications in vegetation and crop type mapping, landscape
ecology, hydrology, and volcanology. Image processing is using
for detecting for objects in radar images. Edge detection; which
is a method of determining the discontinuities in gray level
images; is a very important initial step in Image processing.
Many classical edge detectors have been developed over time.
Some of the well-known edge detection operators based on the
first derivative of the image are Roberts, Prewitt, Sobel which is
traditionally implemented by convolving the image with masks.
Also Gaussian distribution has been used to build masks for the
first and second derivative. However, this distribution has limit
to only symmetric shape. This paper will use to construct the
masks, the Weibull distribution which was more general than
Gaussian because it has symmetric and asymmetric shape. The
constructed masks are applied to images and we obtained good
results.
- Iris biometric recognition system employing
Canny operator
Binsu C. Kovoor, Supriya M.H. and K. Poulose Jacob, Cochin University of Science and Technology,kerala,India.
ABSTRACT
Biometrics has become important in
security applications. In comparison with many other
biometric features, iris recognition has very high
recognition accuracy because it depends on iris which
is located in a place that still stable through human life
and the probability to find two identical iris's is close to
zero. The identification system consists of several stages
including segmentation stage which is the most serious
and critical one. The current segmentation methods still
have limitation in localizing the iris due to circular
shape consideration of the pupil. In this research,
Daugman method is done to investigate the
segmentation techniques. Eyelid detection is another
step that has been included in this study as a part of
segmentation stage to localize the iris accurately and
remove unwanted area that might be included. The
obtained iris region is encoded using haar wavelets to
construct the iris code, which contains the most
discriminating feature in the iris pattern. Hamming
distance is used for comparison of iris templates in the
recognition stage. The dataset which is used for the
study is UBIRIS database. A comparative study of
different edge detector operator is performed. It is
observed that canny operator is best suited to extract
most of the edges to generate the iris code for
comparison. Recognition rate of 89% and rejection rate
of 95% is achieved.
