Abstract: Web sites are rapidly becoming the preferred media
choice for our daily works such as information search, company
presentation, shopping, and so on. At the same time, we live in a
period where visual appearances play an increasingly important
role in our daily life. In spite of designers- effort to develop a web
site which be both user-friendly and attractive, it would be difficult
to ensure the outcome-s aesthetic quality, since the visual
appearance is a matter of an individual self perception and opinion.
In this study, it is attempted to develop an automatic system for
web pages aesthetic evaluation which are the building blocks of
web sites. Based on the image processing techniques and artificial
neural networks, the proposed method would be able to categorize
the input web page according to its visual appearance and aesthetic
quality. The employed features are multiscale/multidirectional
textural and perceptual color properties of the web pages, fed to
perceptron ANN which has been trained as the evaluator. The
method is tested using university web sites and the results
suggested that it would perform well in the web page aesthetic
evaluation tasks with around 90% correct categorization.
Abstract: This paper presents a comparative analysis of a new
unsupervised PCA-based technique for steel plates texture segmentation
towards defect detection. The proposed scheme called Variance
Based Component Analysis or VBCA employs PCA for feature
extraction, applies a feature reduction algorithm based on variance of
eigenpictures and classifies the pixels as defective and normal. While
the classic PCA uses a clusterer like Kmeans for pixel clustering,
VBCA employs thresholding and some post processing operations to
label pixels as defective and normal. The experimental results show
that proposed algorithm called VBCA is 12.46% more accurate and
78.85% faster than the classic PCA.
Abstract: Optical character recognition of cursive scripts
presents a number of challenging problems in both segmentation and
recognition processes in different languages, including Persian. In
order to overcome these problems, we use a newly developed Persian
word segmentation method and a recognition-based segmentation
technique to overcome its segmentation problems. This method is
robust as well as flexible. It also increases the system-s tolerances to
font variations. The implementation results of this method on a
comprehensive database show a high degree of accuracy which meets
the requirements for commercial use. Extended with a suitable pre
and post-processing, the method offers a simple and fast framework
to develop a full OCR system.
Abstract: As days go by, we hear more and more about HIV,
Ebola, Bird Flu and other dreadful viruses which were unknown a
few decades ago. In both detecting and fighting viral diseases
ordinary methods have come across some basic and important
difficulties. Vaccination is by a sense introduction of the virus to the
immune system before the occurrence of the real case infection. It is
very successful against some viruses (e.g. Poliomyelitis), while
totally ineffective against some others (e.g. HIV or Hepatitis-C). On
the other hand, Anti-virus drugs are mostly some tools to control and
not to cure a viral disease. This could be a good motivation to try
alternative treatments. In this study, some key features of possible
physical-based alternative treatments for viral diseases are presented.
Electrification of body parts or fluids (especially blood) with micro
electric signals with adjusted current or frequency is also studied. The
main approach of this study is to find a suitable energy field, with
appropriate parameters that are able to kill or deactivate viruses. This
would be a lengthy, multi-disciplinary research which needs the
contribution of virology, physics, and signal processing experts. It
should be mentioned that all the claims made by alternative cures
researchers must be tested carefully and are not advisable at the time
being.