Abstract: In this paper, we present a robust algorithm to recognize extracted text from grocery product images captured by mobile phone cameras. Recognition of such text is challenging since text in grocery product images varies in its size, orientation,
style, illumination, and can suffer from perspective distortion.
Pre-processing is performed to make the characters scale and
rotation invariant. Since text degradations can not be appropriately
defined using well-known geometric transformations such
as translation, rotation, affine transformation and shearing, we
use the whole character black pixels as our feature vector.
Classification is performed with minimum distance classifier
using the maximum likelihood criterion, which delivers very
promising Character Recognition Rate (CRR) of 89%. We
achieve considerably higher Word Recognition Rate (WRR) of
99% when using lower level linguistic knowledge about product
words during the recognition process.
Abstract: Real time image and video processing is a demand in
many computer vision applications, e.g. video surveillance, traffic
management and medical imaging. The processing of those video
applications requires high computational power. Thus, the optimal
solution is the collaboration of CPU and hardware accelerators. In
this paper, a Canny edge detection hardware accelerator is proposed.
Edge detection is one of the basic building blocks of video and image
processing applications. It is a common block in the pre-processing
phase of image and video processing pipeline. Our presented
approach targets offloading the Canny edge detection algorithm from
processing system (PS) to programmable logic (PL) taking the
advantage of High Level Synthesis (HLS) tool flow to accelerate the
implementation on Zynq platform. The resulting implementation
enables up to a 100x performance improvement through hardware
acceleration. The CPU utilization drops down and the frame rate
jumps to 60 fps of 1080p full HD input video stream.
Abstract: Red blood cells (RBC) are the most common types of
blood cells and are the most intensively studied in cell biology. The
lack of RBCs is a condition in which the amount of hemoglobin level
is lower than normal and is referred to as “anemia”. Abnormalities in
RBCs will affect the exchange of oxygen. This paper presents a
comparative study for various techniques for classifying the RBCs as
normal or abnormal (anemic) using WEKA. WEKA is an open
source consists of different machine learning algorithms for data
mining applications. The algorithms tested are Radial Basis Function
neural network, Support vector machine, and K-Nearest Neighbors
algorithm. Two sets of combined features were utilized for
classification of blood cells images. The first set, exclusively consist
of geometrical features, was used to identify whether the tested blood
cell has a spherical shape or non-spherical cells. While the second
set, consist mainly of textural features was used to recognize the
types of the spherical cells. We have provided an evaluation based on
applying these classification methods to our RBCs image dataset
which were obtained from Serdang Hospital - Malaysia, and
measuring the accuracy of test results. The best achieved
classification rates are 97%, 98%, and 79% for Support vector
machines, Radial Basis Function neural network, and K-Nearest
Neighbors algorithm respectively.
Abstract: Image spam is a kind of email spam where the spam
text is embedded with an image. It is a new spamming technique
being used by spammers to send their messages to bulk of internet
users. Spam email has become a big problem in the lives of internet
users, causing time consumption and economic losses. The main
objective of this paper is to detect the image spam by using histogram
properties of an image. Though there are many techniques to
automatically detect and avoid this problem, spammers employing
new tricks to bypass those techniques, as a result those techniques are
inefficient to detect the spam mails. In this paper we have proposed a
new method to detect the image spam. Here the image features are
extracted by using RGB histogram, HSV histogram and combination
of both RGB and HSV histogram. Based on the optimized image
feature set classification is done by using k- Nearest Neighbor(k-NN)
algorithm. Experimental result shows that our method has achieved
better accuracy. From the result it is known that combination of RGB
and HSV histogram with k-NN algorithm gives the best accuracy in
spam detection.
Abstract: Steganography is the art and science that hides the information in an appropriate cover carrier like image, text, audio and video media. In this work the authors propose a new image based steganographic method for hiding information within the complex bit planes of the image. After slicing into bit planes the cover image is analyzed to extract the most complex planes in decreasing order based on their bit plane complexity. The complexity function next determines the complex noisy blocks of the chosen bit plane and finally pixel mapping method (PMM) has been used to embed secret bits into those regions of the bit plane. The novel approach of using pixel mapping method (PMM) in bit plane domain adaptively embeds data on most complex regions of image, provides high embedding capacity, better imperceptibility and resistance to steganalysis attack.
Abstract: Environmental management implementation is
presently one of the ways of organization success and value
improvement. Increasing an organization motivation to
environmental measures introduction is caused primarily by the rising
pressure of the society that generates various incentives to endeavor
for the environmental performance improvement.
The aim of the paper is to identify and characterize the key
incentives and expectations leading organizations to the
environmental management implementation. The author focuses on
five businesses of different size and field, operating in the Czech
Republic. The qualitative approach and grounded theory procedure
are used in research.
The results point out that the significant incentives for
environmental management implementation represent primarily
demands of customers, the opportunity to declare the environmental
commitment and image improvement. The researched enterprises less
commonly expect the economical contribution, competitive
advantage increase or export rate improvement. The results show that
marketing contributions are primarily expected from the
environmental management implementation.
Abstract: In this study, epoxy composite specimens reinforced
with multi-walled carbon nanotube filler were fabricated using shear
mixer and ultra-sonication processor. The mechanical and thermal
properties of the fabricated specimens were measured and evaluated.
From the electron microscope images and the results from the
measurements of tensile strengths, the specimens having 0.6 wt%
nanotube content show better dispersion and higher strength than those
of the other specimens. The Young’s moduli of the specimens
increased as the contents of the nanotube filler in the matrix were
increased. The specimen having a 0.6 wt% nanotube filler content
showed higher thermal conductivity than that of the other specimens.
While, in the measurement of thermal expansion, specimens having
0.4 and 0.6 wt% filler contents showed a lower value of thermal
expansion than that of the other specimens. On the basis of the
measured and evaluated properties of the composites, we believe that
the simple and time-saving fabrication process used in this study was
sufficient to obtain improved properties of the specimens.
Abstract: Among modern airflow measurement methods,
Particle Image Velocimetry (PIV) and Particle Tracking Velocimetry
(PTV), as visualized and non-instructive measurement techniques, are
playing more important role. This paper conducts a comparative
experimental study for airflow measurement employing both
techniques with the same condition. Velocity vector fields, velocity
contour fields, voticity profiles and turbulence profiles are selected as
the comparison indexes. The results show that the performance of both
PIV and PTV techniques for airflow measurement is satisfied, but
some differences between the both techniques are existed, it suggests
that selecting the measurement technique should be based on a
comprehensive consideration.
Abstract: Floods play a key role in landform evolution of an
area. This process is likely to alter the topography of the earth’s
surface. The present study area, Kota Bharu is very prone to floods
extends from upstream of Kelantan River near Kemubu to the
downstream area near Kuala Besar. These flood events which occur
every year in the study area exhibit a strong bearing on river
morphological set-up. In the present study, three satellite imageries of
different time periods have been used to manifest the post-flood
landform changes. The pre-processing of the images such as subset,
geometric corrections and atmospheric corrections were carried-out
using ENVI 4.5 followed by the analysis processes. Twenty sets of
cross sections were plotted using software Erdas 9.2, ERDAS and
ArcGis 10 for the all three images. The results show a significant
change in the length of the cross section which suggest that the
geomorphological processes play a key role in carving and shaping
the river banks during the floods.
Abstract: The fuzzy composition of objects depicted in images
acquired through MR imaging or the use of bio-scanners has often
been a point of controversy for field experts attempting to effectively
delineate between the visualized objects. Modern approaches in
medical image segmentation tend to consider fuzziness as a
characteristic and inherent feature of the depicted object, instead of
an undesirable trait. In this paper, a novel technique for efficient
image retrieval in the context of images in which segmented objects
are either crisp or fuzzily bounded is presented. Moreover, the
proposed method is applied in the case of multiple, even conflicting,
segmentations from field experts. Experimental results demonstrate
the efficiency of the suggested method in retrieving similar objects
from the aforementioned categories while taking into account the
fuzzy nature of the depicted data.
Abstract: Images are important source of information used as
evidence during any investigation process. Their clarity and accuracy
is essential and of the utmost importance for any investigation.
Images are vulnerable to losing blocks and having noise added to
them either after alteration or when the image was taken initially,
therefore, having a high performance image processing system and it
is implementation is very important in a forensic point of view. This
paper focuses on improving the quality of the forensic images.
For different reasons packets that store data can be affected,
harmed or even lost because of noise. For example, sending the
image through a wireless channel can cause loss of bits. These types
of errors might give difficulties generally for the visual display
quality of the forensic images.
Two of the images problems: noise and losing blocks are covered.
However, information which gets transmitted through any way of
communication may suffer alteration from its original state or even
lose important data due to the channel noise. Therefore, a developed
system is introduced to improve the quality and clarity of the forensic
images.
Abstract: Tumor is an uncontrolled growth of tissues in any part
of the body. Tumors are of different types and they have different
characteristics and treatments. Brain tumor is inherently serious and
life-threatening because of its character in the limited space of the
intracranial cavity (space formed inside the skull). Locating the tumor
within MR (magnetic resonance) image of brain is integral part of the
treatment of brain tumor. This segmentation task requires
classification of each voxel as either tumor or non-tumor, based on
the description of the voxel under consideration. Many studies are
going on in the medical field using Markov Random Fields (MRF) in
segmentation of MR images. Even though the segmentation process
is better, computing the probability and estimation of parameters is
difficult. In order to overcome the aforementioned issues, Conditional
Random Field (CRF) is used in this paper for segmentation, along
with the modified artificial bee colony optimization and modified
fuzzy possibility c-means (MFPCM) algorithm. This work is mainly
focused to reduce the computational complexities, which are found in
existing methods and aimed at getting higher accuracy. The
efficiency of this work is evaluated using the parameters such as
region non-uniformity, correlation and computation time. The
experimental results are compared with the existing methods such as
MRF with improved Genetic Algorithm (GA) and MRF-Artificial
Bee Colony (MRF-ABC) algorithm.
Abstract: Oases are complex and fragile agro-ecosystems. They
have always existed in environments characterized by an arid climate,
scarcity of rainfall, high temperatures and high evaporation. These
palms have grown up despite the severity of the physical
characteristics thanks to the water's existence and irrigation practice.
The oases are generally spread along non-perennial rivers (wadis),
shallow water table or deep artesian groundwater. However, the
sustainability of oasis system is threatened by water scarcity and
declining of water table levels particularly in arid areas. Located in
the southern east area of Morocco, Tafilalet plain encompasses one of
the largest palm groves in the kingdom. In recent years, this area has
become increasingly threatened by water shortage and has seen a
sharp deterioration under the effect of several combined
anthropogenic and climatic factors. The Bayoud disease, successive
years of drought, Hassan Addakhil dam construction etc are all
factors that have affected both water and phoenicicole heritage of the
area. The objective of this study is to understand the interaction
between qualitative and quantitative degradation of groundwater
resources, and the palm grove dynamics, while reviewing the
assumption that groundwater resources contribute in a direct way to
the conservation of this oasis agroecosystem. A historical analysis
tracing both the oasis dynamics and the groundwater evolution has
been established. Data were collected from satellite images, surveys
with different actors (farmers, Regional Office for Agricultural
Development, Basin agency...). They were complemented by a
synthesis of numerous technical reports in the area. The results
showed that within 40 years, the thickness of the groundwater table
has dropped in 50 %. Along with this, there has been a downsizing of
date palm by 50 %. Areas with higher groundwater level were the
least affected by the downsizing. So we can say that the shallow
groundwater contribute significantly and directly to the water supply
of date palm through its root system, and largely ensures the oasis
ecosystem sustainability.
Abstract: Augmented Reality is a technology that involves the
overlay of virtual content, which is context or environment sensitive,
on images of the physical world in real time. This paper presents the
development of a catalog system that facilitates and allows the
creation, publishing, management and exploitation of augmented
multimedia contents and Augmented Reality applications, creating an
own space for anyone that wants to provide information to real
objects in order to edit and share it then online with others. These
spaces would be built for different domains without the initial need of
expert users. Its operation focuses on the context of Web 2.0 or
Social Web, with its various applications, developing contents to
enrich the real context in which human beings act permitting the
evolution of catalog’s contents in an emerging way.
Abstract: Sports games conducted as a group are a form of
therapeutic exercise for aged people with decreased strength and for
people suffering from permanent damage of stroke and other
conditions. However, it is difficult for patients with different athletic
abilities to play a game on an equal footing. This study specifically
examines a computer video game designed for therapeutic exercise,
and a game system with support given depending on athletic ability.
Thereby, anyone playing the game can participate equally. This
video-game, to be specific, is a popular variant of balloon volleyball,
in which players hit a balloon by hand before it falls to the floor. In this
game system, each player plays the game watching a monitor on which
the system displays tailor-made video-game images adjusted to the
person’s athletic ability, providing players with player-adaptive assist
support. We have developed a multiplayer game system with an image
generation technique for the tailor-made video-game and conducted
tests to evaluate it.
Abstract: Mammography has been one of the most reliable
methods for early detection of breast cancer. There are different
lesions which are breast cancer characteristic such as
microcalcifications, masses, architectural distortions and bilateral
asymmetry. One of the major challenges of analysing digital
mammogram is how to extract efficient features from it for accurate
cancer classification. In this paper we proposed a hybrid feature
extraction method to detect and classify all four signs of breast
cancer. The proposed method is based on multiscale surrounding
region dependence method, Gabor filters, multi fractal analysis,
directional and morphological analysis. The extracted features are
input to self adaptive resource allocation network (SRAN) classifier
for classification. The validity of our approach is extensively
demonstrated using the two benchmark data sets Mammographic
Image Analysis Society (MIAS) and Digital Database for Screening
Mammograph (DDSM) and the results have been proved to be
progressive.
Abstract: Skin detection is an important task for computer
vision systems. A good method of skin detection means a good and
successful result of the system.
The colour is a good descriptor for image segmentation and
classification; it allows detecting skin colour in the images. The
lighting changes and the objects that have a colour similar than skin
colour make the operation of skin detection difficult.
In this paper, we proposed a method using the YCbCr colour space
for skin detection and lighting effects elimination, then we use the
information of texture to eliminate the false regions detected by the
YCbCr skin model.
Abstract: Key frame extraction methods select the most
representative frames of a video, which can be used in different areas
of video processing such as video retrieval, video summary, and video
indexing. In this paper we present a novel approach for extracting key
frames from video sequences. The frame is characterized uniquely by
his contours which are represented by the dominant blocks. These
dominant blocks are located on the contours and its near textures.
When the video frames have a noticeable changement, its dominant
blocks changed, then we can extracte a key frame. The dominant
blocks of every frame is computed, and then feature vectors are
extracted from the dominant blocks image of each frame and arranged
in a feature matrix. Singular Value Decomposition is used to calculate
sliding windows ranks of those matrices. Finally the computed ranks
are traced and then we are able to extract key frames of a video.
Experimental results show that the proposed approach is robust
against a large range of digital effects used during shot transition.
Abstract: Domestic goats (Capra hircus) are extremely diverse
species and principal animal genetic resource of the developing
world. These facilitate a persistent supply of meat, milk, fibre, and
skin and are considered as important revenue generators in small
pastoral environments. This study aimed to fingerprint β-LG gene at
PCR-RFLP level in native Saudi goat breeds (Ardi, Habsi and Harri)
in an attempt to have a preliminary image of β-LG genotypic patterns
in Saudi breeds as compared to other foreign breeds such as Indian
and Egyptian. Also, the Phylogenetic analysis was done to investigate
evolutionary trends and similarities among the caprine β-LG gene
with that of the other domestic specie, viz. cow, buffalo and sheep.
Blood samples were collected from 300 animals (100 for each breed)
and genomic DNA was extracted. A fragment of the β-LG gene
(427bp) was amplified using specific primers. Subsequent digestion
with Sac II restriction endonuclease revealed two alleles (A and B)
and three different banding patterns or genotypes i.e. AA, AB and
BB. The statistical analysis showed a general trend that β-LG AA
genotype had higher milk yield than β-LG AB and β-LG BB
genotypes. Nucleotide sequencing of the selected β-LG fragments
was done and submitted to GenBank NCBI (Accession No.
KJ544248, KJ588275, KJ588276, KJ783455, KJ783456 and
KJ874959). Phylogenetic analysis on the basis of nucleotide
sequences of native Saudi goats indicated evolutional similarity with
the GenBank reference sequences of goat, Bubalus bubalis and Bos
taurus. However, the origin of sheep which is the most closely
related from the evolutionary point of view, was located some
distance away.
Abstract: The Quad Tree Decomposition based performance
analysis of compressed image data communication for lossy and
lossless through wireless sensor network is presented. Images have
considerably higher storage requirement than text. While transmitting
a multimedia content there is chance of the packets being dropped
due to noise and interference. At the receiver end the packets that
carry valuable information might be damaged or lost due to noise,
interference and congestion. In order to avoid the valuable
information from being dropped various retransmission schemes have
been proposed. In this proposed scheme QTD is used. QTD is an
image segmentation method that divides the image into homogeneous
areas. In this proposed scheme involves analysis of parameters such
as compression ratio, peak signal to noise ratio, mean square error,
bits per pixel in compressed image and analysis of difficulties during
data packet communication in Wireless Sensor Networks. By
considering the above, this paper is to use the QTD to improve the
compression ratio as well as visual quality and the algorithm in
MATLAB 7.1 and NS2 Simulator software tool.