Abstract: When neck pain is associated with pain, numbness, or
weakness in the arm, shoulder, or hand, further investigation is
needed as these are symptoms indicating pressure on one or more
nerve roots. Evaluation necessitates a neurologic examination and
imaging using an MRI/CT scan. A degenerating disc loses some
thickness and is less flexible, causing inter-vertebrae space to narrow.
A radiologist diagnoses an Intervertebral Disc Degeneration (IDD) by
localizing every inter-vertebral disc and identifying the pathology in
a disc based on its geometry and appearance. Accurate localizing is
necessary to diagnose IDD pathology. But, the underlying image
signal is ambiguous: a disc’s intensity overlaps the spinal nerve
fibres. Even the structure changes from case to case, with possible
spinal column bending (scoliosis). The inter-vertebral disc
pathology’s quantitative assessment needs accurate localization of the
cervical region discs. In this work, the efficacy of multilevel set
segmentation model, to segment cervical discs is investigated. The
segmented images are annotated using a simple distance matrix.
Abstract: Image segmentation and edge detection is a fundamental section in image processing. In case of noisy images Edge Detection is very less effective if we use conventional Spatial Filters like Sobel, Prewitt, LOG, Laplacian etc. To overcome this problem we have proposed the use of Stochastic Gradient Mask instead of Spatial Filters for generating gradient images. The present study has shown that the resultant images obtained by applying Stochastic Gradient Masks appear to be much clearer and sharper as per Edge detection is considered.
Abstract: Due to rapid advancement of powerful image
processing software, digital images are easy to manipulate and
modify by ordinary people. Lots of digital images are edited for a
specific purpose and more difficult to distinguish form their original
ones. We propose a clustering method to detect a copy-move image
forgery of JPEG, BMP, TIFF, and PNG. The process starts with
reducing the color of the photos. Then, we use the clustering
technique to divide information of measuring data by Hausdorff
Distance. The result shows that the purposed methods is capable of
inspecting the image file and correctly identify the forgery.
Abstract: Mammography is widely used technique for breast cancer
screening. There are various other techniques for breast cancer screening
but mammography is the most reliable and effective technique. The
images obtained through mammography are of low contrast which
causes problem for the radiologists to interpret. Hence, a high quality
image is mandatory for the processing of the image for extracting any
kind of information from it. Many contrast enhancement algorithms have
been developed over the years. In the present work, an efficient
morphology based technique is proposed for contrast enhancement of
masses in mammographic images. The proposed method is based on
Multiscale Morphology and it takes into consideration the scale of the
structuring element. The proposed method is compared with other stateof-
the-art techniques. The experimental results show that the proposed
method is better both qualitatively and quantitatively than the other
standard contrast enhancement techniques.
Abstract: Image Processing is a structure of Signal Processing
for which the input is the image and the output is also an image or
parameter of the image. Image Resolution has been frequently
referred as an important aspect of an image. In Image Resolution
Enhancement, images are being processed in order to obtain more
enhanced resolution. To generate highly resoluted image for a low
resoluted input image with high PSNR value. Stationary Wavelet
Transform is used for Edge Detection and minimize the loss occurs
during Downsampling. Inverse Discrete Wavelet Transform is to get
highly resoluted image. Highly resoluted output is generated from the
Low resolution input with high quality. Noisy input will generate
output with low PSNR value. So Noisy resolution enhancement
technique has been used for adaptive sub-band thresholding is used.
Downsampling in each of the DWT subbands causes information loss
in the respective subbands. SWT is employed to minimize this loss.
Inverse Discrete wavelet transform (IDWT) is to convert the object
which is downsampled using DWT into a highly resoluted object.
Used Image denoising and resolution enhancement techniques will
generate image with high PSNR value. Our Proposed method will
improve Image Resolution and reached the optimized threshold.
Abstract: Fabric textures are very common in our daily life.
However, the representation of fabric textures has never been explored
from neuroscience view. Theoretical studies suggest that primary
visual cortex (V1) uses a sparse code to efficiently represent natural
images. However, how the simple cells in V1 encode the artificial
textures is still a mystery. So, here we will take fabric texture as
stimulus to study the response of independent component analysis that
is established to model the receptive field of simple cells in V1. We
choose 140 types of fabrics to get the classical fabric textures as
materials. Experiment results indicate that the receptive fields of
simple cells have obvious selectivity in orientation, frequency and
phase when drifting gratings are used to determine their tuning
properties. Additionally, the distribution of optimal orientation and
frequency shows that the patch size selected from each original fabric
image has a significant effect on the frequency selectivity.
Abstract: Edge is variation of brightness in an image. Edge
detection is useful in many application areas such as finding forests,
rivers from a satellite image, detecting broken bone in a medical
image etc. The paper discusses about finding edge of multiple aerial
images in parallel. The proposed work tested on 38 images 37
colored and one monochrome image. The time taken to process N
images in parallel is equivalent to time taken to process 1 image in
sequential. Message Passing Interface (MPI) and Open Computing
Language (OpenCL) is used to achieve task and pixel level
parallelism respectively.
Abstract: In this paper we propose a novel methodology for
extracting a road network and its nodes from satellite images of
Algeria country.
This developed technique is a progress of our previous research
works. It is founded on the information theory and the mathematical
morphology; the information theory and the mathematical
morphology are combined together to extract and link the road
segments to form a road network and its nodes.
We therefore have to define objects as sets of pixels and to study
the shape of these objects and the relations that exist between them.
In this approach, geometric and radiometric features of roads are
integrated by a cost function and a set of selected points of a crossing
road. Its performances were tested on satellite images of Algeria
country.
Abstract: With the growing of computer and network, digital
data can be spread to anywhere in the world quickly. In addition,
digital data can also be copied or tampered easily so that the security
issue becomes an important topic in the protection of digital data.
Digital watermark is a method to protect the ownership of digital data.
Embedding the watermark will influence the quality certainly. In this
paper, Vector Quantization (VQ) is used to embed the watermark into
the image to fulfill the goal of data hiding. This kind of watermarking
is invisible which means that the users will not conscious the existing
of embedded watermark even though the embedded image has tiny
difference compared to the original image. Meanwhile, VQ needs a lot
of computation burden so that we adopt a fast VQ encoding scheme by
partial distortion searching (PDS) and mean approximation scheme to
speed up the data hiding process.
The watermarks we hide to the image could be gray, bi-level and
color images. Texts are also can be regarded as watermark to embed.
In order to test the robustness of the system, we adopt Photoshop to
fulfill sharpen, cropping and altering to check if the extracted
watermark is still recognizable. Experimental results demonstrate that
the proposed system can resist the above three kinds of tampering in
general cases.
Abstract: Ibeno, Nigeria hosts the operational base of Mobil
Producing Nigeria Unlimited (MPNU), a subsidiary of ExxonMobil
and the current highest oil & condensate producer in Nigeria. Besides
MPNU, other oil companies operate onshore, on the continental shelf
and deep offshore of the Atlantic Ocean in Ibeno, Nigeria. This study
was designed to delineate oil polluted sites in Ibeno, Nigeria using
geophysical methods of electrical resistivity (ER) and ground
penetrating radar (GPR). Results obtained revealed that there have
been hydrocarbon contaminations of this environment by past crude
oil spills as observed from high resistivity values and GPR profiles
which clearly show the distribution, thickness and lateral extent of
hydrocarbon contamination as represented on the radargram reflector
tones. Contaminations were of varying degrees, ranging from slight
to high, indicating levels of substantial attenuation of crude oil
contamination over time. Moreover, the display of relatively lower
resistivities of locations outside the impacted areas compared to
resistivity values within the impacted areas and the 3-D Cartesian
images of oil contaminant plume depicted by red, light brown and
magenta for high, low and very low oil impacted areas, respectively
confirmed significant recent pollution of the study area with crude
oil.
Abstract: Image compression based on fractal coding is a lossy
compression method and normally used for gray level images range
and domain blocks in rectangular shape. Fractal based digital image
compression technique provide a large compression ratio and in this
paper, it is proposed using YUV colour space and the fractal theory
which is based on iterated transformation. Fractal geometry is mainly
applied in the current study towards colour image compression
coding. These colour images possesses correlations among the colour
components and hence high compression ratio can be achieved by
exploiting all these redundancies. The proposed method utilises the
self-similarity in the colour image as well as the cross-correlations
between them. Experimental results show that the greater
compression ratio can be achieved with large domain blocks but more
trade off in image quality is good to acceptable at less than 1 bit per
pixel.
Abstract: Non contact evaluation of the thickness of paint
coatings can be attempted by different destructive and nondestructive
methods such as cross-section microscopy, gravimetric mass
measurement, magnetic gauges, Eddy current, ultrasound or
terahertz. Infrared thermography is a nondestructive and non-invasive
method that can be envisaged as a useful tool to measure the surface
thickness variations by analyzing the temperature response. In this
paper, the thermal quadrupole method for two layered samples heated
up with a pulsed excitation is firstly used. By analyzing the thermal
responses as a function of thermal properties and thicknesses of both
layers, optimal parameters for the excitation source can be identified.
Simulations show that a pulsed excitation with duration of ten
milliseconds allows obtaining a substrate-independent thermal
response. Based on this result, an experimental setup consisting of a
near-infrared laser diode and an Infrared camera was next used to
evaluate the variation of paint coating thickness between 60 μm and
130 μm on two samples. Results show that the parameters extracted
for thermal images are correlated with the estimated thicknesses by
the Eddy current methods. The laser pulsed thermography is thus an
interesting alternative nondestructive method that can be moreover
used for nonconductive substrates.
Abstract: Image enhancement is a challenging issue in many applications. In the last two decades, there are various filters developed. This paper proposes a novel method which removes Gaussian noise from the gray scale images. The proposed technique is compared with Enhanced Fuzzy Peer Group Filter (EFPGF) for various noise levels. Experimental results proved that the proposed filter achieves better Peak-Signal-to-Noise-Ratio PSNR than the existing techniques. The proposed technique achieves 1.736dB gain in PSNR than the EFPGF technique.
Abstract: In order to protect data privacy, image with sensitive or
private information needs to be encrypted before being outsourced to
the cloud. However, this causes difficulties in image retrieval and data
management. A secure image retrieval method based on orthogonal
decomposition is proposed in the paper. The image is divided into two
different components, for which encryption and feature extraction are
executed separately. As a result, cloud server can extract features from
an encrypted image directly and compare them with the features of the
queried images, so that the user can thus obtain the image. Different
from other methods, the proposed method has no special requirements
to encryption algorithms. Experimental results prove that the proposed
method can achieve better security and better retrieval precision.
Abstract: Image segmentation plays an important role in
medical imaging applications. Therefore, accurate methods are
needed for the successful segmentation of medical images for
diagnosis and detection of various diseases. In this paper, we have
used maximum entropy to achieve image segmentation. Maximum
entropy has been calculated using Shannon, Renyi and Tsallis
entropies. This work has novelty based on the detection of skin lesion
caused by the bite of a parasite called Sand Fly causing the disease is
called Cutaneous Leishmaniasis.
Abstract: Bir El Djir is an important coastal township in Oran
department, located at 450 Km far away from Algiers on northwest of
Algeria. In this coastal area, the urban sprawl is one of the main
problems that reduce the limited highly fertile land. So, using the
remote sensing and GIS technologies have shown their great
capabilities to solve many earth resources issues.
The aim of this study is to produce land use and cover map for the
studied area at varied periods to monitor possible changes that may
occurred, particularly in the urban areas and subsequently predict
likely changes. For this, two spatial images SPOT and Landsat
satellites from 1987 and 2014 respectively were used to assess the
changes of urban expansion and encroachment during this period
with photo-interpretation and GIS approach.
The results revealed that the town of Bir El Djir has shown a
highest growth rate in the period 1987-2014 which is 1201.5 hectares
in terms of area. These expansions largely concern the new real estate
constructions falling within the social and promotional housing
programs launched by the government.
The most urban expansion is characterized by the new
construction in the form of spontaneous or peripheral precarious
habitat, but also unstructured slums settled especially in the
southeastern part of town.
Abstract: The detection of moving objects from a video image
sequences is very important for object tracking, activity recognition,
and behavior understanding in video surveillance.
The most used approach for moving objects detection / tracking is
background subtraction algorithms. Many approaches have been
suggested for background subtraction. But, these are illumination
change sensitive and the solutions proposed to bypass this problem
are time consuming.
In this paper, we propose a robust yet computationally efficient
background subtraction approach and, mainly, focus on the ability to
detect moving objects on dynamic scenes, for possible applications in
complex and restricted access areas monitoring, where moving and
motionless persons must be reliably detected. It consists of three
main phases, establishing illumination changes invariance,
background/foreground modeling and morphological analysis for
noise removing.
We handle illumination changes using Contrast Limited Histogram
Equalization (CLAHE), which limits the intensity of each pixel to
user determined maximum. Thus, it mitigates the degradation due to
scene illumination changes and improves the visibility of the video
signal. Initially, the background and foreground images are extracted
from the video sequence. Then, the background and foreground
images are separately enhanced by applying CLAHE.
In order to form multi-modal backgrounds we model each channel
of a pixel as a mixture of K Gaussians (K=5) using Gaussian Mixture
Model (GMM). Finally, we post process the resulting binary
foreground mask using morphological erosion and dilation
transformations to remove possible noise.
For experimental test, we used a standard dataset to challenge the
efficiency and accuracy of the proposed method on a diverse set of
dynamic scenes.
Abstract: Since the initial creation of the Barbie doll in 1959, it
became a symbol of US society. Likewise, the Licca-chan, a Japanese
doll created in 1967, also became a Japanese symbolic doll of Japanese
society. Prior to the introduction of Licca-chan, Barbie was already
marketed in Japan but their sales were dismal. Licca-chan (an actual
name: Kayama Licca) is a plastic doll with a variety of sizes ranging
from 21.0 cm to 29.0 cm which many Japanese girls dream of having.
For over 35 years, the manufacturer, Takara Co., Ltd. has sold over 48
million dolls and has produced doll houses, accessories, clothes, and
Licca-chan video games for the Nintendo DS. Many First-generation
Licca-chan consumers still are enamored with Licca-chan, and go to
Licca-chan House, in an amusement park with their daughters. These
people are called Licca-chan maniacs, as they enjoy touring the
Licca-chan’s factory in Tohoku or purchase various Licca-chan
accessories. After the successful launch of Licca-chan into the
Japanese market, a mixed-like doll from the US and Japan, a doll,
JeNny, was later sold in the same Japanese market by Takara Co., Ltd.
in 1982.
Comparison of these cultural iconic dolls, Barbie and Licca-chan,
are analyzed in this paper. In fact, these dolls have concepts of girls’
dreams. By using concepts of mythology of Jean Baudrillard, these
dolls can be represented idealized images of figures in the products for
consumers, but at the same time, consumers can see products with
different perspectives, which can cause controversy.
Abstract: Co metal supported on SiO2 and Al2O3 catalysts with
a metal loading varied from 30 of 70 wt.% were evaluated for
decomposition of methane to COx free hydrogen and carbon
nanomaterials. The catalytic runs were carried out from 550-800oC
under atmospheric pressure using fixed bed vertical flow reactor. The
fresh and spent catalysts were characterized by BET surface area
analyzer, XRD, SEM, TEM and TG analysis. The data showed that
50% Co/Al2O3 catalyst exhibited remarkable higher activity at 800oC
with respect to H2 production compared to rest of the catalysts.
However, the catalytic activity and durability was greatly declined at
higher temperature. The main reason for the catalytic inhibition of Co
containing SiO2 catalysts is the higher reduction temperature of
Co2SiO4. TEM images illustrate that the carbon materials with
various morphologies, carbon nanofibers (CNFs), helical-shaped
CNFs and branched CNFs depending on the catalyst composition and
reaction temperature were obtained.
Abstract: Content Based Image Retrieval (CBIR) coupled with
Case Based Reasoning (CBR) is a paradigm that is becoming
increasingly popular in the diagnosis and therapy planning of medical
ailments utilizing the digital content of medical images. This paper
presents a survey of some of the promising approaches used in the
detection of abnormalities in retina images as well in
mammographic screening and detection of regions of interest
in MRI scans of the brain. We also describe our proposed
algorithm to detect hard exudates in fundus images of the
retina of Diabetic Retinopathy patients.