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: Quantitative analyses of whisker movements provide a
means to study functional recovery and regeneration of mouse facial
nerve after an injury. However, accurate tracking of the mouse whisker
movement is challenging. Most methods for whisker tracking require
manual intervention, e.g. fixing the head of the mouse during a study.
Here we describe a semi-automated image processing method, which
is applied to high-speed video recordings of free-moving mice to track
the whisker movements. We first track the head movement of a mouse
by delineating the lower head contour frame-by-frame that allows for
detection of the location and orientation of the head. Then, a region of
interest is identified for each frame; the subsequent application of a
mask and the Hough transform detects the selected whiskers on each
side of the head. Our approach is used to examine the functional
recovery of damaged facial nerves in mice over a course of 21 days.
Abstract: In this paper, a model is proposed to determine the life
distribution parameters of the useful life region for the PV system
utilizing a combination of non-parametric and linear regression
analysis for the failure data of these systems. Results showed that this
method is dependable for analyzing failure time data for such reliable
systems when the data is scarce.
Abstract: This study investigates the use of a time-series of
MODIS NDVI data to identify agricultural land cover change on an
annual time step (2007 - 2012) and characterize the trend. Following
an ISODATA classification of the MODIS imagery to selectively
mask areas not agriculture or semi-natural, NDVI signatures were
created to identify areas cereals and vineyards with the aid of
ancillary, pictometry and field sample data for 2010. The NDVI
signature curve and training samples were used to create a decision
tree model in WEKA 3.6.9 using decision tree classifier (J48)
algorithm; Model 1 including ISODATA classification and Model 2
not. These two models were then used to classify all data for the
study area for 2010, producing land cover maps with classification
accuracies of 77% and 80% for Model 1 and 2 respectively. Model 2
was subsequently used to create land cover classification and change
detection maps for all other years. Subtle changes and areas of
consistency (unchanged) were observed in the agricultural classes
and crop practices. Over the years as predicted by the land cover
classification. Forty one percent of the catchment comprised of
cereals with 35% possibly following a crop rotation system.
Vineyards largely remained constant with only one percent
conversion to vineyard from other land cover classes.
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: This paper presents two techniques, local feature
extraction using image spectrum and low frequency spectrum
modelling using GMM to capture the underlying statistical
information to improve the performance of face recognition
system. Local spectrum features are extracted using overlap sub
block window that are mapped on the face image. For each of this
block, spatial domain is transformed to frequency domain using
DFT. A low frequency coefficient is preserved by discarding high
frequency coefficients by applying rectangular mask on the
spectrum of the facial image. Low frequency information is non-
Gaussian in the feature space and by using combination of several
Gaussian functions that has different statistical properties, the best
feature representation can be modelled using probability density
function. The recognition process is performed using maximum
likelihood value computed using pre-calculated GMM components.
The method is tested using FERET datasets and is able to achieved
92% recognition rates.
Abstract: Tsunami early detection and warning systems have proved to be of ultimate importance, especially after the destructive tsunami that hit Japan in March 2012. Such systems are crucial to inform the authorities of any risk of a tsunami and of the degree of its danger in order to make the right decision and notify the public of the actions they need to take to save their lives. The purpose of this research is to enhance existing tsunami detection and warning systems. We first propose an automated and miniaturized model of an early tsunami detection and warning system. The model for the operation of a tsunami warning system is simulated using the data acquisition toolbox of Matlab and measurements acquired from specified internet pages due to the lack of the required real-life sensors, both seismic and hydrologic, and building a graphical user interface for the system. In the second phase of this work, we implement various satellite image filtering schemes to enhance the acquired synthetic aperture radar images of the tsunami affected region that are masked by speckle noise. This enables us to conduct a post-tsunami damage extent study and calculate the percentage damage. We conclude by proposing improvements to the existing telecommunication infrastructure of existing warning tsunami systems using a migration to IP-based networks and fiber optics links.
Abstract: This paper is aimed to investigate farmers’ level of awareness and behavior of chemical pesticide uses, by using a case study of Suan Luang Sub- District Municipality, Ampawa, Samut Songkram Province. Questionnaire was employed in this study with the farmers from 46 households to explore their level of awareness in chemical pesticide uses, while interview and observation were adopted in exploring their behavior of chemical pesticide uses. The findings reflected the farmers’ high level of awareness in chemical pesticide uses in the hazardous effects of the chemical to human and environmental health, while their behavior of chemical pesticide uses explained their awareness paid to the right way of using pesticides, for instance reading the direction on the label, keeping children and animals away from the area of pesticide mixing, covering body with clothes and wearing hat and mask, no smoking, eating or drinking during pesticide spray or standing in windward direction.
Abstract: In this paper, design and fabrication of an actuated parallel-plate mirror based on a 3D-printer is described. The mirror and electrode layers are fabricated separately and assembled thereafter. The alignment is performed by dowel pin-hole pairs fabricated on the respective layers. The electrodes are formed on the surface of the electrode layer by Au ion sputtering using a suitable mask, which is also fabricated by a 3D-printer.For grounding the mirror layer, except the contact area with the electrode paths, all the surface is Au ion sputtered. 3D-printers are widely used for creating 3D models or mock-ups. The authors have recently proposed that these models can perform electromechanical functions such as actuators by suitably masking them followed by metallization process. Since the smallest possible fabrication size is in the order of sub-millimeters, these electromechanical devices are named by the authors as SMEMS (Sub-Milli Electro-Mechanical Systems) devices. The proposed mirror described in this paper which consists of parallel-plate electrostatic actuators is also one type of SMEMS devices. In addition, SMEMS is totally environment-clean compared to MEMS (Micro Electro-Mechanical Systems) fabrication processes because any hazardous chemicals or gases are utilized.
Abstract: Corn is cultivated in most countries because of high consumption, quality, and food value. This study evaluated needed energy for cutting corn stems in different levels of cutting height and moisture content. For this reason, test device was fabricated and then calibrated. The device works on the principle of conservation of energy. The results were analyzed using split plot design and SAS software. The results showed that effect of height and moisture content and their interaction effect on cutting energy are significant (P
Abstract: This paper introduces an image denoising algorithm based on generalized Srivastava-Owa fractional differential operator for removing Gaussian noise in digital images. The structures of nxn fractional masks are constructed by this algorithm. Experiments show that, the capability of the denoising algorithm by fractional differential-based approach appears efficient to smooth the Gaussian noisy images for different noisy levels. The denoising performance is measured by using peak signal to noise ratio (PSNR) for the denoising images. The results showed an improved performance (higher PSNR values) when compared with standard Gaussian smoothing filter.
Abstract: In this paper, we present a non-blind technique of
adding the watermark to the Fourier spectral components of audio
signal in a way such that the modified amplitude does not exceed the
maximum amplitude spread (MAS). This MAS is due to individual
Discrete fourier transform (DFT) coefficients in that particular frame,
which is derived from the Energy Spreading function given by
Schroeder. Using this technique one can store double the information
within a given frame length i.e. overriding the watermark on the
host of equal length with least perceptual distortion. The watermark
is uniformly floating on the DFT components of original signal.
This helps in detecting any intentional manipulations done on the
watermarked audio. Also, the scheme is found robust to various signal
processing attacks like presence of multiple watermarks, Additive
white gaussian noise (AWGN) and mp3 compression.
Abstract: Image Edge Detection is one of the most important
parts of image processing. In this paper, by fuzzy technique, a new
method is used to improve digital image edge detection. In this
method, a 3x3 mask is employed to process each pixel by means of
vicinity. Each pixel is considered a fuzzy input and by examining
fuzzy rules in its vicinity, the edge pixel is specified and by utilizing
calculation algorithms in image processing, edges are displayed more
clearly. This method shows significant improvement compared to
different edge detection methods (e.g. Sobel, Canny).
Abstract: In this paper we introduced new wavelet based algorithm for speckle reduction of synthetic aperture radar images, which uses combination of undecimated wavelet transformation, wiener filter (which is an adaptive filter) and mean filter. Further more instead of using existing thresholding techniques such as sure shrinkage, Bayesian shrinkage, universal thresholding, normal thresholding, visu thresholding, soft and hard thresholding, we use brute force thresholding, which iteratively run the whole algorithm for each possible candidate value of threshold and saves each result in array and finally selects the value for threshold that gives best possible results. That is why it is slow as compared to existing thresholding techniques but gives best results under the given algorithm for speckle reduction.
Abstract: Super-resolution is nowadays used for a high-resolution
image produced from several low-resolution noisy frames. In
this work, we consider the problem of high-quality interpolation of a
single noise-free image. Such images may come from different sources,
i.e., they may be frames of videos, individual pictures, etc. On
the other hand, in the encoder we apply a downsampling via
bidimen-sional interpolation of each frame, and in the decoder we
apply a upsampling by which we restore the original size of the
image. If the compression ratio is very high, then we use a
convolutive mask that restores the edges, eliminating the blur.
Finally, both, the encoder and the complete decoder are implemented
on General-Purpose computation on Graphics Processing Units
(GPGPU) cards. In fact, the mentioned mask is coded inside texture
memory of a GPGPU.
Abstract: In the course of the present work, plain (nonencapsulated)
and microencapsulated polyphenols were produced
using olive mill wastewater (OMW) as raw material, in order to be
used for enrichment of yogurt and dairy products. The OMW was
first clarified by using membrane technology and subsequently the
contained poly-phenols were isolated by adsorption-desorption
technique using selective macro-porous resins and finally recovered
in dry form after been processed by RO membrane technique
followed by freeze drying. Moreover, the polyphenols were
encapsulated in modified starch by freeze drying in order to mask the
color and bitterness effect and improve their functionality. The two
products were used successfully as additives in yogurt preparations
and the produced products were acceptable by the consumers and
presented with certain advantage to the plain yogurt. For the herein
proposed production scheme a patent application was already
submitted.
Abstract: The aim of this study was to test whether the Attention
Networks Test (ANT) showed temporal decrements in performance.
Vigilance tasks typically show such decrements, which may reflect
impairments in executive control resulting from cognitive fatigue.
The ANT assesses executive control, as well as alerting and
orienting. Thus, it was hypothesized that ANT executive control
would deteriorate over time. Manipulations including task condition
(trial composition) and masking were included in the experimental
design in an attempt to increase performance decrements. However,
results showed that there is no temporal decrement on the ANT. The
roles of task demands, cognitive fatigue and participant motivation in
producing this result are discussed. The ANT may not be an effective
tool for investigating temporal decrement in attention.
Abstract: In this study, a novel approach of image embedding is introduced. The proposed method consists of three main steps. First, the edge of the image is detected using Sobel mask filters. Second, the least significant bit LSB of each pixel is used. Finally, a gray level connectivity is applied using a fuzzy approach and the ASCII code is used for information hiding. The prior bit of the LSB represents the edged image after gray level connectivity, and the remaining six bits represent the original image with very little difference in contrast. The proposed method embeds three images in one image and includes, as a special case of data embedding, information hiding, identifying and authenticating text embedded within the digital images. Image embedding method is considered to be one of the good compression methods, in terms of reserving memory space. Moreover, information hiding within digital image can be used for security information transfer. The creation and extraction of three embedded images, and hiding text information is discussed and illustrated, in the following sections.
Abstract: Waiting times and queues are a daily problem for theme parks. Fast lines or priority queues appear as a solution for a specific segment of customers, that is, tourists who are willing to pay to avoid waiting. This paper analyzes the fast line system and explores the factors that affect the decision to purchase a fast line pass. A greater understanding of these factors may help companies to design appropriate products and services. This conceptual paper was based on a literature review in marketing and consumer behavior. Additional research was identified in related disciplines such as leisure studies, psychology, and sociology. A conceptual framework of the factors influencing the decision to purchase a fast line pass is presented.
Abstract: This paper explores the importance of privacy in a
contemporary online world. Crucial to the discussion is the idea of
the Lacanian postmodern fragmented self and the problem of how to
ensure that we have room to fully explore various aspects of our
personalities in an environment which is–or at least feels--safe and
free from observation by others. The paper begins with an
exploration of the idea of the self with particular regard to the ways
in which contemporary life and technology seems to have multiplied
the various faces or masks which we present in different contexts. A
brief history of privacy and surveillance follows. Finally, the paper
ends with an affirmation of the importance of private space as an
essential component of our spiritual and emotional well-being in
today-s wired world.