Abstract: In remote sensing, shadow causes problems in many
applications such as change detection and classification. It is caused
by objects which are elevated, thus can directly affect the accuracy of
information. For these reasons, it is very important to detect shadows
particularly in urban high spatial resolution imagery which created a
significant problem. This paper focuses on automatic shadow
detection based on a new spectral index for multispectral imagery
known as Shadow Detection Index (SDI). The new spectral index
was tested on different areas of WorldView-2 images and the results
demonstrated that the new spectral index has a massive potential to
extract shadows with accuracy of 94% effectively and automatically.
Furthermore, the new shadow detection index improved road
extraction from 82% to 93%.
Abstract: In the past, the most comprehensively adopted light
source was incandescent light bulbs, but with the appearance of LED
light sources, traditional light sources have been gradually replaced by
LEDs because of its numerous superior characteristics. However,
many of the standards do not apply to LEDs as the two light sources
are characterized differently. This also intensifies the significance of
studies on LEDs. As a Kansei design study investigating the visual
glare produced by traffic arrows implemented with LEDs, this study
conducted a semantic analysis on the styles of traffic arrows used in
domestic and international occasions. The results will be able to
reduce drivers’ misrecognition that results in the unsuccessful arrival
at the destination, or in traffic accidents. This study started with a
literature review and surveyed the status quo before conducting
experiments that were divided in two parts. The first part involved a
screening experiment of arrow samples, where cluster analysis was
conducted to choose five representative samples of LED displays. The
second part was a semantic experiment on the display of arrows using
LEDs, where the five representative samples and the selected ten
adjectives were incorporated. Analyzing the results with
Quantification Theory Type I, it was found that among the
composition of arrows, fletching was the most significant factor that
influenced the adjectives. In contrast, a “no fletching” design was
more abstract and vague. It lacked the ability to convey the intended
message and might bear psychological negative connotation including
“dangerous,” “forbidden,” and “unreliable.” The arrow design
consisting of “> shaped fletching” was found to be more concrete and
definite, showing positive connotation including “safe,” “cautious,”
and “reliable.” When a stimulus was placed at a farther distance, the
glare could be significantly reduced; moreover, the visual evaluation
scores would be higher. On the contrary, if the fletching and the shaft
had a similar proportion, looking at the stimuli caused higher
evaluation at a closer distance. The above results will be able to be
applied to the design of traffic arrows by conveying information
definitely and rapidly. In addition, drivers’ safety could be enhanced
by understanding the cause of glare and improving visual
recognizability.
Abstract: In this increasingly visual world, how can we best decipher and understand the many ways that our everyday lives are organized around looking practices and the many images we encounter each day? Indeed, how we interact with and interpret visual images is a basic component of human life. Today, however, we are living in one of the most artificial visual and image-saturated cultures in human history, which makes understanding the complex construction and multiple social functions of visual imagery more important than ever before. Themes regarding our experience of a visually pervasive mediated culture, here, termed visual spectacle.
Abstract: An analysis of word semantics focusing on the invariance of advanced imagery in several pressing problems. Interest in the language of imagery is caused by the introduction, in the linguistics sphere, of a new paradigm, the center of which is the personality of the speaker (the subject of the language). Particularly noteworthy is the question of the place of the image when discussing the lexical, phraseological values and the relationship of imagery and metaphors. In part, the formation of a metaphor, as an interaction between two intellective entities, occurs at a cognitive level, and it is the category of the image, having cognitive roots, which aides in the correct interpretation of the results of this process on the lexical-semantic level.
Abstract: Structural interpretation of aeromagnetic data and Landsat imagery over the Middle Benue Trough was carried out to determine the depth to basement, delineate the basement morphology and relief, and the structural features within the basin. The aeromagnetic and Landsat data were subjected to various image and data enhancement and transformation routines. Results of the study revealed lineaments with trend directions in the N-S, NE-SW, NWSE and E-W directions, with the NE-SW trends been dominant. The depths to basement within the trough were established to be at 1.8, 0.3 and 0.8km, as shown from the spectral analysis plot. The Source Parameter Imaging (SPI) plot generated showed the centralsouth/ eastern portion of the study area as being deeper in contrast to the western-south-west portion. The basement morphology of the trough was interpreted as having parallel sets of micro-basins which could be considered as grabens and horsts in agreement with the general features interpreted by early workers.
Abstract: Functional near infrared spectroscopy (fNIRS) is a
practical non-invasive optical technique to detect characteristic of
hemoglobin density dynamics response during functional activation of
the cerebral cortex. In this paper, fNIRS measurements were made in
the area of motor cortex from C4 position according to international
10-20 system. Three subjects, aged 23 - 30 years, were participated in
the experiment.
The aim of this paper was to evaluate the effects of different motor
activation tasks of the hemoglobin density dynamics of fNIRS signal.
The chaotic concept based on deterministic dynamics is an important
feature in biological signal analysis. This paper employs the chaotic
properties which is a novel method of nonlinear analysis, to analyze
and to quantify the chaotic property in the time series of the
hemoglobin dynamics of the various motor imagery tasks of fNIRS
signal. Usually, hemoglobin density in the human brain cortex is
found to change slowly in time. An inevitable noise caused by various
factors is to be included in a signal. So, principle component analysis
method (PCA) is utilized to remove high frequency component. The
phase pace is reconstructed and evaluated the Lyapunov spectrum, and
Lyapunov dimensions. From the experimental results, it can be
conclude that the signals measured by fNIRS are chaotic.
Abstract: In this paper, a novel road extraction method using Stationary Wavelet Transform is proposed. To detect road features from color aerial satellite imagery, Mexican hat Wavelet filters are used by applying the Stationary Wavelet Transform in a multiresolution, multi-scale, sense and forming the products of Wavelet coefficients at a different scales to locate and identify road features at a few scales. In addition, the shifting of road features locations is considered through multiple scales for robust road extraction in the asymmetry road feature profiles. From the experimental results, the proposed method leads to a useful technique to form the basis of road feature extraction. Also, the method is general and can be applied to other features in imagery.
Abstract: In this paper we investigate the watermarking authentication when applied to medical imagery field. We first give an overview of watermarking technology by paying attention to fragile watermarking since it is the usual scheme for authentication.We then analyze the requirements for image authentication and integrity in medical imagery, and we show finally that invertible schemes are the best suited for this particular field. A well known authentication method is studied. This technique is then adapted here for interleaving patient information and message authentication code with medical images in a reversible manner, that is using lossless compression. The resulting scheme enables on a side the exact recovery of the original image that can be unambiguously authenticated, and on the other side, the patient information to be saved or transmitted in a confidential way. To ensure greater security the patient information is encrypted before being embedded into images.
Abstract: The noteworthy point in the advancement of Brain Machine Interface (BMI) research is the ability to accurately extract features of the brain signals and to classify them into targeted control action with the easiest procedures since the expected beneficiaries are of disabled. In this paper, a new feature extraction method using the combination of adaptive band pass filters and adaptive autoregressive (AAR) modelling is proposed and applied to the classification of right and left motor imagery signals extracted from the brain. The introduction of the adaptive bandpass filter improves the characterization process of the autocorrelation functions of the AAR models, as it enhances and strengthens the EEG signal, which is noisy and stochastic in nature. The experimental results on the Graz BCI data set have shown that by implementing the proposed feature extraction method, a LDA and SVM classifier outperforms other AAR approaches of the BCI 2003 competition in terms of the mutual information, the competition criterion, or misclassification rate.
Abstract: Addis Ababa is a seat of African Union (AU), United
Nations Economic Commission for Africa (UN-ECA) and hundreds of
embassies and consular representatives. Addis Ababa is one of the
highest capitals in the world with an average 2400 meters above sea
level. It is dichotomous city with a blend of modern high-rise and
deteriorating slum quarters. Water supply and sanitation, waste
management and housing are continuing to be serious problems.
Forest wood based domestic energy use as well as uncontrolled
emissions from mobile and fixed sources has endangered the state of
the urban environment. Analysis based on satellite imagery has
revealed the deteriorating urban environment within the last three
decades. The recently restructured city administration has brought
improvements in the condition of the urban environment. However,
the overwhelming size of the challenges faced by the city dwarfed
their fairly good results.
Abstract: We demonstrate the synthesis of intermediary views
within a sequence of color encoded, materials discriminating, X-ray
images that exhibit animated depth in a visual display. During the
image acquisition process, the requirement for a linear X-ray detector
array is replaced by synthetic image. Scale Invariant Feature
Transform, SIFT, in combination with material segmented morphing
is employed to produce synthetic imagery. A quantitative analysis of
the feature matching performance of the SIFT is presented along with
a comparative study of the synthetic imagery. We show that the total
number of matches produced by SIFT reduces as the angular
separation between the generating views increases. This effect is
accompanied by an increase in the total number of synthetic pixel
errors. The trends observed are obtained from 15 different luggage
items. This programme of research is in collaboration with the UK
Home Office and the US Dept. of Homeland Security.
Abstract: This paper presents an integrated model that
automatically measures the change of rivers, damage area of bridge
surroundings, and change of vegetation. The proposed model is on the
basis of a neurofuzzy mechanism enhanced by SOM optimization
algorithm, and also includes three functions to deal with river imagery.
High resolution imagery from FORMOSAT-2 satellite taken before
and after the invasion period is adopted. By randomly selecting a
bridge out of 129 destroyed bridges, the recognition results show that
the average width has increased 66%. The ruined segment of the
bridge is located exactly at the most scour region. The vegetation
coverage has also reduced to nearly 90% of the original. The results
yielded from the proposed model demonstrate a pinpoint accuracy rate
at 99.94%. This study brings up a successful tool not only for
large-scale damage assessment but for precise measurement to
disasters.
Abstract: In this study we focus on improvement performance
of a cue based Motor Imagery Brain Computer Interface (BCI). For
this purpose, data fusion approach is used on results of different
classifiers to make the best decision. At first step Distinction
Sensitive Learning Vector Quantization method is used as a feature
selection method to determine most informative frequencies in
recorded signals and its performance is evaluated by frequency
search method. Then informative features are extracted by packet
wavelet transform. In next step 5 different types of classification
methods are applied. The methodologies are tested on BCI
Competition II dataset III, the best obtained accuracy is 85% and the
best kappa value is 0.8. At final step ordered weighted averaging
(OWA) method is used to provide a proper aggregation classifiers
outputs. Using OWA enhanced system accuracy to 95% and kappa
value to 0.9. Applying OWA just uses 50 milliseconds for
performing calculation.
Abstract: Currently in many major cities, public transit schedules
are disseminated through lists of routes, grids of stop times and
static maps. This paper describes a web based geographic information
system which disseminates the same schedule information through
intuitive GIS techniques. Using data from Calgary, Canada, an map
based interface has been created to allow users to see routes, stops and
moving buses all at once. Zoom and pan controls as well as satellite
imagery allows users to apply their personal knowledge about the
local geography to achieve faster, and more pertinent transit results.
Using asynchronous requests to web services, users are immersed
in an application where buses and stops can be added and removed
interactively, without the need to wait for responses to HTTP requests.
Abstract: The main issue of interest here is whether individuals
who differ in arithmetical reasoning ability and levels of imagery ability display different brain activity during the conduct of mental
arithmetical reasoning tasks. This was a case study of four
participants who represented four extreme combinations of Maths –Imagery abilities: ie., low-low, high-high, high-low, low-high respectively. As the Ps performed a series of 60 arithmetical reasoning tasks, 128-channel EEG recordings were taken and the
pre-response interval subsequently analysed using EGI GeosourceTM
software. The P who was high in both imagery and maths ability
showed peak activity prior to response in BA7 (superior parietal cortex) but other Ps did not show peak activity in this region. The
results are considered in terms of the diverse routes that may be employed by individuals during the conduct of arithmetical reasoning
tasks and the possible implications of this for mathematics education.
Abstract: Megalopolis is a group of densely populated metropolitan areas that combine to form an urban complex. Since China introduced the economic reforms in late 1970s, the Chinese urban system has experienced unprecedented growth. The process of urbanisation prevailed in the 1980s, and the process of predominantly large city growth appeared to continue through 1990s and 2000s. In this study, the magnitude and pattern of urbanisation in China during 1990s were examined using remotely sensed imagery acquired by TM/ETM+ sensor onboard the Landsat satellites. The development of megalopolis areas in China was also studied based on the GIS analysis of the increases of urban and built-up area from 1990 to 2000. The analysis suggests that in the traditional agricultural zones in China, e.g., Huang-Huai-Hai Plains, Changjiang River Delta, Pearl River Delta and Sichuan Basin, the urban and built-up areas increased by 1.76 million hectares, of which 0.82 million hectares are expansion of urban areas, an increase of 24.78% compared with 1990 at the national scale. The Yellow River Delta, Changjiang River Delta and Pearl River Delta also saw an increase of urban and built-up area by 63.9%, 66.2% and 83.0% respectively. As a result, three major megalopolises were developed in China: the Guangzhou-Shenzhen-Hong Kong- Macau (Pearl River Delta: PRD) megalopolis area, the Shanghai- Nanjing-Hangzhou (Changjiang River Delta: CRD) megalopolis area and the Beijing-Tianjing-Tangshan-Qinhuangdao (Yellow River Delta-Bohai Sea Ring: YRD) megalopolis area. The relationship between the processed of megalopolisation and the inter-provincial population flow was also explored in the context of social-economic and transport infrastructure development in Post-reform China.
Abstract: Repeated observation of a given area over time yields
potential for many forms of change detection analysis. These
repeated observations are confounded in terms of radiometric
consistency due to changes in sensor calibration over time,
differences in illumination, observation angles and variation in
atmospheric effects.
This paper demonstrates applicability of an empirical relative
radiometric normalization method to a set of multitemporal cloudy
images acquired by Resourcesat1 LISS III sensor. Objective of this
study is to detect and remove cloud cover and normalize an image
radiometrically. Cloud detection is achieved by using Average
Brightness Threshold (ABT) algorithm. The detected cloud is
removed and replaced with data from another images of the same
area. After cloud removal, the proposed normalization method is
applied to reduce the radiometric influence caused by non surface
factors. This process identifies landscape elements whose reflectance
values are nearly constant over time, i.e. the subset of non-changing
pixels are identified using frequency based correlation technique. The
quality of radiometric normalization is statistically assessed by R2
value and mean square error (MSE) between each pair of analogous
band.
Abstract: Texture information plays increasingly an important
role in remotely sensed imagery classification and many pattern
recognition applications. However, the selection of relevant textural
features to improve this classification accuracy is not a straightforward
task. This work investigates the effectiveness of two Mutual
Information Feature Selector (MIFS) algorithms to select salient
textural features that contain highly discriminatory information for
multispectral imagery classification. The input candidate features are
extracted from a SPOT High Resolution Visible(HRV) image using
Wavelet Transform (WT) at levels (l = 1,2).
The experimental results show that the selected textural features
according to MIFS algorithms make the largest contribution to
improve the classification accuracy than classical approaches such
as Principal Components Analysis (PCA) and Linear Discriminant
Analysis (LDA).
Abstract: The objective of this paper is to characterize the spontaneous Electroencephalogram (EEG) signals of four different motor imagery tasks and to show hereby a possible solution for the present binary communication between the brain and a machine ora Brain-Computer Interface (BCI). The processing technique used in this paper was the fractal analysis evaluated by the Critical Exponent Method (CEM). The EEG signal was registered in 5 healthy subjects,sampling 15 measuring channels at 1024 Hz.Each channel was preprocessed by the Laplacian space ltering so as to reduce the space blur and therefore increase the spaceresolution. The EEG of each channel was segmented and its Fractaldimension (FD) calculated. The FD was evaluated in the time interval corresponding to the motor imagery and averaged out for all the subjects (each channel). In order to characterize the FD distribution,the linear regression curves of FD over the electrodes position were applied. The differences FD between the proposed mental tasks are quantied and evaluated for each experimental subject. The obtained results of the proposed method are a substantial fractal dimension in the EEG signal of motor imagery tasks and can be considerably utilized as the multiple-states BCI applications.
Abstract: The class of geometric deformable models, so-called
level sets, has brought tremendous impact to medical imagery. In
this paper we present yet another application of level sets to medical
imaging. The method we give here will in a way modify the speed
term in the standard level sets equation of motion. To do so we
build a potential based on the distance and the gradient of the
image we study. In turn the potential gives rise to the force field:
F~F(x, y) = P
∀(p,q)∈I
((x, y) - (p, q)) |ÔêçI(p,q)|
|(x,y)-(p,q)|
2 . The direction
and intensity of the force field at each point will determine the
direction of the contour-s evolution. The images we used to test
our method were produced by the Univesit'e de Sherbrooke-s PET
scanners.