5,346 research outputs found
A Comparative study of Arabic handwritten characters invariant feature
This paper is practically interested in the unchangeable feature of Arabic
handwritten character. It presents results of comparative study achieved on
certain features extraction techniques of handwritten character, based on Hough
transform, Fourier transform, Wavelet transform and Gabor Filter. Obtained
results show that Hough Transform and Gabor filter are insensible to the
rotation and translation, Fourier Transform is sensible to the rotation but
insensible to the translation, in contrast to Hough Transform and Gabor filter,
Wavelets Transform is sensitive to the rotation as well as to the translation
Automated Quantitative Description of Spiral Galaxy Arm-Segment Structure
We describe a system for the automatic quantification of structure in spiral
galaxies. This enables translation of sky survey images into data needed to
help address fundamental astrophysical questions such as the origin of spiral
structure---a phenomenon that has eluded theoretical description despite 150
years of study (Sellwood 2010). The difficulty of automated measurement is
underscored by the fact that, to date, only manual efforts (such as the citizen
science project Galaxy Zoo) have been able to extract information about large
samples of spiral galaxies. An automated approach will be needed to eliminate
measurement subjectivity and handle the otherwise-overwhelming image quantities
(up to billions of images) from near-future surveys. Our approach automatically
describes spiral galaxy structure as a set of arcs, precisely describing spiral
arm segment arrangement while retaining the flexibility needed to accommodate
the observed wide variety of spiral galaxy structure. The largest existing
quantitative measurements were manually-guided and encompassed fewer than 100
galaxies, while we have already applied our method to more than 29,000
galaxies. Our output matches previous information, both quantitatively over
small existing samples, and qualitatively against human classifications from
Galaxy Zoo.Comment: 9 pages;4 figures; 2 tables; accepted to CVPR (Computer Vision and
Pattern Recognition), June 2012, Providence, Rhode Island, June 16-21, 201
Kannada Character Recognition System A Review
Intensive research has been done on optical character recognition ocr and a
large number of articles have been published on this topic during the last few
decades. Many commercial OCR systems are now available in the market, but most
of these systems work for Roman, Chinese, Japanese and Arabic characters. There
are no sufficient number of works on Indian language character recognition
especially Kannada script among 12 major scripts in India. This paper presents
a review of existing work on printed Kannada script and their results. The
characteristics of Kannada script and Kannada Character Recognition System kcr
are discussed in detail. Finally fusion at the classifier level is proposed to
increase the recognition accuracy.Comment: 12 pages, 8 figure
A rigorous definition of axial lines: ridges on isovist fields
We suggest that 'axial lines' defined by (Hillier and Hanson, 1984) as lines
of uninterrupted movement within urban streetscapes or buildings, appear as
ridges in isovist fields (Benedikt, 1979). These are formed from the maximum
diametric lengths of the individual isovists, sometimes called viewsheds, that
make up these fields (Batty and Rana, 2004). We present an image processing
technique for the identification of lines from ridges, discuss current
strengths and weaknesses of the method, and show how it can be implemented
easily and effectively.Comment: 18 pages, 5 figure
Image fusion techniqes for remote sensing applications
Image fusion refers to the acquisition, processing and synergistic combination of information provided by various sensors or by the same sensor in many measuring contexts. The aim of this survey paper is to describe three typical applications of data fusion in remote sensing. The first study case considers the problem of the Synthetic Aperture Radar (SAR) Interferometry, where a pair of antennas are used to obtain an elevation map of the observed scene; the second one refers to the fusion of multisensor and multitemporal (Landsat Thematic Mapper and SAR) images of the same site acquired at different times, by using neural networks; the third one presents a processor to fuse multifrequency, multipolarization and mutiresolution SAR images, based on wavelet transform and multiscale Kalman filter. Each study case presents also results achieved by the proposed techniques applied to real data
Ship Wake Detection in SAR Images via Sparse Regularization
In order to analyse synthetic aperture radar (SAR) images of the sea surface,
ship wake detection is essential for extracting information on the wake
generating vessels. One possibility is to assume a linear model for wakes, in
which case detection approaches are based on transforms such as Radon and
Hough. These express the bright (dark) lines as peak (trough) points in the
transform domain. In this paper, ship wake detection is posed as an inverse
problem, which the associated cost function including a sparsity enforcing
penalty, i.e. the generalized minimax concave (GMC) function. Despite being a
non-convex regularizer, the GMC penalty enforces the overall cost function to
be convex. The proposed solution is based on a Bayesian formulation, whereby
the point estimates are recovered using maximum a posteriori (MAP) estimation.
To quantify the performance of the proposed method, various types of SAR images
are used, corresponding to TerraSAR-X, COSMO-SkyMed, Sentinel-1, and ALOS2. The
performance of various priors in solving the proposed inverse problem is first
studied by investigating the GMC along with the L1, Lp, nuclear and total
variation (TV) norms. We show that the GMC achieves the best results and we
subsequently study the merits of the corresponding method in comparison to two
state-of-the-art approaches for ship wake detection. The results show that our
proposed technique offers the best performance by achieving 80% success rate.Comment: 18 page
Thermal tides in the Martian middle atmosphere as seen by the Mars Climate Sounder
The first systematic observations of the middle atmosphere of Mars (35â80km) with the Mars Climate Sounder (MCS) show dramatic patterns of diurnal thermal variation, evident in retrievals of temperature and water ice opacity. At the time of writing, the data set of MCS limb retrievals is sufficient for spectral analysis within a limited range of latitudes and seasons. This analysis shows that these thermal variations are almost exclusively associated with a diurnal thermal tide. Using a Martian general circulation model to extend our analysis, we show that the diurnal thermal tide dominates these patterns for all latitudes and all seasons
Coronal Mass Ejection Detection using Wavelets, Curvelets and Ridgelets: Applications for Space Weather Monitoring
Coronal mass ejections (CMEs) are large-scale eruptions of plasma and
magnetic feld that can produce adverse space weather at Earth and other
locations in the Heliosphere. Due to the intrinsic multiscale nature of
features in coronagraph images, wavelet and multiscale image processing
techniques are well suited to enhancing the visibility of CMEs and supressing
noise. However, wavelets are better suited to identifying point-like features,
such as noise or background stars, than to enhancing the visibility of the
curved form of a typical CME front. Higher order multiscale techniques, such as
ridgelets and curvelets, were therefore explored to characterise the morphology
(width, curvature) and kinematics (position, velocity, acceleration) of CMEs.
Curvelets in particular were found to be well suited to characterising CME
properties in a self-consistent manner. Curvelets are thus likely to be of
benefit to autonomous monitoring of CME properties for space weather
applications.Comment: Accepted for publication in Advances in Space Research (3 April 2010
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