29,770 research outputs found
Multiscale Extraction and Representation of Features from Medical Images
For automatic registration of medical images, we must search for geometric features that are invariant both with respect to rigid transformations and to smooth changes of resolution. Beginning with Witkin's seminal paper, scale space theory provides an elegant framework for studying the multiscale behavior of these characteristics. However, a natural scale-space representation of features, useful for practical applications, is still missing. We address here the problem of multiscale extraction and representation of characteristic points based on iso-surface techniques. Our main concern is with images: we analyze corner points at increasing scales using the Marching Lines algorithm. Since we can exploit the intrinsic nature of intensity of medical images, segmentation of components or parameterization of curves is not needed, in contrast with other methods. Due to the direct use of the coordinates of points, we get a representation of orbits, which is very convenient both for detection at coarse scale and for localization at fine scale. We find that the significance of \corner\ depends not only on their scale-space lifetime but also on their relationship with curvature inflexion points
The Local Structure of Space-Variant Images
Local image structure is widely used in theories of both machine and biological vision. The form of the differential operators describing this structure for space-invariant images has been well documented (e.g. Koenderink, 1984). Although space-variant coordinates are universally used in mammalian visual systems, the form of the operators in the space-variant domain has received little attention. In this report we derive the form of the most common differential operators and surface characteristics in the space-variant domain and show examples of their use. The operators include the Laplacian, the gradient and the divergence, as well as the fundamental forms of the image treated as a surface. We illustrate the use of these results by deriving the space-variant form of corner detection and image enhancement algorithms. The latter is shown to have interesting properties in the complex log domain, implicitly encoding a variable grid-size integration of the underlying PDE, allowing rapid enhancement of large scale peripheral features while preserving high spatial frequencies in the fovea.Office of Naval Research (N00014-95-I-0409
Performance Assessment of Feature Detection Algorithms: A Methodology and Case Study on Corner Detectors
In this paper we describe a generic methodology for evaluating the labeling performance of feature detectors. We describe a method for generating a test set and apply the methodology to the performance assessment of three well-known corner detectors: the Kitchen-Rosenfeld, Paler et al. and Harris-Stephens corner detectors. The labeling deficiencies of each of these detectors is related to their discrimination ability between corners and various of the features which comprise the class of noncorners
Direct Observation of Cosmic Strings via their Strong Gravitational Lensing Effect: II. Results from the HST/ACS Image Archive
We have searched 4.5 square degrees of archival HST/ACS images for cosmic
strings, identifying close pairs of similar, faint galaxies and selecting
groups whose alignment is consistent with gravitational lensing by a long,
straight string. We find no evidence for cosmic strings in five large-area HST
treasury surveys (covering a total of 2.22 square degrees), or in any of 346
multi-filter guest observer images (1.18 square degrees). Assuming that
simulations ccurately predict the number of cosmic strings in the universe,
this non-detection allows us to place upper limits on the unitless Universal
cosmic string tension of G mu/c^2 < 2.3 x 10^-6, and cosmic string density of
Omega_s < 2.1 x 10^-5 at the 95% confidence level (marginalising over the other
parameter in each case). We find four dubious cosmic string candidates in 318
single filter guest observer images (1.08 square degrees), which we are unable
to conclusively eliminate with existing data. The confirmation of any one of
these candidates as cosmic strings would imply G mu/c^2 ~ 10^-6 and Omega_s ~
10^-5. However, we estimate that there is at least a 92% chance that these
string candidates are random alignments of galaxies. If we assume that these
candidates are indeed false detections, our final limits on G mu/c^2 and
Omega_s fall to 6.5 x 10^-7 and 7.3 x 10^-6. Due to the extensive sky coverage
of the HST/ACS image archive, the above limits are universal. They are quite
sensitive to the number of fields being searched, and could be further reduced
by more than a factor of two using forthcoming HST data.Comment: 21 pages, 18 figure
A new Edge Detector Based on Parametric Surface Model: Regression Surface Descriptor
In this paper we present a new methodology for edge detection in digital
images. The first originality of the proposed method is to consider image
content as a parametric surface. Then, an original parametric local model of
this surface representing image content is proposed. The few parameters
involved in the proposed model are shown to be very sensitive to
discontinuities in surface which correspond to edges in image content. This
naturally leads to the design of an efficient edge detector. Moreover, a
thorough analysis of the proposed model also allows us to explain how these
parameters can be used to obtain edge descriptors such as orientations and
curvatures.
In practice, the proposed methodology offers two main advantages. First, it
has high customization possibilities in order to be adjusted to a wide range of
different problems, from coarse to fine scale edge detection. Second, it is
very robust to blurring process and additive noise. Numerical results are
presented to emphasis these properties and to confirm efficiency of the
proposed method through a comparative study with other edge detectors.Comment: 21 pages, 13 figures and 2 table
An Atomic Gravitational Wave Interferometric Sensor in Low Earth Orbit (AGIS-LEO)
We propose an atom interferometer gravitational wave detector in low Earth
orbit (AGIS-LEO). Gravitational waves can be observed by comparing a pair of
atom interferometers separated over a ~30 km baseline. In the proposed
configuration, one or three of these interferometer pairs are simultaneously
operated through the use of two or three satellites in formation flight. The
three satellite configuration allows for the increased suppression of multiple
noise sources and for the detection of stochastic gravitational wave signals.
The mission will offer a strain sensitivity of < 10^(-18) / Hz^(1/2) in the 50
mHz - 10 Hz frequency range, providing access to a rich scientific region with
substantial discovery potential. This band is not currently addressed with the
LIGO or LISA instruments. We analyze systematic backgrounds that are relevant
to the mission and discuss how they can be mitigated at the required levels.
Some of these effects do not appear to have been considered previously in the
context of atom interferometry, and we therefore expect that our analysis will
be broadly relevant to atom interferometric precision measurements. Finally, we
present a brief conceptual overview of shorter-baseline (< 100 m) atom
interferometer configurations that could be deployed as proof-of-principle
instruments on the International Space Station (AGIS-ISS) or an independent
satellite.Comment: 37 pages, 21 figure
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