66,962 research outputs found
Dynamic 3D shape measurement based on the phase-shifting moir\'e algorithm
In order to increase the efficiency of phase retrieval,Wang proposed a
high-speed moire phase retrieval method.But it is used only to measure the tiny
object. In view of the limitation of Wang method,we proposed a dynamic
three-dimensional (3D) measurement based on the phase-shifting moire
algorithm.First, four sinusoidal fringe patterns with a pi/2 phase-shift are
projected on the reference plane and acquired four deformed fringe patterns of
the reference plane in advance. Then only single-shot deformed fringe pattern
of the tested object is captured in measurement process.Four moire fringe
patterns can be obtained by numerical multiplication between the the AC
component of the object pattern and the AC components of the reference patterns
respectively. The four low-frequency components corresponding to the moire
fringe patterns are calculated by the complex encoding FT (Fourier transform)
,spectrum filtering and inverse FT.Thus the wrapped phase of the object can be
determined in the tangent form from the four phase-shifting moire fringe
patterns using the four-step phase shifting algorithm.The continuous phase
distribution can be obtained by the conventional unwrapping algorithm. Finally,
experiments were conducted to prove the validity and feasibility of the
proposed method. The results are analyzed and compared with those of Wang
method, demonstrating that our method not only can expand the measurement
scope, but also can improve accuracy.Comment: 14 pages,5 figures. ams.or
Structured Knowledge Representation for Image Retrieval
We propose a structured approach to the problem of retrieval of images by
content and present a description logic that has been devised for the semantic
indexing and retrieval of images containing complex objects. As other
approaches do, we start from low-level features extracted with image analysis
to detect and characterize regions in an image. However, in contrast with
feature-based approaches, we provide a syntax to describe segmented regions as
basic objects and complex objects as compositions of basic ones. Then we
introduce a companion extensional semantics for defining reasoning services,
such as retrieval, classification, and subsumption. These services can be used
for both exact and approximate matching, using similarity measures. Using our
logical approach as a formal specification, we implemented a complete
client-server image retrieval system, which allows a user to pose both queries
by sketch and queries by example. A set of experiments has been carried out on
a testbed of images to assess the retrieval capabilities of the system in
comparison with expert users ranking. Results are presented adopting a
well-established measure of quality borrowed from textual information
retrieval
A new design tool for feature extraction in noisy images based on grayscale hit-or-miss transforms
The Hit-or-Miss transform (HMT) is a well known morphological transform capable of identifying features in digital images. When image features contain noise, texture or some other distortion, the HMT may fail. Various researchers have extended the HMT in different ways to make it more robust to noise. The most successful, and most recent extensions of the HMT for noise robustness, use rank order operators in place of standard morphological erosions and dilations. A major issue with the proposed methods is that no technique is provided for calculating the parameters that are introduced to generalize the HMT, and, in most cases, these parameters are determined empirically. We present here, a new conceptual interpretation of the HMT which uses a percentage occupancy (PO) function to implement the erosion and dilation operators in a single pass of the image. Further, we present a novel design tool, derived from this PO function that can be used to determine the only parameter for our routine and for other generalizations of the HMT proposed in the literature. We demonstrate the power of our technique using a set of very noisy images and draw a comparison between our method and the most recent extensions of the HMT
Improved shape-signature and matching methods for model-based robotic vision
Researchers describe new techniques for curve matching and model-based object recognition, which are based on the notion of shape-signature. The signature which researchers use is an approximation of pointwise curvature. Described here is curve matching algorithm which generalizes a previous algorithm which was developed using this signature, allowing improvement and generalization of a previous model-based object recognition scheme. The results and the experiments described relate to 2-D images. However, natural extensions to the 3-D case exist and are being developed
Deep Exemplar 2D-3D Detection by Adapting from Real to Rendered Views
This paper presents an end-to-end convolutional neural network (CNN) for
2D-3D exemplar detection. We demonstrate that the ability to adapt the features
of natural images to better align with those of CAD rendered views is critical
to the success of our technique. We show that the adaptation can be learned by
compositing rendered views of textured object models on natural images. Our
approach can be naturally incorporated into a CNN detection pipeline and
extends the accuracy and speed benefits from recent advances in deep learning
to 2D-3D exemplar detection. We applied our method to two tasks: instance
detection, where we evaluated on the IKEA dataset, and object category
detection, where we out-perform Aubry et al. for "chair" detection on a subset
of the Pascal VOC dataset.Comment: To appear in CVPR 201
The Bar Pattern Speed of NGC 1433 Estimated Via Sticky-Particle Simulations
We present detailed numerical simulations of NGC 1433, an intermediate-type
barred spiral showing strong morphological features including a secondary bar,
nuclear ring, inner ring, outer pseudoring, and two striking, detached spiral
arcs known as ``plumes.'' This galaxy is an ideal candidate for recreating the
observed morphology through dynamical models and determining the pattern speed.
We derived a gravitational potential from an -band image of the galaxy and
simulated the behavior of a two-dimensional disk of 100,000 inelastically
colliding gas particles. We find that the closest matching morphology between a
-band image and a simulation occurs with a pattern speed of 0.89 km s
arcsec 5-10%. We also determine that the ratio of corotation
radius to the average published bar radius is 1.7 0.3, with the ambiguity
in the bar radius being the largest contributor to the error.Comment: Accepted for publication by The Astronomical Journal. 34 pages, 13
figures, 2 table
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