Planned Papers
J. Apolinar Muñoz-Rodríguez *
Centro de Investigaciones en Optica, A. C., Leon, Gto, 37150 Mexico, Tel: (477) 441 42 00
*Author to whom correspondence should be addressed; E-mail: munoza@foton.cio.mx
Article: Surface sensing by dynamic metrology and algorithms of artificial intelligence
Abstract:
A vision system for three-dimensional sensing based on algorithms of
artificial intelligence in laser metrology is presented. In this
technique, the surface detection is performed by a dynamic setup based
on laser scanning and image processing. The modeling of this setup is
performed by a network of a laser line and the camera position. Also,
the vision parameters are deduced by the network and image processing.
From this dynamic setup, occlusions and small details can be retrieved.
These results can not be produced by a static setup. The camera
is moved toward the surface to capture the small details. In the
occlusions, the camera is moved toward the laser line to retrieve the
occluded region. The surface assembling of the occluded region is
performed by pattern recognition via Hu moments. Thus, the complete
surface reconstruction is performed automatically by computational
algorithms. In this manner, the errors of the physical measurements are
not passed to the vision system. This kind of modeling improves the
performance and the accuracy of the surface sensor. To elucidate this
out, the network results are compared with the results of a contact
method. To carry it out, a root mean square of error is calculated.
Thus, a contribution in laser metrology for shape detection is
achieved. This technique is tested with real objects and its
experimental results are presented. Also, the time processing is
described.
Keywords: Sensor of surface, laser metrology, Pattern recognition, approximation network.
Liangpei
Zhang, Xin HuangThe
State Key Laboratory of Information Engineering in Surveying,
Mapping and Remote Sensing; Wuhan University, P. R. China
Article: Advances in feature
extraction, mapping and application algorithms for very high resolution (VHR) remote
sensors
Abstract: In recent years, the image processing
algorithms for very high resolution (VHR) imagery have received much attention
since this new data can provide a large amount of detailed ground information.
However, the availability of this type of data poses challenges to image
information extraction, classification and applications. This paper reviews the
feature extraction, classification and application algorithms for imagery from the
VHR sensors. First, we introduce the widely used VHR sensors (e.g. SPOT-5,
QuickBird, IKONOS). Then, we present an overview of the new advances in feature
extraction, including extraction of shape and structural information,
exploitation of texture measures, and analysis of object-based segmentation. Meanwhile,
the classifiers used for VHR image classification are also discussed, such as
the traditional Gaussian maximum likelihood (GML), neural networks (NN),
support vector machines (SVM), and machine learning algorithms. After that, the
applications of the VHR sensors are summarized, concerning the environment
management, precision farming, military applications, hazards monitoring, etc.
Key Words: VHR sensors,
feature extraction, classification, classifiers.
Chunyu Ai, N. Xiong, A. Vasilakos, Yingshu LiArticle: Data Estimation in Sensor Networks Using
Physical and Statistical Methodologies
Abstract: Wireless
Sensor Networks (WSNs) are employed in
many applications in order to collect data. One key challenge is to
minimize energy consumption to prolong network lifetime. A scheme of
making some nodes asleep and estimating their values according to the
other active nodes’ readings has been proved energy-efficient. For the
purpose of improving the precision of estimation, we propose two
powerful estimation models, Data Estimation using Physical Model (DEPM)
and Data Estimation using Statistical Model (DESM). DEPM estimates the
values of sleeping nodes by the physical characteristics of sensed
attributes, while DESM estimates the values through the spatial and
temporal correlations of the nodes. Experimental results on real sensor
networks show that the proposed techniques provide accurate estimations
and conserve energy efficiently.
Jiang DongReview: Advances
in multiple resource data fusion: algorithm and application.
Abstract: will be added soon.
Shaohui ChenArticle: Scaling-up Transformation of Multisensor Images with
Multiple Resolutions.
Abstract: Intensity
hue saturation (IHS) and empirical mode decomposition (EMD) are two
highly efficient image processing methods. In this paper, a combination
of the IHS transform and the EMD is proposed as a general scaling-up
transformation method for fusing high resolution panchromatic image
(HRPI) with low resolution multispectral images (LRMIs). The principle
consists of transforming the LRMIs into the IHS components.The
low-resolution intensity component (LRIC) is fused with the HRPI in the
EMD domain through a suitable model. Then, the high-resolution
intensity component (HRIC) produced is substituted to the LRIC. High
resolution multispectral images (HRMIs) are obtained through
the inverse EMD and IHS transforms. Quickbird images are used to
illustrate the superiority of this approach over the IHS and dyadic
wavelet transform(DWT) based methods in terms of preservation of
spectral properties visually and quantitatively.
Ah-Lam Lee, Jung-Han KimArticle: 3-Dimentional Pose Sensor Algorithm for Humanoid Robot
Abstract: In
this paper, an effective 3D pose attitude estimation system for a
humanoid robot was developed. The developed 3D pose sensor system has
four small inertial sensors(One 3D accelerometer and three 1D
gyroscopes) and DSP for its estimation algorithms, and it is
developed for motion feedback in humanoid robots. The developed 3D pose
estimation algorithm has a very effective simple structure composed by
3 modules of a linear acceleration estimator, an external acceleration
detector and a pseudo-accelerometer output estimator. The algorithm
also has an effective switching structure based on probability and
simple feedback loop for the extended Kalman filter. A special
test equipment using linear motor for the testing of the 3D pose sensor
was built and the experimental results showed its very fast convergence
to real values and effective responses. Popular commercial DSP of
TMS320F2812 was used to calculate robot's 3D attitude and translated
acceleration, and the whole system were packed in a small size for
humanoids robots. The output of the 3D pose sensor(pitch, roll, 3D
linear acceleration, and 3D angular rate) can be transmitted to a
humanoid robot at 200Hz frequency.
Keywords: 3D pose sensor, Attitude estimation, Humanoid robot, Extended Kalman filter.
Yaowen YangArticle: Effect of structural vibration on PZT impedance signature
Abstract: Piezoelectric
ceramic Lead Zirconate Titanate (PZT) transducers, working on the
principle of electromechanical impedance (EMI), are increasingly
applied for structural health monitoring (SHM) in aerospace, civil and
mechanical engineering. The PZT transducers are usually surface bonded
to or embedded in a structure and subjected to actuation so as to
interrogate the structure at the desired frequency range. The
interrogation results in the electromechanical admittance (inverse of
EMI) signatures which can be used to estimate the structural health or
integrity according to the changes of the signatures. In the existing
EMI method, the monitored structure is only excited by the PZT
transducers for the interrogating of EMI signature, while the vibration
of the structure caused by the external excitations other than the PZT
actuation is not considered. However, many structures work under
vibrations in practice. To monitor such structures, issues related to
the effects of vibration on the EMI signature need to be addressed
because these effects may lead to misinterpretation of the structural
health. This paper develops an EMI model for beam structures, which
takes into account the effect of beam vibration caused by the external
excitations. An experimental study is carried out to verify the
theoretical model. A lab sized specimen with different external
excitations is tested and the effect of vibration on EMI signature is
discussed.
Silvia Ferrari et al.Article: Robust Deployment of Ocean Sensor Networks for Cooperative Target Tracking
Abstract: will be added soon
M. Baietto, A. D. Wilson, and D. BassiReview tentative title: Applications and advances in electronic-nose technologies
Abstract: will be added soon
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Summary
will be added soon
Keywords
will be added soon
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Mr. Matthias Burkhalter and
Ms. Laura
SimonManaging Editor
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MDPI - Matthias Burkhalter - 4 September 2008