136,029 research outputs found
Motion compensated micro-CT reconstruction for in-situ analysis of dynamic processes
This work presents a framework to exploit the synergy between Digital Volume Correlation ( DVC) and iterative CT reconstruction to enhance the quality of high-resolution dynamic X-ray CT (4D-mu CT) and obtain quantitative results from the acquired dataset in the form of 3D strain maps which can be directly correlated to the material properties. Furthermore, we show that the developed framework is capable of strongly reducing motion artifacts even in a dataset containing a single 360 degrees rotation
Automatic detection of welding defects using the convolutional neural network
Quality control of welded joints is an important step before commissioning of various types of metal structures. The main obstacles to the commissioning of such facilities are the areas where the welded joint deviates from acceptable defective standards. The defects of welded joints include non-welded, foreign inclusions, cracks, pores, etc. The article describes an approach to the detection of the main types of defects of welded joints using a combination of convolutional neural networks and support vector machine methods. Convolutional neural networks are used for primary classification. The support vector machine is used to accurately define defect boundaries. As a preprocessing in our work, we use the methods of morphological filtration. A series of experiments confirms the high efficiency of the proposed method in comparison with pure CNN method for detecting defects
Synchronization of spatiotemporal semiconductor lasers and its application in color image encryption
Optical chaos is a topic of current research characterized by
high-dimensional nonlinearity which is attributed to the delay-induced
dynamics, high bandwidth and easy modular implementation of optical feedback.
In light of these facts, which adds enough confusion and diffusion properties
for secure communications, we explore the synchronization phenomena in
spatiotemporal semiconductor laser systems. The novel system is used in a
two-phase colored image encryption process. The high-dimensional chaotic
attractor generated by the system produces a completely randomized chaotic time
series, which is ideal in the secure encoding of messages. The scheme thus
illustrated is a two-phase encryption method, which provides sufficiently high
confusion and diffusion properties of chaotic cryptosystem employed with unique
data sets of processed chaotic sequences. In this novel method of cryptography,
the chaotic phase masks are represented as images using the chaotic sequences
as the elements of the image. The scheme drastically permutes the positions of
the picture elements. The next additional layer of security further alters the
statistical information of the original image to a great extent along the
three-color planes. The intermediate results during encryption demonstrate the
infeasibility for an unauthorized user to decipher the cipher image. Exhaustive
statistical tests conducted validate that the scheme is robust against noise
and resistant to common attacks due to the double shield of encryption and the
infinite dimensionality of the relevant system of partial differential
equations.Comment: 20 pages, 11 figures; Article in press, Optics Communications (2011
An Automated Method for Tracking Clouds in Planetary Atmospheres
We present an automated method for cloud tracking which can be applied to planetary images. The method is based on a digital correlator which compares two or more consecutive images and identifies patterns by maximizing correlations between image blocks. This approach bypasses the problem of feature detection. Four variations of the algorithm are tested on real cloud images of Jupiter’s white ovals from the Galileo mission, previously analyzed in Vasavada et al. [Vasavada, A.R., Ingersoll, A.P., Banfield, D., Bell, M.,
Gierasch, P.J., Belton, M.J.S., Orton, G.S., Klaasen, K.P., Dejong, E., Breneman, H.H., Jones, T.J., Kaufman, J.M., Magee, K.P., Senske, D.A. 1998. Galileo imaging of Jupiter’s atmosphere: the great red spot, equatorial region, and white ovals. Icarus, 135, 265, doi:10.1006/icar.1998.5984]. Direct correlation, using the sum of squared differences between image radiances as a distance estimator (baseline case), yields displacement vectors very similar to this previous analysis. Combining this distance estimator with the method
of order ranks results in a technique which is more robust in the presence of outliers and noise and of better quality. Finally, we introduce a distance metric which, combined with order ranks, provides results of similar quality to the baseline case and is faster. The new approach can be applied to data from a number of space-based imaging instruments with a non-negligible gain in computing time
A novel pseudo-random number generator based on discrete chaotic iterations
Security of information transmitted through the Internet, against passive or
active attacks is an international concern. The use of a chaos-based
pseudo-random bit sequence to make it unrecognizable by an intruder, is a field
of research in full expansion. This mask of useful information by modulation or
encryption is a fundamental part of the TLS Internet exchange protocol. In this
paper, a new method using discrete chaotic iterations to generate pseudo-random
numbers is presented. This pseudo-random number generator has successfully
passed the NIST statistical test suite (NIST SP800-22). Security analysis shows
its good characteristics. The application for secure image transmission through
the Internet is proposed at the end of the paper.Comment: The First International Conference on Evolving Internet:Internet 2009
pp.71--76 http://dx.doi.org/10.1109/INTERNET.2009.1
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