100,436 research outputs found
An Online Distributed Boundary Detection and Classiļ¬cation Algorithm for Mobile Sensor Networks
We present a novel online distributed boundaryĀ detection and classiļ¬cation algorithm in order to improveĀ accuracy of boundary detection and classiļ¬cation for mobileĀ sensor networks. This algorithm is developed by incorporating aĀ boundary detection algorithm and our newly proposed boundaryĀ error correction algorithm. It is a fully distributed algorithmĀ based on the geometric approach allowing to remove boundaryĀ errors without recursive process and global synchronization.Ā Moreover, the algorithm allows mobile nodes to identify theirĀ states corresponding to their positions in network topologies,Ā leading to self-classiļ¬cation of interior and exterior boundariesĀ of network topologies. We have demonstrated effectiveness ofthis algorithm in both simulation and real-world experimentsĀ and proved that the accuracy of the ratio of correctly identiļ¬edĀ nodes over the total number of nodes is 100%
Overviews of Optimization Techniques for Geometric Estimation
We summarize techniques for optimal geometric estimation from noisy observations for computer
vision applications. We first discuss the interpretation of optimality and point out that geometric
estimation is different from the standard statistical estimation. We also describe our noise
modeling and a theoretical accuracy limit called the KCR lower bound. Then, we formulate estimation
techniques based on minimization of a given cost function: least squares (LS), maximum
likelihood (ML), which includes reprojection error minimization as a special case, and Sampson
error minimization. We describe bundle adjustment and the FNS scheme for numerically solving
them and the hyperaccurate correction that improves the accuracy of ML. Next, we formulate
estimation techniques not based on minimization of any cost function: iterative reweight, renormalization,
and hyper-renormalization. Finally, we show numerical examples to demonstrate that
hyper-renormalization has higher accuracy than ML, which has widely been regarded as the most
accurate method of all. We conclude that hyper-renormalization is robust to noise and currently is
the best method
Spread spectrum-based video watermarking algorithms for copyright protection
Merged with duplicate record 10026.1/2263 on 14.03.2017 by CS (TIS)Digital technologies know an unprecedented expansion in the last years. The consumer can
now benefit from hardware and software which was considered state-of-the-art several years
ago. The advantages offered by the digital technologies are major but the same digital
technology opens the door for unlimited piracy. Copying an analogue VCR tape was certainly
possible and relatively easy, in spite of various forms of protection, but due to the analogue
environment, the subsequent copies had an inherent loss in quality. This was a natural way of
limiting the multiple copying of a video material. With digital technology, this barrier
disappears, being possible to make as many copies as desired, without any loss in quality
whatsoever. Digital watermarking is one of the best available tools for fighting this threat.
The aim of the present work was to develop a digital watermarking system compliant with the
recommendations drawn by the EBU, for video broadcast monitoring. Since the watermark
can be inserted in either spatial domain or transform domain, this aspect was investigated and
led to the conclusion that wavelet transform is one of the best solutions available. Since
watermarking is not an easy task, especially considering the robustness under various attacks
several techniques were employed in order to increase the capacity/robustness of the system:
spread-spectrum and modulation techniques to cast the watermark, powerful error correction
to protect the mark, human visual models to insert a robust mark and to ensure its invisibility.
The combination of these methods led to a major improvement, but yet the system wasn't
robust to several important geometrical attacks. In order to achieve this last milestone, the
system uses two distinct watermarks: a spatial domain reference watermark and the main
watermark embedded in the wavelet domain. By using this reference watermark and techniques
specific to image registration, the system is able to determine the parameters of the attack and
revert it. Once the attack was reverted, the main watermark is recovered. The final result is a
high capacity, blind DWr-based video watermarking system, robust to a wide range of attacks.BBC Research & Developmen
Results of precision processing (scene correction) of ERTS-1 images using digital image processing techniques
ERTS-1 MSS and RBV data recorded on computer compatible tapes have been analyzed and processed, and preliminary results have been obtained. No degradation of intensity (radiance) information occurred in implementing the geometric correction. The quality and resolution of the digitally processed images are very good, due primarily to the fact that the number of film generations and conversions is reduced to a minimum. Processing times of digitally processed images are about equivalent to the NDPF electro-optical processor
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