• Journal of KIISE:Computer Systems and Theory
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• v.31 no.5_6
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• pp.288-296
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• 2004

This paper proposes a new mesh simplification algorithm using differential error metric. Many simplification algorithms make use of a distance error metric, but it is hard to measure an accurate geometric error for the high-curvature region even though it has a small distance error measured in distance error metric. This paper proposes a new differential error metric that results in unifying a distance metric and its first and second order differentials, which become tangent vector and curvature metric. Since discrete surfaces may be considered as piecewise linear approximation of unknown smooth surfaces, theses differentials can be estimated and we can construct new concept of differential error metric for discrete surfaces with them. For our simplification algorithm based on iterative edge collapses, this differential error metric can assign the new vertex position maintaining the geometry of an original appearance. In this paper, we clearly show that our simplified results have better quality and smaller geometry error than others.

• Journal of KIISE:Computer Systems and Theory
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• v.27 no.3
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• pp.245-254
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• 2000

This paper proposes a new discrete curvature error metric to generate LOD meshes. For mesh simplification, discrete curvatures are defined with geometric attributes, such as angles and areas of triangular polygonal model, and dihedral angles without any smooth approximation. They can represent characteristics of polygonal surface well. The new error metric based on them, discrete curvature error metric, increases the accuracy of simplified model by preserving the geometric information of original model and can be used as a global error metric. Also we suggest that LOD should be generated not by a simplification ratio but by an error metric. Because LOD means the degree of closeness between original and each level's simplified model. Therefore discrete curvature error metric needs relatively more computations than known other error metrics, but it can efficiently generate and control LOD meshes which preserve overall appearance of original shape and are recognizable explicitly with each level.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 1997.11a
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• pp.435-449
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• 1997

In this paper, a new metric, universal metric, is Proposed for sequential decoding of convolutional decoding. The complexity of Fano metric for Fano's sequential decoding algorithm is compared with that of the proposed universal metric. Since the Fano metric assumes that it has previous knowledge of channel transition probability, the complexity of Fano metric increases as the assumed channel error probability does not coincide with the true channel error probability. However, the universal metric dose not require the previous knowledge of the channel transition probability since it is estimated on a branch by branch basis. It is shown that the complexity of universal metric is much less than that of the Fano metric for bursty noisy channel.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.1
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• pp.97-105
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• 2015

Multiresponse optimization (MRO) seeks to find the setting of input variables, which optimizes the multiple responses simultaneously. The approach of weighted mean squared error (WMSE) minimization for MRO imposes a different weight on the squared bias and variance, which are the two components of the mean squared error (MSE). To date, a weighted sum-based method has been proposed for WMSE minimization. On the other hand, this method has a limitation in that it cannot find the most preferred solution located in a nonconvex region in objective function space. This paper proposes a Tchebycheff metric-based method to overcome the limitations of the weighted sum-based method.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.41 no.10
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• pp.45-52
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• 2004

This Paper presents a modified hard decision Viterbi decoder with an error prediction circuit enhancing performance for the burst error inputs. Viterbi decoder employs the maximum likelihood decoding algorithm which shows excellent error correction capability for the random error inputs. Viterbi decoders, however, suffer poor error correction performance for the burst error inputs under the fading channel. The proposed error prediction algorithm increases error correction capability for the burst errors. The algorithm estimaties the burst error data area using the maximum path metric for the erroneous inputs, It calculates burst error intervals based on increases in the maximum values of a path metric. The proposed decoder keeps a performance the same as the conventional decoders on AWGN channels for the IEEE802.l1a WLAN system. It shows performance inproving 15% on the burst error of multi-path fading channels, widely used in mobile systems.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.50 no.7
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• pp.350-353
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• 2001

In general, the Least Square Error method is used for signal classification to measure distance in the $l^2$ metric or the $L^2$ metric space. A defect of the Least Square Error method is that it does not classify properly some waveforms, which is due to the property of the Least Square Error method: the global analysis. This paper proposes a new linear operator, the Integra-Normalizer, that removes the problem. The Integra-Normalizer possesses excellent property that measures the degree of relative similarity between signals by expanding the functional space with removing the restriction on the functional space inherited by the Least Square Error method. The Integra-Normalizer shows superiority to the Least Square Error method in measuring the relative similarity among one dimensional waveforms.

• Proceedings of the IEEK Conference
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• 2000.11c
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• pp.109-112
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• 2000

Many applications in computer graphics require highly detailed complex models. However, the level of detail may vary considerably according to applications. It is often desirable to use approximations in place of excessively detailed models. We have developed a surface simplification algorithm which uses iterative contractions of edges to simplify models and maintains surface error approximations using a quadric metric. In this paper, we present an improved quadric error metric for simplifying meshes. The new metric, based on subdivided edge classification, results in more accurate simplified meshes. We show that a subdivided edge classification captures discontinuities efficiently. The new scheme is demonstrated on a variety of meshes.

• Journal of Korea Society of Industrial Information Systems
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• v.2 no.2
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• pp.219-228
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• 1997

The Fano metric is the maximum likelihood decoding choice for convlutional code for binary symmetric channel. The Fano metric assumes that it has previous knowledge of channel error probability. However, the bit errors in real channel occur in bursts and the channel error probability can not be known exactly. Thus, the Fano metric is not the maximum likelihood choice for bursty-noise channel. In this paper universal metri which dose not require the previous knowlege of the channel transition probability is used for sequential decoding. It is shown that the complexity of the universal is much less than that of the Fano metric bursty-noise channel, since it is estimated on a branch by branch basis.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.6 no.1
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• pp.13-24
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• 1988

The determination of three-dimensional positions on a circular or cylindrical surface covers a variety of applications. As an example, consider the monitoring of structures, which is an important topic in the broad category of deformation analysis. The use of convergent photography in determination of these positions has the many advantages over survey based procedures. This paper illustrates results from bundle adjustments derived from convergent photography of a cylindrical object, with both metric and non-metric cameras utilized in the test. In addition to standard error comparisons resulting from the error analysis provided by the bundle adjustments, object space coordinates resulting from metric and non-metric camera network geometries will also be compared.

• Journal of Korea Society of Digital Industry and Information Management
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• v.18 no.4
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• pp.13-21
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• 2022

Recently, in wireless video sensor networks(WVSN), various schemes for efficient video data transmission have been studied. In this paper, a layer based cooperative relaying(LCR) algorithm is proposed for minimizing scalable video transmission distortion from packet loss in WVSN. The proposed LCR algorithm consists of two modules. In the first step, a parameter based error propagation metric is proposed to predict the effect of each scalable layer on video quality degradation at low complexity. In the second step, a layer-based cooperative relay algorithm is proposed to minimize distortion due to packet loss using the proposed error propagation metric and channel information of the video sensor node and relay node. In the experiment, the proposed algorithm showed that the improvement of peak signal-to-noise ratio (PSNR) in various channel environments, compared to the previous algorithm(Energy based Cooperative Relaying, ECR) without considering the metric of error propagation.The proposed LCR algorithm minimizes video quality degradation from packet loss using both the channel information of relaying node and the amount of layer based error propagation in scalable video.