• Journal of KIISE:Software and Applications
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• v.27 no.5
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• pp.543-550
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• 2000

An adaptive bit-reduced mean absolute difference (ABRMAD) is presented as a criterion for the block-matching algorithm (BMA) to reduce the complexity of the VLSI Implementation and to improve the processing time. The ABRMAD uses the lower pixel resolution of the significant bits instead of full resolution pixel values to estimate the motion vector (MV) by examining the pixels Ina block. Simulation results show that the 4-bit ABRMAD has competitive mean square error (MSE)results and a half less hardware complexity than the MAD criterion, It has also better characteristics in terms of both MSE performance and hardware complexity than the Minimax criterion and has better MSE performance than the difference pixel counting(DPC), binary block-matching with edge-map(BBME), and bit-plane matching(BPM) with the same number of bits.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.8C
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• pp.1125-1132
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• 2004

In this Paper, we Propose an effective boundary matching based error detection algorithm using causal neighbor blocks to improve video quality degraded from channel error in block-coded video. The proposed algorithm first calculates boundary mismatch powers between a current block and each of its causal neighbor blocks. It then decides that a current block should be normal if all the mismatch powers are less than an adaptive threshold, which is adaptively determined using the statistics of the two adjacent blocks. In some experiments under the environment of 16bi1s burst error at bit error rates (BERs) of 10$^{-3}$ -10$^{-4}$ , it is shown that the proposed algorithm yields the improvements of maximum 20% in error detection rate and of maximum 3.5㏈ in PSNR of concealed kames, compared with Zeng's error detection algorithm.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2008.11a
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• pp.23-24
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• 2008

• The Korean Journal of Applied Statistics
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• v.15 no.2
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• pp.405-414
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• 2002

We consider the problem of estimating the error variance of in a two-way mixed-effects ANOVA model using noninformative priors. First, we derive Jeffreys' prior, a reference prior, and matching priors. We then provide marginal posterior distributions under those noninformative priors. Finally, we provide graphs of marginal posterior densities of the error variance and credible intervals for the error variance in two real data set and compare these credible intervals.

• Progress in Medical Physics
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• v.14 no.3
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• pp.189-195
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• 2003

The comparative analysis of a portal image and a simulation image is a very important process in radiotherapy for verifying the accuracy of an actual treatment field. In this study, we applied a chamfer-matching algorithm to compare a portal image with a simulation image and verified the accuracy of the algorithm to analyze the field matching error in the portal image. We also developed an analysis program that could analyze the two images more effectively with a chamfer-matching method and demonstrated its efficacy through a feasibility study. With virtual portal images, the accuracy of the analysis algorithm were acceptable considering the average error of shift (0.64 mm), rotation (0.32$^{\circ}$), and scale (1.61%). When the portal images of a head and neck phantom were analyzed, the accuracy and suitability of the developed analysis program was proven considering the acceptable average error of shift (1.55 mm), rotation (0.80$^{\circ}$), and scale (1.72%). We verified the applicability of a chamfer-matching algorithm to the comparative analysis of a portal image with a simulation image. The analysis program developed in this study was a practical tool to calculate the quantitative error of the treatment field in a portal image.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.2
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• pp.79-84
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• 2019

This paper compare the performance of CM-MMA (Constellation Matching-MMA) and RMMA (Region-based MMA) blind equalization algorithm for improve the QoS by minimizing the intersymbol interference that is occurred in nonlinear communication channel when transmitting the QAM signal. In the tap coefficient update for adaptive, CM-MMA use the error of nonconstant modulus signal adding the current MMA cost fuction and constellation matching error terms of sinusoidal power function, and the RMMA use the error by transfoms the nonconstant modulus signal of equalizer output constellation to 4-QAM constant modulus signal. They has different equalization performance by these error signal, it were compared in this paper by simulation, and performance index such as output signal constellation of equalizer, residual isi, maximum distortion, SER curves are applied for this. As a result of computer simulation, the RMMA has more better performance in the every performance index, convergence speed, residual value, noise robustness compared to CM-MMA.

• Journal of KIISE:Software and Applications
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• v.32 no.10
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• pp.949-955
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• 2005

In this Paper, we propose fast block matching algorithm by dividing complex areas based on complexity order of reference block and square sub-block to reduce an amount of computation of full starch(FS) algorithm for fast motion estimation, while keeping the same prediction quality compared with the full search algorithm. By using the fact that matching error is proportional to the gradient of reference block, we reduced unnecessary computations with square sub-block adaptive matching scan based image complexity instead of conventional sequential matching scan and row/column based matching scan. Our algorithm reduces about $30\%$ of computations for block matching error compared with the conventional partial distortion elimination(PDE) algorithm without any prediction quality, and our algorithm will be useful in real-time video coding applications using MPEG-4 AVC or MPEG-2.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.5C
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• pp.683-691
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• 2004

To transmit MPEG-2 video on an errorneous channel, a number of error control techniques are needed. Especially, error concealment techniques which can be implemented on receivers independent of transmitters are essential to obtain good video quality. In this paper, prediction of motion vector and an adaptive boundary matching algorithm are presented for temporal error concealment. Before the complex BMA, we perform error concealment by a motion vector prediction using neighboring motion vectors. If the candidate of error concealment is not satisfied, search range and reliable boundary pixels are selected by the temporal activity or motion vectors and a damaged macroblock is concealed by applying an adaptive BMA. This error concealment technique reduces the complexity and maintains a PSNR gain of 0.3∼0.7㏈ compared to conventional BMA.

• Journal of Information Processing Systems
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• v.13 no.2
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• pp.256-267
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• 2017

An active research area in computer vision, stereo matching is aimed at obtaining three-dimensional (3D) information from a stereo image pair captured by a stereo camera. To extract accurate 3D information, a number of studies have examined stereo matching algorithms that employ adaptive support weight. Among them, the adaptive census transform (ACT) algorithm has yielded a relatively strong matching capability. The drawbacks of the ACT, however, are that it produces low matching accuracy at the border of an object and is vulnerable to noise. To mitigate these drawbacks, this paper proposes and analyzes the features of an improved stereo matching algorithm that not only enhances matching accuracy but also is also robust to noise. The proposed algorithm, based on the ACT, adopts the truncated absolute difference and the multiple sparse windows method. The experimental results show that compared to the ACT, the proposed algorithm reduces the average error rate of depth maps on Middlebury dataset images by as much as 2% and that is has a strong robustness to noise.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2001.04a
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• pp.170-173
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• 2001

To apply stereo vision system to obstacle recognition system of AGV, we constructed algorithm of stereo matching and distance measuring with stereo image for positioning of object in area. And using this system, we look into the error between real position and measured position, and studied relationship of compensation.