• Journal of Korea Multimedia Society
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• v.21 no.3
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• pp.342-347
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• 2018

We proposed a fast detection of copy-move image forgery using four step search algorithm in the spatial domain. In the four-step search algorithm, the search area is 21 (-10 ~ +10), and the number of pixels to be scanned is 33. Our algorithm reduced computational complexity more than conventional copy move image forgery methods. The proposed method reduced 92.34 % of computational complexity compare to exhaustive search algorithm.

• Journal of Communications and Networks
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• v.11 no.5
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• pp.473-479
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• 2009

Conventional frequency domain equalization (FDE) schemes were originally devised for quasi-static channels. Thus, such equalization schemes could suffer from significant performance degradation in fast-fading channels. This paper proposes a frequency domain equalization algorithm to mitigate the effect of fast time-varying fading. First, a mathematical expression is derived to quantify the total interference resulting from the time variation of the channel. Then, the proposed approach attempts to eliminate the effect of time-variations of the channel. This cancellation allows efficient use of the classical FDE structures in fast time-varying fading environments, although they are built upon the quasi-static channel model. Simulation results of bit-error-rate performance are provided to demonstrate the effectiveness of the proposed algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1379-1382
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• 1997

We introduce a fast implementation of the adaptive transversal filter which uses least-mean-square(LMS) algorithm. The fast Hadamard transform(FHT) is used for the implementation of the filter. By using the proposed filter we can get the significant time reduction in computatioin over the conventional time domain LMS filter at the cost of a little performance. By computer simulation, we show the comparison of the propsed Hadamard-domain filter and the time domain filter in the view of multiplication time, mean-square error and robustness for noise.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.9
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• pp.77-83
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• 1997

We present a fast adaptive block matching algorithm using variable search area and subsampling to estimate motion vector more exactly. In the presented method, the block is classified into one of three motion categories: zero motion vector block, medium-motion bolck or high-motion block according to mean absolute difference of the block. By the simulation, the computation amount of the presented methoe comparable to three step search algorithm and new three step search algorithm. In the fast image sequence, the PSNR of our algorithm increased more than TSS and NTSS, because our algorithm estimated motion vector more accurately.

• Journal of information and communication convergence engineering
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• v.13 no.2
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• pp.113-122
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• 2015

Feature subset selection is as a pre-processing step in learning algorithms. In this paper, we propose an efficient algorithm, ModifiedFAST, for feature subset selection. This algorithm is suitable for text datasets, and uses the concept of information gain to remove irrelevant and redundant features. A new optimal value of the threshold for symmetric uncertainty, used to identify relevant features, is found. The thresholds used by previous feature selection algorithms such as FAST, Relief, and CFS were not optimal. It has been proven that the threshold value greatly affects the percentage of selected features and the classification accuracy. A new performance unified metric that combines accuracy and the number of features selected has been proposed and applied in the proposed algorithm. It was experimentally shown that the percentage of selected features obtained by the proposed algorithm was lower than that obtained using existing algorithms in most of the datasets. The effectiveness of our algorithm on the optimal threshold was statistically validated with other algorithms.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.1A
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• pp.43-50
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• 2012

The use of an error-correcting code is essential in digital communication systems where the channel is noisy. Unless a receiver has accurate channel coding parameters, it becomes difficult to decode the digitized encoding bits correctly. In this paper, estimation algorithm for RM(Reed-Muller) codes using FHT (Fast Hadamard algorithm) is proposed. The proposed algorithm estimates the channel coding parameters of RM codes and then decodes the codes using the characteristic of FHT. And we also verify the algorithm by performing intensive computer simulation in additive white gaussian noise (AWGN) channel.

• Proceedings of the IEEK Conference
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• 2000.11d
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• pp.183-186
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• 2000

Motion estimation technique has been used to increase video compression rates in motion video applications. One of the important algorithms to implement the motion estimation technique is search algorithm. Among many search algorithms, the H.263 adopted the Nearest Neighbors algorithm for fast search. In this paper, motion estimation block for the Nearest Neighbors algorithm is designed on FPGA and coded using VHDL and simulated under the Xilinx foundation environments. In the experiment results, we verified that the algorithm was properly designed and performed on the Xilinx FPGA(XCV300Q240)

• Korean Journal of Mathematics
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• v.19 no.3
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• pp.243-253
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• 2011

We would like to propose a Cooley-Tukey modied algorithm in fast Fourier transform(FFT). Of course, this is a kind of Cooley-Tukey twiddle factor algorithm and we focused on the choice of integers. The proposed algorithm is better than existing ones in speeding up the calculation of the FFT.

• Proceedings of the IEEK Conference
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• 2002.06d
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• pp.179-182
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• 2002

In this paper, we propose a wavelet based adaptive algorithm which improves the convergence speed and reduces computational complexity using the fast running FIR filtering efficiently We compared the performance of the proposed algorithm with time and frequence domain adaptive algorithm using computer simulation of adaptive noise canceler based on synthesis speech. As the result, the proposed algorithm is suitable for adaptive signal processing area using speech or acoustic field.

• ETRI Journal
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• v.31 no.6
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• pp.784-794
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• 2009

We present a full HD (1080p) H.264/AVC High Profile hardware encoder based on fast motion estimation (ME). Most processing cycles are occupied with ME and use external memory access to fetch samples, which degrades the performance of the encoder. A novel approach to fast ME which uses shared multibank memory can solve these problems. The proposed pixel subsampling ME algorithm is suitable for fast motion vector searches for high-quality resolution images. The proposed algorithm achieves an 87.5% reduction of computational complexity compared with the full search algorithm in the JM reference software, while sustaining the video quality without any conspicuous PSNR loss. The usage amount of shared multibank memory between the coarse ME and fine ME blocks is 93.6%, which saves external memory access cycles and speeds up ME. It is feasible to perform the algorithm at a 270 MHz clock speed for 30 frame/s real-time full HD encoding. Its total gate count is 872k, and internal SRAM size is 41.8 kB.