• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권1호
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• pp.343-364
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• 2021

In the 5G era, the communication networks tend to be ultra-densified, which will improve the accuracy of indoor positioning and further improve the quality of positioning service. In this study, we propose an indoor three-dimensional (3D) dynamic reconstruction fingerprint matching algorithm (DSR-FP) in a 5G ultra-dense network. The first step of the algorithm is to construct a local fingerprint matrix having low-rank characteristics using partial fingerprint data, and then reconstruct the local matrix as a complete fingerprint library using the FPCA reconstruction algorithm. In the second step of the algorithm, a dynamic base station matching strategy is used to screen out the best quality service base stations and multiple sub-optimal service base stations. Then, the fingerprints of the other base station numbers are eliminated from the fingerprint database to simplify the fingerprint database. Finally, the 3D estimated coordinates of the point to be located are obtained through the K-nearest neighbor matching algorithm. The analysis of the simulation results demonstrates that the average relative error between the reconstructed fingerprint database by the DSR-FP algorithm and the original fingerprint database is 1.21%, indicating that the accuracy of the reconstruction fingerprint database is high, and the influence of the location error can be ignored. The positioning error of the DSR-FP algorithm is less than 0.31 m. Furthermore, at the same signal-to-noise ratio, the positioning error of the DSR-FP algorithm is lesser than that of the traditional fingerprint matching algorithm, while its positioning accuracy is higher.

• 한국통신학회논문지
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• 제32권4C호
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• pp.396-400
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• 2007

본 논문은 고속 PDE 알고리즘을 제안한다. 기존 PDE 알고리즘이 부분 정합오차를 이용해 후보블록의 나머지 정합 과정을 생략할 수 없을 때 제안된 알고리즘은 계산된 부분 정합오차로부터 예측된 블록 정합오차를 이용해 다시 한번 나머지 정합 과정을 생략하는 것을 평가한다. 예측된 블록 정합오차는 부분 정합오차보다 항상 크므로 제안된 알고리즘은 기존 PDE보다 일찍 불가능한 후보 블록을 제거할 수 있다. 모의 실험의 결과들은 제안된 알고리즘이 기존 PDE 정도의 화질을 유지하면서 계산량을 크게 줄여주는 것을 보여준다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2003년도 학술회의 논문집 정보 및 제어부문 B
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• pp.532-535
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• 2003

In this paper, we propose a new algorithm that can enhance the speed of template matching of hand vascular pattern person verification or recognition system. Various template matching algorithms have advantages in the matching accuracy, but most of the algorithms suffer from computational burden. To reduce the computational amount, with accuracy maintained, we propose following template matching scenario as follows. firstly, original hand vascular image is re-sampled in order to reduce spatial resolution. Secondly, reconstructed image is projected to vertical and horizontal direction, being converted to two one dimensional (1D) data. Thirdly, converted data is used to estimate spatial discrepancy between stored template image and target image. Finally, matching begins from where the estimated order is highest, and finishes when matching decision function is computed to be over certain threshold. We've applied the proposed algorithm to hand vascular pattern identification application for biometrics, and observed dramatic matching speed enhancement. This paper presents detailed explanation of the proposed algorithm and evaluation results.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 1999년도 하계종합학술대회 논문집
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• pp.474-478
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• 1999

Genetic algorithm is an efficient search method using principles of natural selection and population genetics. In conventional genetic algorithms, however, the size of gene pool should be increased to insure a convergency. Therefore, many memory spaces and much computation time were needed. Also, since child chromosomes were generated by chromosome crossover and gene mutation, the algorithms have a complex structure. Thus, in this paper, a compact stereo matching algorithm using a population-based incremental teaming based on probability vector is proposed to reduce these problems. The PBIL method is modified for matching environment. Since the Proposed algorithm uses a probability vector and eliminates gene pool, chromosome crossover, and gene mutation, the matching algorithm is simple and the computation load is considerably reduced. Even if the characteristics of images are changed, stable outputs are obtained without the modification of the matching algorithm.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 1999년도 추계종합학술대회 논문집
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• pp.1097-1100
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• 1999

Due to the significant computation of full search in motion estimation, extensive research in fast motion estimation algorithms has been carried out. However, most of the algorithms have the degradation in predicted images compared with the full search algorithm. To reduce an amount of significant computation while keeping the same prediction quality of the full search, we propose a fast block-matching algorithm based on gradient magnitude of reference block without any degradation of predicted image. By using Taylor series expansion, we show that the block matching errors between reference block and candidate block are proportional to the gradient magnitude of matching block. With the derived result, we propose fast full search algorithm with adaptively determined scan direction in the block matching. Experimentally, our proposed algorithm is very efficient in terms of computational speedup and has the smallest computation among all the conventional full search algorithms. Therefore, our algorithm is useful in VLSI implementation of video encoder requiring real-time application.

• 한국멀티미디어학회논문지
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• 제10권11호
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• pp.1439-1445
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• 2007

본 논문에서는 기존의 PDE방법의 계산량을 줄이고 동시에 동일한 예측화질을 얻기 위해, 초기 매칭블록의 서브블록별 SAD값의 비교를 통한 고속 움직임 예측 알고리즘을 제안한다. 제안한 방법은 최초 매칭 블록의 서브블록별 매칭 에러의 복잡도의 비교를 통해 후보블록들의 매칭순서를 변경하여 불필요한 계산량을 줄이는 방법을 제안한다. 제안한 알고리즘은 예측 화질의 저하 없이 기존의 PDE(partial distortion elimination) 알고리즘을 이용한 전영역 탐색 방법에 비해 45%의 계산량을 줄였으며, MPEG-2 및 MPEG-4 AVC를 이용하는 비디오 압축 응용분야에 유용하게 사용될 수 있을 것이다.

• 한국통신학회논문지
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• 제29권7C호
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• pp.946-953
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• 2004

고속 탐색 및 기존의 이진 연산 움직임 추정 알고리즘은 연산량 및 처리시간을 대폭 줄일 수 있지만 전역 탐색 움직임 추정 알고리즘에 비하여 성능이 떨어지는 단점이 있다. 따라서 본 논문에서는 하드웨어 구현이 용이하고 움직임 추정을 고속으로 수행 할 수 있는 새로운 BC-ABBM 알고리즘을 제안하였다. BC-ABBM 알고리즘은 움직임 추정시 필요한 연산을 이진 연산으로만 수행하면서 전역 탐색에 근접한 성능을 나타낸다. BC-ABBM 알고리즘의 움직임 추정 성능은 QCIF와 CIF 포맷의 100프레임 영상을 이용하여 분석하였다. BC-ABBM 알고리즘의 PSNR 성능은 전역 탐색 알고리즘보다 약 0.04dB 정도 떨어지지만, 고속 탐색 알고리즘 및 기존의 이진 연산 알고리즘보다는 약 0.6∼l.4dB 정도 우수함을 모의실험을 통해 확인하였다.

• 전자공학회논문지B
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• 제31B권8호
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• pp.11-19
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• 1994

The matching probability P(ο/$\lambda$), of the signal sequence(ο) observed for a finite time interval with a HMM (Hidden Markov Model $\lambda$) indicates the probability that signal comes from the given model. By utilizing the fact that the probability represents matching score of the observed signal with the model we can recognize an unknown signal pattern by comparing the magnitudes of the matching probabilities with respect to the known models. Because the algorithm however uses floating point variables during the computing process hardware implementation of the algorithm requires floating point units. This paper proposes an integer algorithm which uses positive integer numbers rather than float point ones to compute the matching probability so that we can economically realize the algorithm into hardware. The algorithm makes the model parameters integer numbers by multiplying positive constants and prevents from divergence of data through the normalization of variables at each step. The final equation of matching probability is composed of constant terms and a variable term which contains logarithm operations. A scheme to make the log conversion table smaller is also presented. To analyze the qualitive characteristics of the proposed algorithm we attatch simulation result performed on two groups of 10 hypothetic models respectively and inspect the statistical properties with repect to the model order the magnitude of scaling constants and the effect of the observation length.

• 융합신호처리학회논문지
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• 제5권2호
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• pp.126-131
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• 2004

전역 탐색 알고리즘은 탐색영역이 증가하는 경우 연산량이 급증하게 되어 처리 시간이 길어지고 하드웨어 복잡도가 증가한다. 고속 탐색 알고리즘 및 기존의 이진 연산 알고리즘은 연산량 및 처리시간을 대폭 줄일 수 있지만 전역 탐색 알고리즘에 비하여 성능이 떨어지는 단점이 있다. 따라서 본 논문에서는 하드웨어 구현이 용이하고 움직임 추정을 고속으로 수행 할 수 있는 새로운 BCBM(Bit Converted Boolean Matching)알고리즘을 제안한다. BCBM 알고리즘은 움직임 추정 시 필요한 연산을 이진 연산으로만 수행하면서 전역 탐색에 근접한 성능을 나타낸다. 움직임 추정 성능은 CIF 포맷의 영상 100프레임을 이용하여 분석하였다. BCBM 알고리즘의 PSNR 성능은 전역 탐색 알고리즘보다 약 0.08㏈ 떨어지지만, 고속 탐색 알고리즘 및 기존의 이진 연산 알고리즘 보다 0.96∼2.02㏈ 정도 우수함을 실험을 통해 확인하였다.

• 대한임베디드공학회논문지
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• 제16권5호
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• pp.179-186
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• 2021

For stereo matching based on deep learning, the design of network structure is crucial to the calculation of matching cost, and the time-consuming problem of convolutional neural network in image processing also needs to be solved urgently. In this paper, a method of stereo matching using sparse loss volume in parallax dimension is proposed. A sparse 3D loss volume is constructed by using a wide step length translation of the right view feature map, which reduces the video memory and computing resources required by the 3D convolution module by several times. In order to improve the accuracy of the algorithm, the nonlinear up-sampling of the matching loss in the parallax dimension is carried out by using the method of multi-category output, and the training model is combined with two kinds of loss functions. Compared with the benchmark algorithm, the proposed algorithm not only improves the accuracy but also shortens the running time by about 30%.