• 전자공학회논문지
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• 제54권5호
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• pp.42-47
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• 2017

본 논문에서는 디지털 영상의 배포에서, 위 변조에 사용되는 미디언 필터링 (Median Filtering : MF)을 분류하는 포렌식 검출 알고리즘을 제안한다. 이러한 문제를 해결하기 위한 특징벡터는 영상의 에지 검출량 정보 32, 64, 128에 대한 허프변환(Hough Transform)에 의하여, 각 허프라인 (Hough Line)의 양끝 좌표값과 Angle-Distance 좌표상의 허프픽크치 (Hough Peaks)를 조합하여 42-Dim.으로 구성하였다. 변조된 영상들 중에서 미디언 필터링을 분류하는 검출기는 SVM (Support Vector Machine)에서 특징벡터를 학습하여 구현되었다. 제안된 미디언 필터링 검출 알고리즘은 특징벡터의 길이가 10-Dim.의 MFR (Median Filtering Residual) 스킴 및 686-Dim.의 SPAM (Subtractive Pixel Adjacency Matrix) 스킴과 비교하여 원영상, 평균필터링 ($3{\times}3$), JPEG (QF=90, 70) 압축, 가우시안 필터링 ($3{\times}3$, $5{\times}5$) 영상 모두에서 미디언 필터링의 포렌식 분류율이 99% 이상의 성능을 확인하였다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2001년도 추계학술대회 논문집 전력기술부문
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• pp.118-120
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• 2001

This paper presents a distance relaying algorithm based on the Discrete Fourier Transform(DFT) for elimination of DC-Offset. When the DFT is applied to current signal. the real and imaginary parts of fundamental component consist of fundamental component itself and DC-Offset. The DC-Offset is calculated by four consecutive values of the imaginary components, so that the fundamental component can be accurately estimated. Performance evaluation is presented for A-phase ground faults on 154kV 80km overhead transmission line. The proposed algorithm is inspected by software simulation and hardware simulation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권7호
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• pp.2914-2935
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• 2016

With the increasing popularization of cloud computing, how to reduce physical energy consumption and increase resource utilization while maintaining system performance has become a research hotspot of virtual machine deployment in cloud platform. Although some related researches have been reported to solve this problem, most of them used the traditional heuristic algorithm based on greedy algorithm and only considered effect of single-dimensional resource (CPU or Memory) on energy consumption. With considerations to multi-dimensional resource utilization, this paper analyzed impact of multi-dimensional resources on energy consumption of cloud computation. A multi-dimensional resource constraint that could maintain normal system operation was proposed. Later, a novel virtual machine deployment method (NVMDM) based on improved particle swarm optimization (IPSO) and Euclidean distance was put forward. It deals with problems like how to generate the initial particle swarm through the improved first-fit algorithm based on resource constraint (IFFABRC), how to define measure standard of credibility of individual and global optimal solutions of particles by combining with Bayesian transform, and how to define fitness function of particle swarm according to the multi-dimensional resource constraint relationship. The proposed NVMDM was proved superior to existing heuristic algorithm in developing performances of physical machines. It could improve utilization of CPU, memory, disk and bandwidth effectively and control task execution time of users within the range of resource constraint.

• 반도체디스플레이기술학회지
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• 제15권3호
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• pp.24-29
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• 2016

One of the main applications of digital image processing is the estimation of the number of certain types of objects (cells, seeds, peoples etc.) in an image. Difficulties of these counting problems depends on various factors including shape and size variation, degree of object clustering, contrast between object and background, object texture and its variation, and so on. In this paper, a new automatic colony counting algorithm is proposed. We focused on the two applications: counting the bacteria colonies on the agar plate and estimating the number of seeds from images captured by smartphone camera. To overcome the shape and size variations of the colonies, we adopted the distance transformation and peak detection approach. To estimate the reference size of the colony robustly, we also used k-means clustering algorithm. Experimental results show that our method works well in real world applications.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 하계종합학술대회 논문집(5)
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• pp.31-34
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• 2000

In this paper, we design an optimal path for multiple mobile robots. For this purpose, we propose a new method of path planning for multiple mobile robots in dynamic environment. First, every mobile robot searches a global path using a distance transform algorithm. Then we put subgoals at crooked path points and optimize them. And finally to obtain an optimal on-line local path, ever)r mobile robot searches a new path with static and dynamic obstacle avoidance.

• Journal of information and communication convergence engineering
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• 제3권4호
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• pp.201-204
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• 2005

Twofish is a 128-bit block cipher that accepts a variable-length key up to 256 bits. The cipher is a 16­round Feistel network with a bijective F function made up of four key-dependent 8-by-8-bit S-boxes, a fixed 4­by-4 maximum distance separable matrix over Galois Field$(GF (2^8)$, a pseudo-Hadamard transform, bitwise rotations, and a carefully designed key schedule. In this paper, the Twofish is modeled in VHDL and simulated. Hardware implementation gives much better performance than software-based approaches.

• 품질경영학회지
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• 제36권2호
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• pp.36-44
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• 2008

In this paper a novel feature extraction and selection is carried out in order to improve the discriminating capability between healthy and damaged structure using vibration signals. Although many feature extraction and selection algorithms have been proposed for vibration signals, most proposed approaches don't consider the discriminating ability of features since they are usually in unsupervised manner. We proposed a novel feature extraction and selection algorithm selecting few wavelet coefficients with higher class discriminating capability for damage detection and class visualization. We applied three class separability measures to evaluate the features, i.e. T test statistics, divergence, and Bhattacharyya distance. Experiments with vibration signals from truss structure demonstrate that class separabilities are significantly enhanced using our proposed algorithm compared to other two algorithms with original time-based features and Fourier-based ones.

• 제어로봇시스템학회논문지
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• 제13권5호
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• pp.493-498
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• 2007

In this paper, a 2-dimensional accurate edge-based matching algorithm using subpixel edges is proposed that combines the Generalized Hough Transform(GHT) and the Chamfer matching to complement the weakness of either method. First, the GHT is used to find the approximate object positions and orientations, and then these positions and orientations are used as starting parameter values to find more accurate position and orientation using the Chamfer matching with distance interpolation. Finally, matching accuracy is further refined by using a subpixel algorithm. Testing results demonstrate that greater matching accuracy is achieved using subpixel edges rather than edge pixels.

• 융합신호처리학회논문지
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• 제7권4호
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• pp.178-183
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• 2006

As a lot of researches on the speech signal processing are performed due to the recent rapid development of the information-communication technology. the pitch period is used as an important element to various speech signal application fields such as the speech recognition. speaker identification. speech analysis. or speech synthesis. A variety of algorithms for the time and the frequency domains related with such pitch period detection have been suggested. One of the pitch detection algorithms for the time domain. AMDF (average magnitude difference function) uses distance between two valley points as the calculated pitch period. However, it has a problem that the algorithm becomes complex in selecting the valley points for the pitch period detection. Therefore, in this paper we proposed the modified AMDF(M-AMDF) algorithm which recognizes the entire minimum valley points as the pitch period of the speech signal by using the rotation transform of AMDF. In addition, a threshold is set to the beginning portion of speech so that it can be used as the selection criteria for the pitch period. Moreover the proposed algorithm is compared with the conventional ones by means of the simulation, and presents better properties than others.

• 전자공학회논문지CI
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• 제40권3호
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• pp.127-136
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• 2003

본 논문에서는 템플릿 변형과 Level-Set 이론을 사용하여 모델과 에지 기반의 객체 추적 방법을 제안한다. 제안된 방법은 배경의 변화, 객체 자체의 모양변화, 객체간의 겹침 등이 있는 경우에도 객체를 추적할 수 있다. 먼저, 객체 추적을 위해 템플릿과 목적 프레임간의 상호 영역 차이(Inter-region distance)와 에지 값으로 구성된 에너지 함수 PDEF(Potential Difference Energy Function)를 새롭게 정의한다. 이 함수는 객체 위치 및 경계 예측과 객체 모양 재결정 단계에서 사용된다. 객체 위치 및 경계 예측 단계에서는 객체의 변화가 어파인(affine) 변형을 따른다는 가정 하에 객체의 대략적인 모양 및 위치를 예측한다. 객체 모양 재결정 단계에서는 퍼텐셜 에너지 지도(Potential energy map)와 수정된 Level-Set 운동 함수를 사용하여 객체의 정확한 형태를 재결정한다. 실험결과에서 제안된 방법은 기존의 방법보다 배경의 변화가 큰경우, 객체 자체의 모양변화가 심한 경우, 객체간의 겹침이 있는 경우 등 다양한 상황이 포함된 동영상에서 정확하게 객체를 추적할 수 있음을 확인할 수 있다.