• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권1호
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• pp.53-76
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• 2020

The synchronous phasor measurement algorithm is the core content of the phasor measurement unit. This manuscript proposes a dynamic synchronous phasor measurement algorithm based on compressed sensing theory. First, a dynamic signal model based on the Taylor series was established. The dynamic power signal was preprocessed using a least mean square error adaptive filter to eliminate interference from noise and harmonic components. A Chirplet overcomplete dictionary was then designed to realize a sparse representation. A reduction of the signal dimension was next achieved using a Gaussian observation matrix. Finally, the improved orthogonal matching pursuit algorithm was used to realize the sparse decomposition of the signal to be detected, the amplitude and phase of the original power signal were estimated according to the best matching atomic parameters, and the total vector error index was used for an error evaluation. Chroma 61511 was used for the output of various signals, the simulation results of which show that the proposed algorithm cannot only effectively filter out interference signals, it also achieves a better dynamic response performance and stability compared with a traditional DFT algorithm and the improved DFT synchronous phasor measurement algorithm, and the phasor measurement accuracy of the signal is greatly improved. In practical applications, the hardware costs of the system can be further reduced.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2002년도 Proceedings of International Symposium on Remote Sensing
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• pp.766-771
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• 2002

Automatic change detection based on the vector-to-raster comparison is hard especially in high-resolution image. This paper proposes a method to designate roads in high-resolution image in sequential manner using the information from vector map in which Hough transform is used for reliability. By its linearity, the road of urban areas in a vector map can be easily parameterized. Following some pre-processing to remove undesirable objects, we obtain the edge map of raster image. Then the edge map is transformed to a parameter space to find the selected road from vector map. The comparison is done in the parameter space to find the best matching. The set of parameters of a road from vector map is treated as the constraints to do matching. After designating the road, we may overlay it on the raster image for precise monitoring. The results can be used for detection of changes in road object in a semi-automatic fashion.

• Journal of Electrical Engineering and Technology
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• 제6권6호
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• pp.776-785
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• 2011

Since the Internet-based real-time Global Positioning System(GPS) synchronized widearea power system frequency monitoring network (FNET) was proposed in 2001, it has been monitoring the power system frequency in interconnected United States power systems and numerous interesting behaviors have been observed, including frequency excursion propagation. We address the consistency of a frequency excursion detection order of frequency disturbance recorders in FNET in relation to the same generation trip, as well as the ability to recreate by power systems dynamic simulation. We also propose a new method, as an application of FNET measurement, to locate a tripped generator using power systems dynamic simulation and wide-area frequency measurement. The simulation database of all the possible trips of generators in the interconnected power systems is created using the off-line power systems dynamic simulation. When FNET detects a sudden drop in the monitoring frequency, which is most likely due to a generation trip in power systems, the proposed algorithm locates a tripped generator by finding the best matching case of the measured frequency excursion in the simulation database in terms of the frequency drop detection order and the time of monitoring points.

• 한국정보과학회논문지:컴퓨팅의 실제 및 레터
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• 제16권5호
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• pp.546-550
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• 2010

본 논문에서는 모바일 폰에서 오프라인 필기체 과분할 인식의 후처리 방법에 관하여 논하였다. 제안된 방법은 조합 행렬 생성, 문자 조합 필터링, 문자 유사도 측정으로 구성된다. 조합 행렬 생성 과정은 각각의 조각의 인식 결과로부터 생성가능한 모든 조합 행렬을 계산하는 부분이며 조합 행렬을 그래프로 구성하게 된다. 문자 조합 필터링 과정은 그래프의 노드들과 단어 사전을 비교하여 불필요한 노드를 삭제하는 과정이며 문자 유사도 측정과정은 단어 사전의 각각의 단어들과 Levenshtein 거리(distance)를 계산하여 최적의 후처리 결과를 추출하게 된다. 제안된 방법의 인식률은 85.8%의 정확도를 보였다.

• 한국멀티미디어학회논문지
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• 제16권10호
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• pp.1156-1162
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• 2013

Face verification has been widely studied during the past two decades. One of the challenges is the rising concern about the security and privacy of the template database. In this paper, we propose a secure face verification system which generates a unique secure cryptographic key from a face template. The face images are processed to produce face templates or codes to be utilized for the encryption and decryption tasks. The result identity data is encrypted using Advanced Encryption Standard (AES). Distance metric naming hamming distance and Euclidean distance are used for template matching identification process, where template matching is a process used in pattern recognition. The proposed system is tested on the ORL, YALEs, and PKNU face databases, which contain 360, 135, and 54 training images respectively. We employ Principle Component Analysis (PCA) to determine the most discriminating features among face images. The experimental results showed that the proposed distance measure was one the promising best measures with respect to different characteristics of the biometric systems. Using the proposed method we needed to extract fewer images in order to achieve 100% cumulative recognition than using any other tested distance measure.

• 대한기계학회논문집A
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• 제23권11호
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• pp.1929-1939
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• 1999

This paper presents a neural network approach, which was named PRONET, to 3D object recognition and pose calculation. 3D objects are represented using a set of centroidal profile patterns that describe the boundary of the 2D views taken from evenly distributed view points. PRONET consists of the training stage and the execution stage. In the training stage, a three-layer feed-forward neural network is trained with the centroidal profile patterns using an error back-propagation method. In the execution stage, by matching a centroidal profile pattern of the given image with the best fitting centroidal profile pattern using the neural network, the identity and approximate orientation of the real object, such as a workpiece in arbitrary pose, are obtained. In the matching procedure, line-to-line correspondence between image features and 3D CAD features are also obtained. An iterative model posing method then calculates the more exact pose of the object based on initial orientation and correspondence.

• 인지과학
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• 제8권4호
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• pp.1-10
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• 1997

본 연구는 우리나라 사람들이 일상생활에서 사용하는 기본 색이름이 몇가지이며 그 색이름에 대응하는 색상이 무엇인지를 알아보기 위해서 수행되었다. 먼저, 우리말 색이름에 관한 전국규모의 표본조사를 실시하였다. 그 결과 한국인 기본색이름목록과 Berlin과 Kay(1969)이론에 근거하여 기본색이름의 보편성을 살펴보았다. 또한 기본색이름에 대응하는 색상연구를 통하여 기본 색이름영역과 그 중심색상을 결정하여 2차원 색채공간상에 나타내었다. 이 연구는 우리나라 사람들의 색채개념의 심리학적 및 언어학적 기초자료를 제공하는 것 뿐 아니라 우리말 색이름의 내적구조를 밝혀주는 연구로서의 의의를 갖는다.

• 한국통신학회논문지
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• 제28권1B호
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• pp.27-32
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• 2003

본 논문에서는 고속 네트웍 기반의 분산 병렬 시스템에서 다양한 내재 병렬 형태를 갖는 프로그램의 효과적인 수행을 위한 유전자 알고리즘 기반의 태스크 스케쥴링 방법(Genetic Algorithm based Task Scheduling GATS)을 제안한다. 분산병렬 시스템은 고속 네트웍을 통해 연결되어진 다수의 범용, 병렬, 벡터 컴퓨터들로 구성되어진다. 분산병렬 처리의 목적은 다양한 내재 병렬 형태를 갖는 연산 집약적인 문제들을 다수의 고성능 및 병렬 컴퓨터들의 각기 다른 능력을 최대한 이용하여 해결함에 있다 분산병렬 시스템에서 스케쥴링을 통하여 더 많은 속도향상을 얻기 위해서는 시스템간의 부하 균형보다는 태스크와 병렬 컴퓨터간의 병렬특성의 일치가 주의 깊게 다루어져야 하며 태스크의 이동으로 인한 통신 오버헤드가 최소화되어야 한다 본 논문에서는 유전자 알고리즘의 동작이 병렬 특성을 감안하여 이루어질 수 있도록 초기화 방법과 지식 기반의 mutation 방법을 제안한다.

• 한국지능시스템학회논문지
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• 제23권3호
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• pp.275-279
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• 2013

최근 멀티미디어 정보가 보편화됨에 따라 인터넷에서 이미지를 기반으로 정보를 검색하려는 다양한 시도가 진행되고 있다. 그러나 이미지에는 다양한 패턴이 포함되어 있기 때문에 정확하게 원하는 이미지를 찾는 것은 아직 어려움이 많다. 본 논문에서는 인터넷 쇼핑몰의 상품검색을 효율적으로 할 수 있는 이미지 기반 검색 시스템을 제안한다. 제안된 검색 방법은 SIFT(Scale Invariant Feature Transform) 알고리즘을 이용하여 이미지 검색을 위한 특징을 추출하고, PCA-SIFT를 이용하여 여러 차원에서 키포인트의 매칭을 반복하여 누적 후 사용자가 원하는 상품을 찾아준다. 제안된 방법의 효율성을 검증하기 위해, 다양한 패턴의 상품 이미지를 이용하여 기존 SIFT, PCA-SIFT 방법과 제안된 방법을 비교한 결과, 상표가 포함되지 않은 이미지의 경우 제안방법이 가장 높은 변별력을 보였으며, 효과적인 이미지 검색의 가능성을 보였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권1호
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• pp.131-147
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• 2020

RFID (Radio Frequency Identification) identifies a specific object by radio signals. As the tag provides a unique ID for the purpose of identification, RFID technology effectively solves the ambiguity and occlusion problem that challenges the laser or camera-based approach. This paper proposes an approach to track a moving object based on the integration of RFID and laser ranging information using a particle filter. To be precise, we split laser scan points into different clusters which contain the potential moving objects and calculate the radial velocity of each cluster. The velocity information is compared with the radial velocity estimated from RFID phase difference. In order to achieve the positioning of the moving object, we select a number of K best matching clusters to update the weights of the particle filter. To further improve the positioning accuracy, we incorporate RFID signal strength information into the particle filter using a pre-trained sensor model. The proposed approach is tested on a SCITOS service robot under different types of tags and various human velocities. The results show that fusion of signal strength and laser ranging information has significantly increased the positioning accuracy when compared to radial velocity matching-based or signal strength-based approaches. The proposed approach provides a solution for human machine interaction and object tracking, which has potential applications in many fields for example supermarkets, libraries, shopping malls, and exhibitions.