• Journal of Electrical Engineering and information Science
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• 제3권1호
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• pp.73-79
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• 1998

In this paper, a new traffic sign detection algorithm.. and a symbol recognition algorithm are proposed. For traffic sign detection, a dominant color transform is introduced, which serves as a tool of highlighting a dominant primary color, while discarding the other two primary colors. For symbol recognition, the curvilinear shape distribution on a circle centered on the centroid of symbol, called a circular pattern vector, is used as a spatial feature of symbol. The circular pattern vector is invariant to scaling, translation, and rotation. As simulation results, the effectiveness of traffic sign detection and recognition algorithms are confirmed, and it is shown that group of circular patter vectors based on concentric circles is more effective than circular pattern vector of a single circle for a given equivalent number of elements of vectors.

• Journal of Biosystems Engineering
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• 제19권4호
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• pp.380-396
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• 1994

A personal computer based color machine vision system with video camera and fluorescent lighting system was used to generate images of stationary tobacco leaves. Image processing algorithms were developed to extract both the geometric and the color features of tobacco leaves. Geometric features include area, perimeter, centroid, roundness and complex ratio. Color calibration scheme was developed to convert measured pixel values to the standard color unit using both statistics and artificial neural network algorithm. Improved back propagation algorithm showed less sum of square errors than multiple linear regression. Color features provide not only quality evaluation quantities but the accurate color measurement. Those quality features would be useful in grading tobacco automatically. This system would also be useful in measuring visual features of other agricultural products.

• 대한원격탐사학회지
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• 제18권5호
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• pp.273-280
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• 2002

This paper describes a mathematical model and its utilization algorithm for calculating the accurate target position on the ellipsoidal earth surface which corresponds to a range-azimuth coordinates of unprocessed synthetic aperture radar (SAR) images. A geometrical model which is a set of coordinate transformations is described. The side-looking directional angle (off-nadir angle) is determined in an iterative fashion by using the model and the accurate slant range which is calculated from the range sampling timing of the instrument. The algorithm can be applied not only for the geolocation of SAR images but also for the high quality SAR image generation by calculating accurate Doppler parameters.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제7권5호
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• pp.1166-1179
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• 2013

In wireless sensor network (WSN) environments, environmental noises are generated by, for example, small passing animals, crickets chirping or foliage blowing and will interfere target detection if the noises are higher than the sensor threshold value. For accurate tracking by acoustic WSNs, these environmental noises should be filtered out before initiating track. This paper presents the effect of environmental noises on target tracking and proposes a new algorithm for the noise mitigation in acoustic WSNs. We find that our noise mitigation algorithm works well even for targets with sensing range shorter than the sensor separation as well as with longer sensing ranges. It is also found that noise duration at each sensor affects the performance of the algorithm. A detection algorithm is also presented to account for the Doppler effect which is an important consideration for tracking higher-speed ground targets. For tracking, we use the weighted sensor position centroid to represent the target position measurement and use the Kalman filter (KF) for tracking.

• 정보관리학회지
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• 제21권4호
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• pp.173-185
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• 2004

정보통신의 기술이 발달하면서 정보의 양이 많아지고 사용자의 질의에 대한 검색 결과 리스트도 많이 추출되므로 빠르고 고품질의 문서 클러스터링 알고리즘이 중요한 역할을 하고 있다. 많은 논문들이 계층적 클러스터링 방법을 이용하여 좋은 성능을 보이지만 시간이 많이 소요된다. 반면 K-means 알고리즘은 시간 복잡도를 줄일 수 있는 방법이다. 본 논문에서는 계층적 클러스터링 시스템인 콘도르(Condor) 시스템에서 간단하고 고품질이며 효율적으로 정보 검색 할 수 있도록 구현하였다. 이 시스템은 K-Means Algorithm을 이용하였으며 클러스터 계층 깊이와 초기값을 조절하여 $88\%$의 정확율을 보였다.

• Journal of Computing Science and Engineering
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• 제9권2호
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• pp.39-50
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• 2015

Genetic algorithm (GA) and particle swarm optimization (PSO) are two excellent approaches to multimodal optimization problems. However, slow convergence or premature convergence readily occurs because of inappropriate and inflexible evolution. In this paper, a novel optimization algorithm with a flexible grid optimization (FGO) is suggested to provide adaptive trade-off between exploration and exploitation according to the specific objective function. Meanwhile, a uniform agents array with adaptive scale is distributed on the gird to speed up the calculation. In addition, a dominance centroid and a fitness center are proposed to efficiently determine the potential guides when the population size varies dynamically. Two types of subregion division strategies are designed to enhance evolutionary diversity and convergence, respectively. By examining the performance on four benchmark functions, FGO is found to be competitive with or even superior to several other popular algorithms in terms of both effectiveness and efficiency, tending to reach the global optimum earlier. Moreover, FGO is evaluated by applying it to a parameter decision in a least squares support vector machine (LS-SVM) to verify its practical competence.

• 대한원격탐사학회지
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• 제26권3호
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• pp.335-346
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• 2010

Recently, ESA (European Space Agency) has launched CryoSAT-2 for polar ice observations. CryoSAT-2 is equipped with a SIRAL (SAR/interferometric radar altimeter), which is a high spatial resolution radar altimeter. Conventional altimeters cannot measure a precise three-dimensional ground position because of the large footprint diameter, while SIRAL altimeter system accomplishes a precise three-dimensional ground positioning by means of interferometric synthetic aperture radar technique. In this study, we developed an efficient SIRAL SARIn mode processing technique to measure a precise three-dimensional ground position. We first simulated SIRAL SARIn RAW data for the ideal target by assuming the flat Earth and linear flight track, and second accessed the precision of three-dimensional geopositioning achieved by the proposed algorithm. The proposed algorithm consists of 1) azimuth processing that determines the squint angle from Doppler centroid, and 2) range processing that estimates the look angle from interferometric phase. In the ideal case, the precisions of look and squint angles achieved by the proposed algorithm were about -2.0 ${\mu}deg$ and 98.0 ${\mu}deg$, respectively, and the three-dimensional geopositioning accuracy was about 1.23 m, -0.02 m, and -0.30 m in X, Y and Z directions, respectively. This means that the SIRAL SARIn mode processing technique enables to measure the three-dimensional ground position with the precision of several meters.

• Current Optics and Photonics
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• 제3권5호
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• pp.466-472
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• 2019

A system for continuous-wave coherent Doppler lidar (CW lidar), made up of all-fiber structures and a coaxial transmission telescope, was set up for wind measurement in Hefei (31.84 N, 117.27 E), Anhui province of China. The lidar uses a fiber laser as a light source at a wavelength of $1.55{\mu}m$, and focuses the laser beam on a location 80 m away from the telescope. Using the CW lidar, radial wind measurement was carried out. Subsequently, the spectra of the atmospheric backscattered signal were analyzed. We tested the noise and obtained the lower limit of wind velocity as 0.721 m/s, through the Rayleigh criterion. According to the number of Doppler peaks in the radial wind spectrum, a classification retrieval algorithm (CRA) combining a Gaussian fitting algorithm and a spectral centroid algorithm is designed to estimate wind velocity. Compared to calibrated pulsed coherent wind lidar, the correlation coefficient for the wind velocity is 0.979, with a standard deviation of 0.103 m/s. The results show that CW lidar offers satisfactory performance and the potential for application in wind measurement.

• 한국산업정보학회논문지
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• 제17권2호
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• pp.57-64
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• 2012

본 논문에서는 텍스트 마이닝 분야에서 중요한 부분을 차지하고 있는 문서 클러스터링을 위하여 다목적 유전자 알고리즘을 제안한다. 문서 클러스터링에 있어 중요한 요소 중 하나는 유사한 문서를 그룹화 하는 클러스터링 알고리즘이다. 지금까지 문서 클러스터링에는 k-means 클러스터링, 유전자 알고리즘 등을 사용한 연구가 많이 진행되고 있다. 하지만 k-means 클러스터링은 초기 클러스터 중심에 따라 성능 차이가 크며 유전자 알고리즘은 목적함수에 따라 지역 최적해에 쉽게 빠지는 단점을 갖고 있다. 본 논문에서는 이러한 단점을 보완하기 위하여 다목적 유전자 알고리즘을 문서 클러스터링에 적용해 보고, 기존의 알고리즘과 정확성을 비교 및 분석한다. 성능 시험을 통해 k-means 클러스터링(약 20%)과 기존의 유전자 알고리즘(약 17%)을 비교할 때 본 논문에서 제안한 다목적 유전자 알고리즘의 성능이 월등하게 향상됨을 보인다.

• 한국멀티미디어학회논문지
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• 제14권4호
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• pp.529-537
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• 2011

본 논문에서는 물체를 구성하고 있는 컬러들의 기하학적 중심을 이용하여 물체의 크기에 적응적인 추적 알고리즘을 제안한다. 대부분의 크기 적응적 알고리즘은 표적윈도우의 크기를 결정하기 위하여 히스토그램을 사용한다. 그러나, 이러한 방법은 표적의 배경에 표적의 색상과 유사한 물체가 존재하거나 표적의 일부분이 폐색되었을 때 표적의 크기를 추정하는데 실패한다. 이것은 히스토그램이 영역에 대한 기하학적인 공간정보를 상실한채 표적 컬러의 화소수하고만 연관되기 때문이다. 이러한 분석을 바탕으로 본 논문은 표적 컬러의 화소수의 변화에 상대적으로 덜 민감한 표적의 컬러 중심을 이용한 크기 적응 알고리즘을 제안한다. 컬러의 중심들은 공간정보를 가지고 있기 때문에 컬러중심과 표적 영역의 크기에는 직접적인 상관관계가 존재한다. 표적의 크기 변화를 추정하기 위하여 각각의 표적 컬러에 대한 줌팩터를 추정한 후, 적절한 필터링 과정을 통해 하나의 줌팩터를 추정한다. 제안한 크기 추정 알고리즘은 중심이동 기반의 추적 알고리즘과 결합된다. 제안된 크기 적응적 추적 알고리즘은 배경에 유사한 컬러가 존재하는 경우에도 안정적으로 작동하는 것을 실험으로 검증한다.