• Title/Summary/Keyword: Multi-Points Method

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Multi-Sensor Multi-Target Passive Locating and Tracking

  • Liu, Mei;Xu, Nuo;Li, Haihao
    • International Journal of Control, Automation, and Systems
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    • v.5 no.2
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    • pp.200-207
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    • 2007
  • The passive direction finding cross localization method is widely adopted in passive tracking, therefore there will exist masses of false intersection points. Eliminating these false intersection points correctly and quickly is a key technique in passive localization. A new method is proposed for passive locating and tracking multi-jammer target in this paper. It not only solves the difficulty of determining the number of targets when masses of false intersection points existing, but also solves the initialization problem of elastic network. Thus this method solves the problem of multi-jammer target correlation and the elimination of static false intersection points. The method which dynamically establishes multiple hypothesis trajectory trees solves the problem of eliminating the remaining false intersection points. Simulation results show that computational burden of the method is lower, the elastic network can more quickly find all or most of the targets and have a more probability of locking the real targets. This method can eliminate more false intersection points.

Development of Pareto strategy multi-objective function method for the optimum design of ship structures

  • Na, Seung-Soo;Karr, Dale G.
    • International Journal of Naval Architecture and Ocean Engineering
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    • v.8 no.6
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    • pp.602-614
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    • 2016
  • It is necessary to develop an efficient optimization technique to perform optimum designs which have given design spaces, discrete design values and several design goals. As optimization techniques, direct search method and stochastic search method are widely used in designing of ship structures. The merit of the direct search method is to search the optimum points rapidly by considering the search direction, step size and convergence limit. And the merit of the stochastic search method is to obtain the global optimum points well by spreading points randomly entire the design spaces. In this paper, Pareto Strategy (PS) multi-objective function method is developed by considering the search direction based on Pareto optimal points, the step size, the convergence limit and the random number generation. The success points between just before and current Pareto optimal points are considered. PS method can also apply to the single objective function problems, and can consider the discrete design variables such as plate thickness, longitudinal space, web height and web space. The optimum design results are compared with existing Random Search (RS) multi-objective function method and Evolutionary Strategy (ES) multi-objective function method by performing the optimum designs of double bottom structure and double hull tanker which have discrete design values. Its superiority and effectiveness are shown by comparing the optimum results with those of RS method and ES method.

Navigation Sign Recognition in Indoor enviroments Using Fuzzy Inference (퍼지추론을 이용한 실내환경에서의 주행신호인식)

  • 김전호;유범재;조영조;박민용;고범석
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1997.11a
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    • pp.141-144
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    • 1997
  • This paper presents a method of navigation sign recognition in indoor environments using a fuzzy inference for an autonomous mobile robot. In order to adapt to image deformation of a navigation sign resulted from variations of view-points and distances, a multi-labeled template matching(MLTM) method and a dynamic area search method(DASM) are proposed. The DASM is proposed to detect correct feature points among incorrect feature points. Finally sugeno-style fuzzy inference are adopted for recognizing the navigation sign.

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Image Scale Prediction Using Key-point Clusters on Multi-scale Image Space (다중 스케일 영상 공간에서 특징점 클러스터를 이용한 영상스케일 예측)

  • Ryu, kwon-Yeal
    • Journal of the Institute of Convergence Signal Processing
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    • v.19 no.1
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    • pp.1-6
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    • 2018
  • In this paper, we propose the method to eliminate repetitive processes for key-point detection on multi-scale image space. The proposed method detects key-points from the original image, and select a good key-points using the cluster filters, and create the key-point clusters. And it select reference objects by using direction angles of the key-point clusters, predict the scale of the original image by using the distributed distance ratio. It transform the scale of the reference image, and apply the detection of key-points to the transformed reference image. In the results of the experiment, the proposed method can be found to improve the key-points detection time by 75 % and 71 % compared to SIFT method and scaled ORB method using the multi-scale images.

Implementation of non-Wearable Air-Finger Mouse by Infrared Diffused Illumination (적외선 확산 투광에 의한 비장착형 공간 손가락 마우스 구현)

  • Lee, Woo-Beom
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.15 no.2
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    • pp.167-173
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    • 2015
  • Extraction of Finger-end points is one of the most process for user multi-commands in the Hand-Gesture interface technology. However, most of previous works use the geometric and morphological method for extracting a finger-end points. Therefore, this paper proposes the method of user finger-end points extraction that is motivated a ultrared diffused illumination, which is used for the user commands in the multi-touch display device. Proposed air-mouse is worked by the quantity state and moving direction of extracted finger-end points. Also, our system includes a basic mouse event, as well as the continuous command function for expending a user multi-gesture. In order to evaluate the performance of the our proposed method, after applying to the web browser application as a command device. As a result, the proposed method showed the average 90% success-rate for the various user-commands.

Automatic Image Registration Based on Extraction of Corresponding-Points for Multi-Sensor Image Fusion (다중센서 영상융합을 위한 대응점 추출에 기반한 자동 영상정합 기법)

  • Choi, Won-Chul;Jung, Jik-Han;Park, Dong-Jo;Choi, Byung-In;Choi, Sung-Nam
    • Journal of the Korea Institute of Military Science and Technology
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    • v.12 no.4
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    • pp.524-531
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    • 2009
  • In this paper, we propose an automatic image registration method for multi-sensor image fusion such as visible and infrared images. The registration is achieved by finding corresponding feature points in both input images. In general, the global statistical correlation is not guaranteed between multi-sensor images, which bring out difficulties on the image registration for multi-sensor images. To cope with this problem, mutual information is adopted to measure correspondence of features and to select faithful points. An update algorithm for projective transform is also proposed. Experimental results show that the proposed method provides robust and accurate registration results.

Highly Dense 3D Surface Generation Using Multi-image Matching

  • Noh, Myoung-Jong;Cho, Woo-Sug;Bang, Ki-In
    • ETRI Journal
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    • v.34 no.1
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    • pp.87-97
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    • 2012
  • This study presents an automatic matching method for generating a dense, accurate, and discontinuity-preserved digital surface model (DSM) using multiple images acquired by an aerial digital frame camera. The proposed method consists of two main procedures: area-based multi-image matching (AMIM) and stereo-pair epipolar line matching (SELM). AMIM evaluates the sum of the normalized cross correlation of corresponding image points from multiple images to determine the optimal height of an object point. A novel method is introduced for determining the search height range and incremental height, which are necessary for the vertical line locus used in the AMIM. This procedure also includes the means to select the best reference and target images for each strip so that multi-image matching can resolve the common problem over occlusion areas. The SELM extracts densely positioned distinct points along epipolar lines from the multiple images and generates a discontinuity-preserved DSM using geometric and radiometric constraints. The matched points derived by the AMIM are used as anchor points between overlapped images to find conjugate distinct points using epipolar geometry. The performance of the proposed method was evaluated for several different test areas, including urban areas.

A Multi-Point Design Optimization of a Space Launcher Nose Shapes Using Response Surface Method (반응면 기법을 이용한 발사체 선두부 다점 최적설계)

  • Kim Sang-Jin;Seon Yong-Hee;Lee Jae-Woo;Byun Yung-Hwan
    • 한국전산유체공학회:학술대회논문집
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    • 2000.10a
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    • pp.46-53
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    • 2000
  • To improve the performance at all design points, multi-point optimization method is implemented for the nose fairing shape design of space launcher. The response surface method is used to effectively reduce the huge computational loads during the optimization process. The drag is selected as the objective function, and the surface heat transfer characteristics, and the internal volume of the nose fairing ate considered as design constraints. Full Wavier-Stokes equations are selected as governing equations. Two points drag minimization, and two points drag / heat flux optimization were successfully performed and configurations which have good performance for the wide operation range were derived. By considering three design points, the space launcher shape which undergoes the least drag during whole flight mission was designed. For all the design cases, the constructed response surfaces show good confidence level with only 23 design points with the proper stretching of the design space.

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Development of a Multi-objective function Method Based on Pareto Optimal Point (Pareto 최적점 기반 다목적함수 기법 개발에 관한 연구)

  • Na, Seung-Soo
    • Journal of the Society of Naval Architects of Korea
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    • v.42 no.2 s.140
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    • pp.175-182
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    • 2005
  • It is necessary to develop an efficient optimization technique to optimize the engineering structures which have given design spaces, discrete design values and several design goals. As optimization techniques, direct search method and stochastic search method are widely used in designing of engineering structures. The merit of the direct search method is to search the optimum points rapidly by considering the search direction, step size and convergence limit. And the merit of the stochastic search method is to obtain the global optimum points by spreading point randomly entire the design spaces. In this paper, a Pareto optimal based multi-objective function method (PMOFM) is developed by considering the search direction based on Pareto optimal points, step size, convergence limit and random search generation . The PMOFM can also apply to the single objective function problems, and can consider the discrete design variables such as discrete plate thickness and discrete stiffener spaces. The design results are compared with existing Evolutionary Strategies (ES) method by performing the design of double bottom structures which have discrete plate thickness and discrete stiffener spaces.