• 제목/요약/키워드: Feature Mapping

검색결과 335건 처리시간 0.022초

Design of a Feature-based Multi-viewpoint Design Automation System

  • Lee, Kwang-Hoon;McMahon, Chris A.;Lee, Kwan-H.
    • International Journal of CAD/CAM
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    • 제3권1_2호
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    • pp.67-75
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    • 2003
  • Viewpoint-dependent feature-based modelling in computer-aided design is developed for the purposes of supporting engineering design representation and automation. The approach of this paper uses a combination of a multi-level modelling approach. This has two stages of mapping between models, and the multi-level model approach is implemented in three-level architecture. Top of this level is a feature-based description for each viewpoint, comprising a combination of form features and other features such as loads and constraints for analysis. The middle level is an executable representation of the feature model. The bottom of this multi-level modelling is a evaluation of a feature-based CAD model obtained by executable feature representations defined in the middle level. The mappings involved in the system comprise firstly, mapping between the top level feature representations associated with different viewpoints, for example for the geometric simplification and addition of boundary conditions associated with moving from a design model to an analysis model, and secondly mapping between the top level and the middle level representations in which the feature model is transformed into the executable representation. Because an executable representation is used as the intermediate layer, the low level evaluation can be active. The example will be implemented with an analysis model which is evaluated and for which results are output. This multi-level modelling approach will be investigated within the framework aimed for the design automation with a feature-based model.

A METHOD OF IMAGE DATA RETRIEVAL BASED ON SELF-ORGANIZING MAPS

  • Lee, Mal-Rey;Oh, Jong-Chul
    • Journal of applied mathematics & informatics
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    • 제9권2호
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    • pp.793-806
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    • 2002
  • Feature-based similarity retrieval become an important research issue in image database systems. The features of image data are useful to discrimination of images. In this paper, we propose the highspeed k-Nearest Neighbor search algorithm based on Self-Organizing Maps. Self-Organizing Maps (SOM) provides a mapping from high dimensional feature vectors onto a two-dimensional space. The mapping preserves the topology of the feature vectors. The map is called topological feature map. A topological feature map preserves the mutual relations (similarity) in feature spaces of input data. and clusters mutually similar feature vectors in a neighboring nodes. Each node of the topological feature map holds a node vector and similar images that is closest to each node vector. In topological feature map, there are empty nodes in which no image is classified. We experiment on the performance of our algorithm using color feature vectors extracted from images. Promising results have been obtained in experiments.

Identification of Topological Entities and Naming Mapping for Parametric CAD Model Exchanges

  • Mun, Duh-Wan;Han, Soon-Hung
    • International Journal of CAD/CAM
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    • 제5권1호
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    • pp.69-81
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    • 2005
  • As collaborative design and configuration design gain increasing importance in product development, it becomes essential to exchange parametric CAD models among participants. Parametric CAD models can be represented and exchanged in the form of a macro file or a part file that contains the modeling history of a product. The modeling history of a parametric CAD model contains feature specifications and each feature has selection information that records the name of the referenced topological entities. Translating this selection information requires solving the problems of how to identify the referenced topological entities of a feature (persistent naming problem) and how to convert the selection information into the format of the receiving CAD system (naming mapping problem). The present paper introduces the problem of exchanging parametric CAD models and proposes a solution to naming mapping.

퍼지 신경망을 이용한 시각구동(I) (Fuzzy Neural Network-based Visual Servoing : part I)

  • 김태원;서일홍
    • 대한전기학회논문지
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    • 제43권6호
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    • pp.1010-1019
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    • 1994
  • It is shown that there exists a nonlinear mapping which transforms image features and their changes to the desired camera motion without measuring of the relative distance between the camera and the object. This nonlinear mapping can eliminate several difficulties occurring in computing the inverse of the feature Jacobian as in the usual feature-based visual feedback control methods. Instead of analytically deriving the closed form of this mapping, a Fuzzy Membership Function-based Neural Network (FMFNN) incorporating a Fuzzy-Neural Interpolating Network is used to approximate the nonlinear mapping. Several FMFNN's are trained to be capable of tracking a moving object in the whole workspace along the line of sight. For an effective implementation of the proposed FMF network, an image feature selection process is investigated. Finally, several numerical examples are presented to show the validity of the proposed visual servoing method.

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Trinocular 정합과 DEM 변환식을 이용한 차폐지역이 포함된 인공지물의 높이 추출 (Height extraction of the man-made structure including occluded region using trinocular matching and DEM mapping)

  • 김지태;엄기문;이쾌희
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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    • pp.260-263
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    • 1996
  • THe Purpose of this paper is to match the feature point of man-made structure and to obtain the DEM which are occluded in a image plane. We use the trinocular matching with epipolar lines and planes. If an occlusion appears at one of the trinocular images, the DEM mapping is used to estimate the height of feature points in it.

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이동로봇을 위한 Sonar Salient 형상과 선 형상을 이용한 EKF 기반의 SLAM (EKF-based SLAM Using Sonar Salient Feature and Line Feature for Mobile Robots)

  • 허영진;임종환;이세진
    • 한국정밀공학회지
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    • 제28권10호
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    • pp.1174-1180
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    • 2011
  • Not all line or point features capable of being extracted by sonar sensors from cluttered home environments are useful for simultaneous localization and mapping (SLAM) due to their ambiguity because it is difficult to determine the correspondence of line or point features with previously registered feature. Confused line and point features in cluttered environments leads to poor SLAM performance. We introduce a sonar feature structure suitable for a cluttered environment and the extended Kalman filter (EKF)-based SLAM scheme. The reliable line feature is expressed by its end points and engaged togather in EKF SLAM to overcome the geometric limits and maintain the map consistency. Experimental results demonstrate the validity and robustness of the proposed method.

퍼지 신경망에 의한 로보트의 시각구동 (Visual servoing of robot manipulator by fuzzy membership function based neural network)

  • 김태원;서일홍;조영조
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1992년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 19-21 Oct. 1992
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    • pp.874-879
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    • 1992
  • It is shown that there exists a nonlinear mappping which transforms features and their changes to the desired camera motion without measurement of the relative distance between the camera and the part, and the nonlinear mapping can eliminate several difficulties encountered when using the inverse of the feature Jacobian as in the usual feature-based visual feedback controls. And instead of analytically deriving the closed form of such a nonlinear mapping, a fuzzy membership function (FMF) based neural network is then proposed to approximate the nonlinear mapping, where the structure of proposed networks is similar to that of radial basis function neural network which is known to be very useful in function approximations. The proposed FMF network is trained to be capable of tracking moving parts in the whole work space along the line of sight. For the effective implementation of proposed IMF networks, an image feature selection processing is investigated, and required fuzzy membership functions are designed. Finally, several numerical examples are illustrated to show the validities of our proposed visual servoing method.

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Experimental Optimal Choice Of Initial Candidate Inliers Of The Feature Pairs With Well-Ordering Property For The Sample Consensus Method In The Stitching Of Drone-based Aerial Images

  • Shin, Byeong-Chun;Seo, Jeong-Kweon
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제14권4호
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    • pp.1648-1672
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    • 2020
  • There are several types of image registration in the sense of stitching separated images that overlap each other. One of these is feature-based registration by a common feature descriptor. In this study, we generate a mosaic of images using feature-based registration for drone aerial images. As a feature descriptor, we apply the scale-invariant feature transform descriptor. In order to investigate the authenticity of the feature points and to have the mapping function, we employ the sample consensus method; we consider the sensed image's inherent characteristic such as the geometric congruence between the feature points of the images to propose a novel hypothesis estimation of the mapping function of the stitching via some optimally chosen initial candidate inliers in the sample consensus method. Based on the experimental results, we show the efficiency of the proposed method compared with benchmark methodologies of random sampling consensus method (RANSAC); the well-ordering property defined in the context and the extensive stitching examples have supported the utility. Moreover, the sample consensus scheme proposed in this study is uncomplicated and robust, and some fatal miss stitching by RANSAC is remarkably reduced in the measure of the pixel difference.

3차원 CAD에서 STEP Part111을 통한 AP224 특징형상 데이터 번역 (AP224 based Feature Translation from 3D CAD through STEP Part111)

  • 김준환
    • 한국CDE학회논문집
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    • 제11권4호
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    • pp.303-314
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    • 2006
  • The exchange of CAD (Computer Aided Design) models between different CAD systems and to downstream applications such as manufacturing has become very important to modem industry. One serious current issue is that the process cannot automatically import existing 3-D solid models in a variety of commercial CAD formats into the process without manually re-mastering the model in current standard including "SIEP AP(Application Protocol) 203 Edition 1" To fully integrate technical data from the design agency to the shop floor, design intent and validated 3D geometry of feature based parametric CAD model should be brought into the standardized processes. To overcome this limitation, AP203 Edition 2 (Ed.2) and its related STEP parts such as Part55, Part108, Part109, Part111 and Part112 are starting to be available to handle this problem. The features in Part111 are harmonized with the machining features available in AP224. This paper is focused on two mapping technologies: CAD to Part111 mapping and Pat111 to AP224 mapping including case studios and it will provide the guideline about what should be done next in the AP203 Ed.2 to AP224 mapping. The final goal of this project is to integrate technical data from CAD to AP224 based manufacturing information through AP203 Ed.2.

휘처-아키텍처 대응을 통한 UML 기반 FORM 아키텍처의 가변성 모델링 및 관리 (Managing and Modeling Variability of UML Based FORM Architectures Through Feature-Architecture Mapping)

  • 이관우
    • 정보처리학회논문지D
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    • 제19D권1호
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    • pp.81-94
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    • 2012
  • FORM 아키텍처 모델은 소프트웨어 프로덕트 라인 내의 제품 개발에 재사용될 수 있는 아키텍처로서 FORM 방법론의 핵심적인 역할을 한다. 하지만 기존의 FORM 아키텍처 모델을 실무에 적용할 때 다음과 같은 문제점들이 있다. 첫째, UML(Unified Modeling Language)과 같이 표준화된 모델이 아니므로, 이 모델을 작성하기 위해서는 고유한 모델링 도구가 필요하다. 둘째, FORM 아키텍처 모델은 휘처모델과의 대응 관계를 통해 가변성을 관리만 할 뿐, 아키텍처의 가변성을 명시적으로 나타내지 않았다. 본 논문에서는 이러한 FORM아키텍처 모델의 문제점을 해결하기 위해서, 먼저 FORM 아키텍처 모델을 UML 모델로 표현할 수 있는 방법을 개발하였다. 이는 FORM 아키텍처 모델링에 다양한 UML모델링 도구를 이용할 수 있는 장점이 있다. 또한, 휘처모델과의 대응관계를 통해서 FORM 아키텍처 모델의 가변성을 효과적으로 관리할 뿐만 아니라 표현 할 수 있는 방법을 개발하였다.