• International Journal of CAD/CAM
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• v.3 no.1_2
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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.

• Journal of applied mathematics & informatics
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• v.9 no.2
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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.

• International Journal of CAD/CAM
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• v.5 no.1
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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.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.43 no.6
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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.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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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.

• Journal of the Korean Society for Precision Engineering
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• v.28 no.10
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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.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.4
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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.

• Korean Journal of Computational Design and Engineering
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• v.11 no.4
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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.

• The KIPS Transactions:PartD
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• v.19D no.1
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• pp.81-94
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• 2012

FORM(Feature-Oriented Reuse Method) is one of representative product line engineering methods. The essence of FORM is the FORM architecture models, which can be reused in the development of multiple products of a software product line. The FORM architecture models, however, have the following problems when applied in practice. First, they are not standardized models like UML(Unified Modeling Language) and therefore they can be constructed only through a specific modeling tool. Second, they do not represent architectural variability explicitly. Instead their variability is only managed through a mapping from a feature model. To address these two problems, we developed at first a method for representing the FORM architecture models using UML, which enables the FORM architecture models to be constructed through various available UML modeling tools. Also, we developed an effective method for representing as well as managing the variability of the FORM architecture models through a mapping from a feature model.