• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.87.3-87
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• 2001

The principle of matching is a new framework for control systems design that requires the matching between the control system and the environment (the source of exogenous inputs). The principle is especially useful for the design of the critical control systems where the responses of the control systems should be kept below the prescribed values. The design problem is reduced to find controller satisfying inequality constraints. However, conventional optimization techniques do not possess structural model selection ability and designers are required to select appropriate controller model. We propose to use a genetic algorithm to find an appropriate controller satisfying the matching conditions. The proposed genetic algorithm ...

• Korean Journal of Remote Sensing
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• v.16 no.4
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• pp.347-353
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• 2000

The purpose of this paper is to extract DEM (Digital Elevation Model) using KOMPSAT images. DEM extraction consists of three parts. First part is the modeling of satellite position and attitude, second part is the matching of two images to find corresponding points of them and third part is to calculate the elevation of each point by using the result of the first and second part. The position and attitude modeling of satellite is processed by using GCPs. Area based matching method is used to find the corresponding points between the stereo satellite images. The elevation of each point is calculated using the exterior orientation information obtained from sensor modeling and the disparity from the stereo matching. In experiment, the KOMPSAT images, 2592$\times$2796 panchromatic images are used to extract DEM. The experiment result show the DEM using KOMPSAT images.

• International journal of advanced smart convergence
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• v.11 no.3
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• pp.49-55
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• 2022

Hair styling has a significant influence on human social perception. An increasing number of people are learning hair styling and obtaining hair designer licenses. However, it takes a considerable amount of money and time to learn professional hairstyle and beauty techniques for hair styling. Since COVID-19, there has been a growing need for offline and video lectures due to the decline in onsite training opportunities. This study provides a field practice environment in which real hair beauty is performed in a virtual space. Further, the hairstyle that is most similar to the user's hair taken with a webcam or mobile phone is determined through an image matching system using the speeded up robust features (SURF) method. The matching hairstyle was created into a three-dimensional (3D) hair model. The created 3D hair model uses a head-mounted display (HMD) and a controller that enables finger tracking through mapping to reproduce the haircutting scissors' motion while providing a feeling of real hair beauty.

• International journal of advanced smart convergence
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• v.12 no.3
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• pp.75-88
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• 2023

In a specific domain, experts have different understanding of domain knowledge or different purpose of constructing ontology. These will lead to multiple different ontologies in the domain. This phenomenon is called the ontology heterogeneity. For research fields that require cross-ontology operations such as knowledge fusion and knowledge reasoning, the ontology heterogeneity has caused certain difficulties for research. In this paper, we propose a novel ontology matching model that combines word embedding and a concatenated continuous bag-of-words model. Our goal is to improve word vectors and distinguish the semantic similarity and descriptive associations. Moreover, we make the most of textual and structural information from the ontology and external resources. We represent the ontology as a graph and use the SimRank algorithm to calculate the structural similarity. Our approach employs a similarity queue to achieve one-to-many matching results which provide a wider range of insights for subsequent mining and analysis. This enhances and refines the methodology used in ontology matching.

• The Journal of Information Systems
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• v.15 no.3
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• pp.159-174
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• 2006

Employment rate of graduating students has been one of the most important issues at universities. Recently interest on internship abroad has been increased significantly due to globalization of the society In particular, central and local governments have developed policies and encouraged university students to participate in internships abroad. However, activities and resources for internships abroad are very limited to a few organizations. This paper investigated the current status of internship in the U.S. and Korea. Then, this paper analyzed differences in demand and supply of the internship and matching mechanism of the internship between the U.S. and Korea. From the results of those analyses, this paper developed an international network model which can help effective and efficient increase in the demand and supply of the internship as well as the internship matching mechanism in Korea. This network model utilizes international NGOs in order to develop internationally cooperative environment. This model provides mechanism for (1) effectively identifying intern applicants who like to work abroad and evaluating thent (2) effectively identifying new internship positions and evaluating companies which plan to hire interns, (3) efficiently matching demand for and supply of internship by identifying appropriate candidates, (4) monitoring companies for their quality of working conditions and interns for their qualities of work This model for internship has been applied for a NGO which is International CBMC (Christian Businessman Committee International)

• The Journal of Korea Robotics Society
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• v.4 no.3
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• pp.185-191
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• 2009

This paper presents a new shape-based algorithm using affine category shape model for object category recognition and model learning. Affine category shape model is a graph of interconnected nodes whose geometric interactions are modeled using pairwise potentials. In its learning phase, it can efficiently handle large pose variations of objects in training images by estimating 2-D homography transformation between the model and the training images. Since the pairwise potentials are defined on only relative geometric relationship betweenfeatures, the proposed matching algorithm is translation and in-plane rotation invariant and robust to affine transformation. We apply spectral matching algorithm to find feature correspondences, which are then used as initial correspondences for RANSAC algorithm. The 2-D homography transformation and the inlier correspondences which are consistent with this estimate can be efficiently estimated through RANSAC, and new correspondences also can be detected by using the estimated 2-D homography transformation. Experimental results on object category database show that the proposed algorithm is robust to pose variation of objects and provides good recognition performance.

• Journal of information and communication convergence engineering
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• v.7 no.1
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• pp.1-6
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• 2009

In order to obtain a 3-D urban model, an abstraction of the surface model is required. This paper describes works on the 3D reconstruction and modeling by the grouping 3D line segments extracted from the stereo matching of edges, which is derived from multiple images. The grouping is achieved by conditions of degrees and distances between lines. Building objects are determined by the junction combinations of the grouped line segments. The proposed algorithm demonstrates effective results of 3D reconstruction of buildings with 2D aerial images.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.10
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• pp.123-131
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• 1999

In this paper, we proposed stereo matching algorithm by dynamic programming with edges emphasized. Existing algorithms show blur generally at depth discontinuities owing to smoothness constraint and non-existence of matching pixel in occlusion regions. Also it accompanies matching error by lackness of matching information in the untextured regions. This paper defines new cost function to make up for the problems occurred to existing algorithms. It is possible through deriving matching of edges in left and right images to be carried out between edge regions anf deriving that in the other regions to be peformed between the other regions. In case of the possibility that edges can be Produced in a large amount, matching between edge information adds weight to cost function in proportion to Path distance. Proposed algorithm was applied to various images obtained by convergent camera model as well as parallel camera model. As the result, proposed algorithm showed improved performance in the aspect of matching error and processing in the occlusion regions compared to existing algorithms. Also it could improve blur especially in discontinuity regions.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.6
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• pp.33-41
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• 2004

This paper proposes a color matching 3D look-up table simplifying the complex color matching procedure between a monitor and a mobile display device. In other to perform color matching, it is necessary to process color of image in the device independent color space like CIEXYZ or CIELAB. To obtain the data of the device independent color space from that of the device dependent RGB color space, we must perform display characterizations. LCD characterization error using S-curve model is larger than tolerance error since LCD is more nonlinear than CRT. This paper improves the S-curve model to have smaller characterization error than tolerance error using the electro-optical transfer functions of X, Y, and Z value. We obtained images having higher color fidelity on mobile display devices through color matching experiments between monitor and mobile display devices. As a result of this experiments, we concluded that the color matching look-up table with 64(4${\times}$4${\times}$4) is the smallest size allowing characterization error to be acceptable.

• Korean Journal of Remote Sensing
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• v.34 no.6_2
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• pp.1251-1260
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• 2018

High-quality sea-ice surface models generated from aerial images can be used effectively as field data for developing satellite-based remote sensing methods but also as analysis data for understanding geometric variations of Arctic sea-ice. However, the lack of texture information on sea-ice surfaces can reduce the accuracy of image matching. In this paper, we analyze the performance of matching cost functions for homogeneous sea-ice surfaces as a part of high-quality sea-ice surface model generation. The matching cost functions include sum of squared differences (SSD), normalized cross-correlation (NCC), and zero-mean normalized cross-correlation (ZNCC) in image domain and phase correlation (PC), orientation correlation (OC), and gradient correlation (GC) in frequency domain. In order to analyze the matching performance for texture changes clearly and objectively, a new evaluation methodology based on the principle of object-space matching technique was introduced. Experimental results showed that it is possible to secure reliability and accuracy of image matching only when optimal search windows are variably applied to each matching point in textureless regions such as sea-ice surfaces. Among the matching cost functions, NCC and ZNCC showed the best performance for texture changes.