• Journal of the Korean Institute of Intelligent Systems
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• v.9 no.6
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• pp.583-590
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• 1999

We propose the reusability decision model of the object-oriented components, which can decide the potentiality of reusability of the object-oriented components actively. Fisrt, we select attributes for the reusability decision of the object-oriented components. Then, we acquire information from the reused components based on the quality measures and criteria proposed by many researches. Lastly, we generate algorithm for the reusability decision of the object-oriented components from the acquired information employing rough set.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.10A
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• pp.990-999
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• 2002

The object-oriented(OO) distributed real-time(RT) programming movement started in 1990's and is growing rapidly at this turn of the century. Distributed real-time simulation is a field in its infancy but it is bounded to receive steadily growing recognition for its importance and wide applicability. The scheme is called the distributed time-triggered simulation scheme which is conceptually simple and easy to use but widely applicable. A new generation object oriented(OO) RT programming scheme is called the time-triggered message triggered object(TMO) programming scheme and it is used to make specific illustrations of the issues. The TMO structuring scheme is a general-style components structuring scheme and supports design of all types of component including hard real time objects and non real time objects within one general structure.

• Journal of Broadcast Engineering
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• v.24 no.6
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• pp.1076-1084
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• 2019

In this paper, we introduced a system that extracts metadata by recognizing characters and objects in media using deep learning technology. In the field of broadcasting, multimedia contents such as video, audio, image, and text have been converted to digital contents for a long time, but the unconverted resources still remain vast. Building media archives requires a lot of manual work, which is time consuming and costly. Therefore, by implementing a deep learning-based metadata generation system, it is possible to save time and cost in constructing media archives. The whole system consists of four elements: training data generation module, object recognition module, character recognition module, and API server. The deep learning network module and the face recognition module are implemented to recognize characters and objects from the media and describe them as metadata. The training data generation module was designed separately to facilitate the construction of data for training neural network, and the functions of face recognition and object recognition were configured as an API server. We trained the two neural-networks using 1500 persons and 80 kinds of object data and confirmed that the accuracy is 98% in the character test data and 42% in the object data.

• 한국신재생에너지학회:학술대회논문집
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• 2008.10a
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• pp.91-93
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• 2008

A Buoyant Hybrid Power Generation System (BHPGS) described in this paper, is a conceptual approach to a hybrid solar-wind power generation in the near sea. The primary purpose of the BHPGS is given to improve utilization of solar cell modules. Main components of the BHPGS include a solar cell module, buoyant object, power generator, and support assembly including weight. Components such a generator controller, DC/AC converter, etc., are not configured in the current BHPGS because they can easily be purchased as a commercial-off-the-shelf product. In addition, some of the BHPGS applications are discussed.

• Journal of Industrial Technology
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• v.27 no.A
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• pp.185-193
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• 2007

The object of this study is the development of a Method which is enable to review the preliminary feasibility for co-generation system in new apartment buildings. In Korea co-generation systems have been installed in most of large industrial plants and commercial buildings which consume a large quantity of electric and heat energy, for energy saving and cutting products cost, under positive governmental supports. However for apartment buildings which consume quite a large electric and heat energy, are still remained in conventional energy supply system, and are not popular to utilize useful co-generation system. One of the major reason for these is the lack of clear and easy justification tool. In this circumstance, this study can provide a tool to verify the feasibility of co-generation in apartment buildings with this handy tools for planners and designers beforehand.

• Journal of KIISE:Computing Practices and Letters
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• v.8 no.4
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• pp.430-441
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• 2002

Video object segmentation is an important component for object-based video coding scheme such as MPEG-4. In this paper, a robust algorithm for segmentation of moving objects in video sequences and VOP(Video Object Planes) extraction is presented. The points of this paper are detection, of an accurate object boundary by associating moving object edge with spatial object edge and generation of VOP. The algorithm begins with the difference between two successive frames. And after extracting difference image, the accurate moving object edge is produced by using the Canny algorithm and morphological operation. To enhance extracting performance, we app]y the morphological operation to extract more accurate VOP. To be specific, we apply morphological erosion operation to detect only accurate object edges. And moving object edges between two images are generated by adjusting the size of the edges. This paper presents a robust algorithm implementation for fast moving object detection by extracting accurate object boundaries in video sequences.

• Journal of Korea Multimedia Society
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• v.7 no.11
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• pp.1550-1555
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• 2004

Shadows increase the visual realism of computer-generated images and they are good hint for spatial relationships between objects. Previous methods to produce a shadow texture for an object are to render all objects between the object and light source. Consequently entire time for generating shadow textures between all objects is Ο(Ν$^2$), where Ν is the number of objects. We propose a novel shadow texture generation method with constant processing time for each object using shadow depth buffet. In addition, we also present method to achieve further speed-up using temporal coherence. If the transition between dynamic and static state is not frequent, depth values of static objects does not vary significantly. So we can reuse the depth value for static objects and render only dynamic objects.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.21 no.2
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• pp.147-154
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• 2003

The close-range photogrammetry is a surveying technique the acquiring the 3D object from 2D geometric appearance shown in the image. Camera treatment is relatively so simple. Camera position refer to the object can be freely adjusted by locating the exposure station at any site. So it is used effectively on a small area or object for survey. In this study, using the digital camera which has capacity of keeping numerical value by itself and easy carrying, we analyze the positioning error according to various change of photographing condition. Also we try to find a effective method of acquiring basis data for 3D monitoring of high-accuracy in sub-pixel degree thorough digital close-range photogrammetry with bundle adjustment for local terrain model generation.

• Journal of KIBIM
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• v.11 no.4
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• pp.53-62
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• 2021

The successful implementation of Scan-to-BIM automation depends on the entire process from scanning of buildings, including indoor facilities and furniture, to generating BIM models. However, the conventional Scan-to-BIM process requires a lot of time, manpower, and cost for the manual generation of BIM models including indoor objects. To solve this problem, this study applied a Scan-to-BIM automation process using a deep learning model and parametric algorithm to an existing building, Kangwon Fire Service Academy. To improve the accuracy of the BIM model, after object data was extracted from the scan data, the data was corrected according to actual object-specific conditions. As a result, the accuracy of the BIM model created by the proposed Scan-to-BIM automation process was 91% compared to the actual area of the construction drawings. In addition, it was confirmed that the BIM objects were automatically generated for 10 object classes.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.10
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• pp.150-161
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• 2013

This paper presents a new system which produces high resolution 3D contents by capturing multiview images of an object using multiple cameras, and estimating geometric and texture information of the object from the captured images. Even though a variety of multiview image-based 3D reconstruction systems have been proposed, it was difficult to generate high resolution 3D contents because multiview image-based 3D reconstruction requires a large amount of memory and computation. In order to reduce computational complexity and memory size for 3D reconstruction, the proposed system predetermines the regions in input images where an object can exist to extract object boundaries fast. And for fast computation of a visual hull, the system represents silhouettes and 3D-2D projection/back-projection relations by chain codes and 1D homographies, respectively. The geometric data of the reconstructed object is compactly represented by a 3D segment-based data format which is called DoCube, and the 3D object is finally reconstructed after 3D mesh generation and texture mapping are performed. Experimental results show that the proposed system produces 3D object contents of $800{\times}800{\times}800$ resolution with a rate of 2.2 seconds per frame.