• 대한건축학회연합논문집
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• 제20권6호
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• pp.81-87
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• 2018

In this paper, in order to maximize the input process efficiency of the building energy simulation field, the authors developed the automatic extraction module of spatial information based BIM geometry information. Existing research or software extracts geometry information based on object information, but it can not be used in the field of energy simulation because it is inconsistent with the geometry information of the object constituting the thermal zone of the actual building model. Especially, IFC-based geometry information extraction module is needed to link with other architectural fields from the viewpoint of reuse of building information. The study method is as follows. (1) Grasp the category and attribute information to be extracted for energy simulation and Analyze the IFC structure based on spatial information (2) Design the algorithm for extracting and reprocessing information for energy simulation from IFC file (use programming language Phython) (3) Develop the module that generates a geometry information database based on spatial information using reprocessed information (4) Verify the accuracy of the development module. In this paper, the reprocessed information can be directly used for energy simulation and it can be widely used regardless of the kind of energy simulation software because it is provided in database format. Therefore, it is expected that the energy simulation process efficiency in actual practice can be maximized.

• 한국산학기술학회:학술대회논문집
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• 한국산학기술학회 2003년도 Proceeding
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• pp.99-104
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• 2003

In this research, we proposed the mechanism to develop self evolving expert systems (SEES) based on data mining (DM), fuzzy neural networks (FNN), and relational database (RDB)-driven forward/backward inference engine. Most former researchers tried to develop a text-oriented knowledge base (KB) and inference engine (IE). However, thy have some limitations such as 1) automatic rule extraction, 2) manipulation of ambiguousness in knowledge, 3) expandability of knowledge base, and 4) speed of inference. To overcome these limitations, many of researchers had tried to develop an automatic knowledge extraction and refining mechanisms. As a result, the adaptability of the expert systems was improved. Nonetheless, they didn't suggest a hybrid and generalized solution to develop self-evolving expert systems. To this purpose, in this study, we propose an automatic knowledge acquisition and composite inference mechanism based on DM, FNN, and RDB-driven inference. Our proposed mechanism has five advantages empirically. First, it could extract and reduce the specific domain knowledge from incomplete database by using data mining algorithm. Second, our proposed mechanism could manipulate the ambiguousness in knowledge by using fuzzy membership functions. Third, it could construct the relational knowledge base and expand the knowledge base unlimitedly with RDBMS (relational database management systems). Fourth, our proposed hybrid data mining mechanism can reflect both association rule-based logical inference and complicate fuzzy logic. Fifth, RDB-driven forward and backward inference is faster than the traditional text-oriented inference.

• 한국HCI학회:학술대회논문집
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• 한국HCI학회 2009년도 학술대회
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• pp.163-167
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• 2009

3 차원 인체 스캔 차원 기술의 활용도는 정확도의 개선과 가격의 저렴화로 인해 산업계에서 점점 부각되고 있다. 이런 인체 스캔 데이터의 활용도를 높이기 위해서는 인체 스캔 데이터의 기준점 추출이 필수적이다. 본 논문에서는 자동으로 인체 스캔 데이터의 기준점을 추출하는 알고리즘을 제안한다. 이를 위해 여러 인체 스캔 데이터들을 활용하여 주성분 분석을 하고 최적화를 거쳐 마커 없는 매칭을 수행한다. 최종적으로는 생성된 인체 모델의 위상 구조에서 기준점을 추출한다.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume I
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• pp.409-412
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• 2006

Today's commercial high resolution satellite imagery such as IKONOS and QuickBird, offers the potential to extract useful spatial information for geographical database construction and GIS applications. Recognizing this potential use of high resolution satellite imagery, KARI is performing a project for developing Korea multipurpose satellite 3(KOMPSAT-3). Therefore, it is necessary to develop techniques for various GIS applications of KOMPSAT-3, using similar high resolution satellite imagery. As fundamental studies for this purpose, we focused on the extraction of 3D spatial information and the update of existing GIS data from QuickBird imagery. This paper examines the scheme for rectification of high resolution image, and suggests the convenient semi-automatic algorithm for extraction of 3D building information from a single image. The algorithm is based on triangular vector structure that consists of a building bottom point, its corresponding roof point and a shadow end point. The proposed method could increase the number of measurable building, and enhance the digitizing accuracy and the computation efficiency.

• 전기학회논문지
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• 제58권5호
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• pp.1025-1034
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• 2009

In steel making production line, steel slabs are given a unique identification number. This identification number, Slab management number(SMN), gives information about the use of the slab. Identification of SMN has been done by humans for several years, but this is expensive and not accurate and it has been a heavy burden on the workers. Consequently, to improve efficiency, automatic recognition system is desirable. Generally, a recognition system consists of text localization, text extraction, character segmentation, and character recognition. For exact SMN identification, all the stage of the recognition system must be successful. In particular, the text localization is great important stage and difficult to process. However, because of many text-like patterns in a complex background and high fuzziness between the slab and background, directly extracting text region is difficult to process. If the slab region including SMN can be detected precisely, text localization algorithm will be able to be developed on the more simple method and the processing time of the overall recognition system will be reduced. This paper describes about the slab region localization using SIFT(Scale Invariant Feature Transform) features in the image. First, SIFT algorithm is applied the captured background and slab image, then features of two images are matched by Nearest Neighbor(NN) algorithm. However, correct matching rate can be low when two images are matched. Thus, to remove incorrect match between the features of two images, geometric locations of the matched two feature points are used. Finally, search rectangle method is performed in correct matching features, and then the top boundary and side boundaries of the slab region are determined. For this processes, we can reduce search region for extraction of SMN from the slab image. Most cases, to extract text region, search region is heuristically fixed [1][2]. However, the proposed algorithm is more analytic than other algorithms, because the search region is not fixed and the slab region is searched in the whole image. Experimental results show that the proposed algorithm has a good performance.

• 대한의용생체공학회:의공학회지
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• 제15권1호
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• pp.27-34
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• 1994

In this paper. a way to analysis a corridor scene for a vehicle's automatic locomotion is presented In general, it's necessary for a vision system of vehicles to identify its positions in given environments. The suggested algorithm is to decide base lines of a corridor image using the vanishing point finding. Feature points are extracted on the base line using a base line extraction tree. This algorithm is suitable for a motorized wheelchair's self locomotion in a building.

• 한국통신학회논문지
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• 제21권8호
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• pp.1885-1896
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• 1996

This paper describes the implementation of the AVT(Automatic video Tracker) using ASIC. The basic tracking algorithm is based on the spatio-temporal gradient method, and adaptive window sizing, track state decision algorithm were also realized. Newly developed ASIC performs recursive image filtering, extraction of spatio-temporal gradient/gradient functions of image in field rate. Using the FPGA/ASIC, the tracker was simply realized in one board type which can be easily applied to various image system. We conformed ASIC operation by computer simulation and tested the system in real tracking situations. From the result, the system can track the moving target which has a velocity of 2-3 pixel/field and a size of varying from 2 to 128 pixes. Also fast refresh rateof motion estimation(60Hz) improves the characteristics of servoing system which forms feedback loop with the tracker.

• 한국컴퓨터정보학회논문지
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• 제20권9호
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• pp.121-128
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• 2015

In this paper, we proposed and implemented the effective automatic foreground motion detection algorithm that detect the foreground motion by analyzing the digital video data that captured by the network camera. We classified the background as moving background, fixed background and normal background based on the standard deviation of background and used it to detect the foreground motion. According to the result of experiment, our algorithm decreased the fault detection of the moving background and increased the accuracy of the foreground motion detection. Also it could extract foreground more exactly by using the statistic information of background in the phase of our foreground extraction.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2001년도 춘계학술대회 학술발표 논문집
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• pp.121-125
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• 2001

본 논문에서는 자동적인 퍼지 규칙 생성을 위해 퍼지 균등화(Fuzzy Equalization)와 유전알고리즘(Genetic Algorithm)을 이용한 TSK 퍼지 시스템의 구축을 다룬다. Pedrycz에 의해 제안된 퍼지 균등화 방법은 수치적인 데이터로부터 확률분포함수를 구축한 후 전체공간상에서 이들을 적절히 표현할 수 있는 소속함수를 생성한다. 이렇게 구축된 각 입력에 대한 소속함수는 유전알고리즘에 의해 입력공간이 분할되며 결론부 파라미터는 최소자승법에 의해 추정되어 진다. 제안된 방법은 그리드 분할로 인해 규칙의 수가 증가하는 문제를 해결하고 학습데이터와 검증데이터에 의해 타당한 입력공간분할과 퍼지 규칙을 생성할 수 있다. 시뮬레이션의 예로서 Box-Jenkins의 가스로 데이터의 모델링에 적용하여 제안된 방법의 유용성을 알 수 있다.

• 한국전자파학회논문지
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• 제25권6호
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• pp.690-699
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• 2014

제트엔진변조(Jet Engine Modulation: JEM) 식별기법은 제트엔진의 주기적인 회전에 의해 변조되는 레이더 반사 신호로부터 제트엔진의 종류를 식별하는 기법이다. 본 논문에서는 JEM의 새로운 접근법으로서, 제트엔진의 특성을 추출하기 위한 자동화 알고리즘을 제안한다. 먼저 복소 신호의 경험적인 모드 분리법(Complex Empirical Mode Decomposition: CEMD)을 거친 JEM 신호의 자기상관도로부터 제트엔진의 회전 주기를 산출한다. 그 후 DM(Divisor-Multiplier) 규칙 및 'Scoring' 개념을 JEM 스펙트럼 해석에 도입하여 최종적인 날개개수를 추정한다. 시뮬레이션 및 측정 JEM 신호로의 적용 결과를 통해 제안된 알고리즘이 정확하고 자동적인 제트엔진 정보 추출에 효과적임을 입증하였다.