• 한국측량학회:학술대회논문집
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• 한국측량학회 2010년 춘계학술발표회 논문집
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• pp.277-280
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• 2010

There is a need to convert the old low- or medium-resolution satellite image-based thematic mapping to the high-resolution satellite image-based mapping of GSD 1m grade or lower. There is also a need to generate middle- or large-scale thematic maps of 1:5,000 or lower. In this study, the DEM and orthoimage is generated with the KOMPSAT-2 stereo image of Yuseong-gu, Daejeon Metropolitan City. By utilizing the orthoimage, automatic extraction experiments of land cover information are generated for buildings, roads and urban areas, raw land(agricultural land), mountains and forests, hydrosphere, grassland, and shadow. The experiment results show that it is possible to classify, in detail, for natural features such as the hydrosphere, mountains and forests, grassland, shadow, and raw land. While artificial features such as roads, buildings, and urban areas can be easily classified with automatic extraction, there are difficulties on detailed classifications along the boundaries. Further research should be performed on the automation methods using the conventional thematic maps and all sorts of geo-spatial information and mapping techniques in order to classify thematic information in detail.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2004년도 Proceedings of ISRS 2004
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• pp.132-135
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• 2004

Building information plays a key role in diverse applications such as urban planning, telecommunication and environment monitoring. Automatic building extraction has been a prime interest in the field of GIS and photogrammetry. In this paper, we presented an automatic approach for building extraction from lidar data. The proposed approach is divided into four processes: pre-processing, filtering, segmentation and building extraction. Experimental results showed that the proposed method detected most of buildings with less commission and omission errors.

• Journal of information and communication convergence engineering
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• 제20권2호
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• pp.113-124
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• 2022

News in the form of web data generates increasingly large amounts of information as unstructured text. The capability of understanding the meaning of news is limited to humans; thus, it causes information overload. This hinders the effective use of embedded knowledge in such texts. Therefore, Automatic Knowledge Extraction (AKE) has now become an integral part of Semantic web and Natural Language Processing (NLP). Although recent literature shows that AKE has progressed, the results are still behind the expectations. This study proposes a method to auto-extract surface knowledge from English news into a machine-interpretable semantic format (triple). The proposed technique was designed using the grammatical structure of the sentence, and 11 original rules were discovered. The initial experiment extracted triples from the Sri Lankan news corpus, of which 83.5% were meaningful. The experiment was extended to the British Broadcasting Corporation (BBC) news dataset to prove its generic nature. This demonstrated a higher meaningful triple extraction rate of 92.6%. These results were validated using the inter-rater agreement method, which guaranteed the high reliability.

• 한국컴퓨터정보학회논문지
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• 제21권2호
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• pp.79-88
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• 2016

In this paper, we propose an efficient automatic observation system for cloud amount and height observations. Observation system consists of clouds observations machinery, operational programs, cloud amount extraction program, cloud height extraction program, expert support programs. The experiment was conducted at the Daegwallyeong and Busan, through experimental observation confirmed the usefulness of the proposed system.

• 한국전자거래학회:학술대회논문집
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• 한국전자거래학회 2005년도 e-Biz World Conference 2005
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• pp.55-61
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• 2005

We will introduce a new web-based knowledge management system in progress, in which XML-based web information extraction and our structuring knowledge technologies are combined using ontology-based natural language processing. Our aim is to provide efficient access to heterogeneous information on the web, enabling users to use a wide range of textual and non textual resources, such as newspapers and databases, effortlessly to accelerate knowledge acquisition from such knowledge sources. In order to achieve the efficient knowledge management, we propose at first an XML-based Web information extraction which contains a sophisticated control language to extract data from Web pages. With using standard XML Technologies in the system, our approach can make extracting information easy because of a) detaching rules from processing, b) restricting target for processing, c) Interactive operations for developing extracting rules. Then we propose a structuring knowledge system which includes, 1) automatic term recognition, 2) domain oriented automatic term clustering, 3) similarity-based document retrieval, 4) real-time document clustering, and 5) visualization. The system supports integrating different types of databases (textual and non textual) and retrieving different types of information simultaneously. Through further explanation to the specification and the implementation technique of the system, we will demonstrate how the system can accelerate knowledge acquisition on the Web even for novice users of the field.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2002년도 ITC-CSCC -1
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• pp.196-199
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• 2002

We presented the automatic extraction technique of a biological internal organization from full-color continuous images. It was implemented using the localized homogeneousness of color intensity, and also using the continuity between neighboring images. Moreover, we set the "four-level status value" of area condition as a value showing "area possibility. This played important role of preventing a miss-judgement of area definition. These our approach had a beneficial effect on tracking color and shape change of the interest area in continuous extraction. As a resell we succeeded in extraction of mouse's stomach from continuous 50 images.

• 한국정보과학회논문지:소프트웨어및응용
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• 제31권4호
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• pp.447-456
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• 2004

정보추출은 한 문서에서 그 문서의 중심적 의미를 나타내는 특정 구성요소를 인식하여 추출하는 작업으로서, 이질적인 여러 정보소스로부터 균일화된 정보추출을 수행하기 위해서는 각 정보소스에 맞는 정보추출 규칙을 생성해야 한다. 기존 정보추출 규칙의 생성 방법에는 전문가에 의한 수동 생성 방법과 에이전트 프로그램에 의한 자동 생성 방법이 있는데, 수동 생성은 규칙의 정확성은 보장되나 확장성과 효율성에 문제가 있고, 자동 생성은 확장성은 있으나 규칙 생성 자체의 어려움과 생성된 규칙의 신뢰성이 문제점으로 대두된다. 본 논문에서는 이러한 두 가지 방법의 문제점을 보완하여 추출 규칙의 정확성과 확장성을 동시에 제공하기 위해 지도 학습(supervised teaming)을 적용한 정보추출 규칙 생성 기법을 제안한다. 본 논문에서 제시하는 방법은 사용자 인터페이스 에이전트를 사용하여 정보추출 규칙 생성을 위한 단서 정보를 사용자로부터 받고 이 정보를 바탕으로 에이전트가 XML로 표현된 규칙을 생성하는 것이다. 결과적으로 정보추출 규칙의 수동 생성과 자동 생성을 혼합한 형태가 된다. 사용자 인터페이스 에이전트는 규칙의 생성 뿐 아니라 기존의 규칙을 수정하거나 확장하는데도 이용된다. 구인 광고와 논문모집 공고와 관련된 정보소스에 대해 이 방법을 테스트한 결과 다른 기법에서 추출하지 못했던 정보를 추출할 수 있었고, 성능 면에서도 80% 이상의 정확도와 재현 율을 보였다. 본 시스템은 추후 정보 중재자 에이전트와 같은 응용 분야에 적용시킬 수 있을 것으로 기대한다.

• 감성과학
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• 제7권2호
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• pp.133-140
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• 2004

최근 대량으로 쏟아지는 감성공학 연구 결과와 논문들을 가치 있는 자료로 만들기 위해서는 감성 데이터가 산업 전반에 활용될 수 있도록 지표로 정리해야 한다. 본 논문에서는 "웹기반 감성 데이터 베이스 구축 및 보급에 관한 연구" 과제를 통해 작성된 감성 데이터 지표에 입각해서 앞으로 대량으로 출현할 감성공학 데이터의 지속적인 지표화를 위한 과정의 자동화를 제안한다. 문서 데이터의 지표화 작업이 자동요약과 유사하다는 점에 착안하여 자동지표화 시스템을 위한 기술들의 기초가 되는 정보유형 및 주요어 추출, 특성표현을 통한 정보문 추출에 대해 감성공학 코퍼스 분석을 통해 연구하고자 한다. 이는 감성공학 분야에서의 지식관리 시스템이나 자동요약 시스템에 활용될 수 있다. 활용될 수 있다.

• 대한원격탐사학회지
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• 제19권5호
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• pp.393-402
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• 2003

In times of the civil uses of commercialized high-resolution satellite imagery, applications of remote sensing have been widely extended to the new fields or the problem solving beyond traditional application domains. Transportation application of this sensor data, related to the automatic or semiautomatic road extraction, is regarded as one of the important issues in uses of remote sensing imagery. Related to these trends, this study focuses on automatic road extraction using Gradient Direction Profile Algorithm (GDPA) scheme, with IKONOS panchromatic imagery having 1 meter resolution. For this, the GDPA scheme and its main modules were reviewed with processing steps and implemented as a prototype software. Using the extracted bi-level image and ground truth coming from actual GIS layer, overall accuracy evaluation and ranking error-assessment were performed. As the processed results, road information can be automatically extracted; by the way, it is pointed out that some user-defined variables should be carefully determined in using high-resolution satellite imagery in the dense or low contrast areas. While, the GDPA method needs additional processing, because direct results using this method do not produce high overall accuracy or ranking value. The main advantage of the GDPA scheme on road features extraction can be noted as its performance and further applicability. This experiment study can be extended into practical application fields related to remote sensing.

• 제어로봇시스템학회논문지
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• 제14권5호
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• pp.432-437
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• 2008

This paper proposes a defect cell extraction algorithm for TFT-LCD auto-repair system. Auto defect search algorithm and automatic defect cell extraction method are very important for TFT-LCD auto repair system. In the previous literature[1], we proposed an automatic visual inspection algorithm of TFT-LCD. Based on the inspected information(defect size and defect axis, if defect exists) by the automatic search algorithm, defect cells should be extracted from the input image for the auto repair system. For automatic extraction of defect cells, we used a novel block matching algorithm and a simple filtering process in order to find a given reference point in the LCD cell. The proposed defect cell extraction algorithm can be used in all kinds of TFT-LCD devices by changing a stored template which includes a given reference point. Various experimental results show the effectiveness of the proposed method.