• ETRI Journal
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• 제43권4호
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• pp.594-602
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• 2021

Recently, quantitative and repetitive inspections of the old urban area were conducted because many structures exceed their designed lifetime. The health of a building can be validated from the condition of the outer wall, while the slant angle of the wall widely serves as an indicator of urban regeneration projects. Mostly, the inspector directly measures the inclination of the wall or partially uses 3D point measurements using a static light detection and ranging (LiDAR). These approaches are costly, time-consuming, and only limited space can be measured. Therefore, we propose a mobile mapping system and automatic slant map generation algorithm, configured to capture urban environments online. Additionally, we use the LiDAR-inertial mapping algorithm to construct raw point clouds with gravity information. The proposed method extracts walls from raw point clouds and measures the slant angle of walls accurately. The generated slant angle map is evaluated in indoor and outdoor environments, and the accuracy is compared with real tiltmeter measurements.

• 정보처리학회논문지A
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• 제14A권1호
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• pp.73-76
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• 2007

단위원의 내부로부터 Jordan 영역으로의 등각사상을 구하는 것은 일반적으로 비선형방정식인 Theodorsen 방정식을 푸는 것으로 귀결된다. 저자는 이 비선형 방정식의 수치적 해법 중 가장 효율적인 방법으로 알려진 Wegmann의 해법에 저주파 필터를 적용하여 개선하고 새로운 산법의 수렴성을 이론적으로 증명한 바 있다[1, 2]. 또한 이 해법에 있어 참값을 모르더라도 오차평가가 가능한 방법을 제안하였다[3]. 본 논문에서는 참값을 모르더라도 오차평가가 가능한 연구결과를 이용하여 주어진 문제영역과 허용오차에 따라 자동으로 수치등각사상이 결정되는 알고리즘을 제안한다. 이 알고리즘에서는 지금까지 경험에 의존했었던 표본수와 저주파 필터 파라메터가 주어진 문제영역에 따라 자동으로 결정된다. 이것은 문제의 난이도가 문제영역의 변형에 의존한다는 전제로 문제영역의 모양을 결정하는 함수를 Fourier 급수로 전개, 분석하여 얻을 수 있다. 수치실험을 통해 그 유효성을 입증한다.

• 한국CDE학회논문집
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• 제11권3호
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• pp.211-222
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• 2006

In collaborative environment, it is necessary that the participants in collaboration should share the same understanding about the semantics of terms. For example, they should know that 'COMPONENT' and 'ITEM' are different word-expressions for the same meaning. In order to handle such problems in information sharing, an information system needs to automatically recognize that the terms have the same semantics. So we develop an algorithm mapping two terms based on their ontological definitions and their similarities. The proposed algorithm consists of four steps: the character matching, the inferencing, the definition comparing and the similarity checking. In the similarity checking step, we consider relation similarity and hierarchical similarity. The algorithm is very primitive, but it shows the possibility of semi-automatic mapping using ontology. In addition, we design a mapping procedure for a mapping system, called SOM (semantic ontology mapper).

• ETRI Journal
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• 제36권6호
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• pp.913-923
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• 2014

This paper proposes a global mapping algorithm for multiple robots from an omnidirectional-vision simultaneous localization and mapping (SLAM) approach based on an object extraction method using Lucas-Kanade optical flow motion detection and images obtained through fisheye lenses mounted on robots. The multi-robot mapping algorithm draws a global map by using map data obtained from all of the individual robots. Global mapping takes a long time to process because it exchanges map data from individual robots while searching all areas. An omnidirectional image sensor has many advantages for object detection and mapping because it can measure all information around a robot simultaneously. The process calculations of the correction algorithm are improved over existing methods by correcting only the object's feature points. The proposed algorithm has two steps: first, a local map is created based on an omnidirectional-vision SLAM approach for individual robots. Second, a global map is generated by merging individual maps from multiple robots. The reliability of the proposed mapping algorithm is verified through a comparison of maps based on the proposed algorithm and real maps.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.75-77
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• 2003

The spatial distribution of snow cover area is a crucial input to models of hydrology and climate in alpine and other seasonally snow covered areas.The objective in our study is to develop a rapidly automatic and high accuracy snow cover mapping algorithm applicable for the Tibetan Plateau which is the most sensitive about climatic change. Monitoring regional snow extent reqires higher temoral frequency-moderate spatial resolution imagery.Our algorithm is based AVHRR and MODIS data and will provide long-term fraction snow cover area map.We present here a technique is based on the multiple endmembers approach and by taking advantages of current approaches, we developed a technique for automatic selection of local reference spectral endmembers.

• 한국재난정보학회 논문집
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• 제12권2호
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• pp.181-188
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• 2016

본 연구에서는 시범지역의 CCTV 제원정보를 전수조사 하여 CCTV 위치, 주감시방향, 감시거리, 최대감시거리, Tele mode 화각, Wide mode 화각 등 CCTV 정보를 표출하기 위한 기본요소를 DB화 하였다. 조사된 CCTV제원 정보를 기초로 하여 공간정보 기반으로 도식화, 시각화 할 수 있는 자동 매핑 알고리즘 제안하였다. 알고리즘을 적용한 결과, 일부 연구지역의 CCTV 위치가 약 11% 중복된 것으로 분석되었고, CCTV 12대 가운데 중복된 CCTV는 총 5대로 도출되었다. 향후, 제시한 알고리즘을 기반으로 CCTV제원 정보를 지도에 표출하여 CCTV 위치 재설계 및 감시방향 변경 등 보다 과학적인 근거자료로 활용이 가능할 것이다.

• Journal of applied mathematics & informatics
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• 제20권1_2호
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• pp.595-602
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• 2006

Determinations of conformal map from the unit disk onto a Jordan region are reduced to solve the Theodorsen equation which is an integral equation for the boundary correspondence function. Among numerical conformal maps the Wegmann's method is well known as a Newton efficient one for solving Theodorsen equation. However this method has not so wide class of convergence. We proposed as an improved method for convergence by applying a low frequency filter to the Wegmann's method. In this paper, we investigate error analysis and propose an automatic algorithm based on this analysis.

• 한국멀티미디어학회논문지
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• 제12권8호
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• pp.1172-1181
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• 2009

전자의무기록(Electronic Medical Record, EMR)은 모든 검사 과정이 텍스트 기반의 데이터 형태로 저장되는 의료 분야의 의무기록 시스템을 의미한다. 그러나 국내의 전자의무기록 시스템은 각 의료기관마다 고유한 의료정보검사코드 형태를 이용하여 기록하는 방식으로 정보를 저장하기 때문에 병원 간의 의료검사 기록 형태들의 공유, 해석, 분석에 많은 문제점들을 가진다. 위의 문제들을 해결하기 위하여 표준화 되어 있지 않은 병원들의 검사코드들을 LOINC (Logical Observation Identifiers Names and Code)로 표준화하려는 연구들이 많다. 현재까지의 연구들은 로컬 의료정보검사코드를 수동으로 LOINC로 변환하는 방법이 연구되었다. 또한 대용량 의학 정보들을 다루기에 적절하지 않은 파일 기반에서 코드들을 관리하는 연구들이 이루어져왔다. 기존의 문제점을 해결하기 위하여 본 논문에서는 의료 용어 표준화 알고리즘을 제안하고, 구현하여 해결하였다. 또한, 대표적인 상용시스템이 가졌던 문제점인 검색어를 의사가 직접 생성해야 했던 부분을 LOINC 의 여섯 가지 자동 속성 추출 및 검색어 자동 생성 기능을 구현하여 해결하였다. 또한, 기존의 시스템들이 고려하지 않았던 대용량 데이터의 매핑 부분을 파일 시스템 기반이 아닌 데이터베이스 기반 검색 프레임웍을 구축하였다.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2002년도 Proceedings of International Symposium on Remote Sensing
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• pp.40-44
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• 2002

Precision correction is the process of geometrically aligning images to a reference coordinate system using GCPs(Ground Control Points). Many applications of remote sensing data, such as change detection, mapping and environmental monitoring, rely on the accuracy of precision correction. However it is a very time consuming and laborious process. It requires GCP collection, the identification of image points and their corresponding reference coordinates. At typical satellite ground stations, GCP collection requires most of man-powers in processing satellite images. A method of automatic registration of satellite images is demanding. In this paper, we propose a new algorithm for automatic precision correction by GCP chips and RANSAC(Random Sample Consensus). The algorithm is divided into two major steps. The first one is the automated generation of ground control points. An automated stereo matching based on normalized cross correlation will be used. We have improved the accuracy of stereo matching by determining the size and shape of match windows according to incidence angle and scene orientation from ancillary data. The second one is the robust estimation of mapping function from control points. We used the RANSAC algorithm for this step and effectively removed the outliers of matching results. We carried out experiments with SPOT images over three test sites which were taken at different time and look-angle with each other. Left image was used to select UP chipsets and right image to match against GCP chipsets and perform automatic registration. In result, we could show that our approach of automated matching and robust estimation worked well for automated registration.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권2호
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• pp.837-856
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• 2016

Underwater image enhancement has received considerable attention in last decades, due to the nature of poor visibility and low contrast of underwater images. In this paper, we propose a new automatic underwater image enhancement algorithm, which combines nonsubsampled contourlet transform (NSCT) domain enhancement techniques with the mechanism of the human visual system (HVS). We apply the multiscale retinex algorithm based on the HVS into NSCT domain in order to eliminate the non-uniform illumination, and adopt the threshold denoising technique to suppress underwater noise. Our proposed algorithm incorporates the luminance masking and contrast masking characteristics of the HVS into NSCT domain to yield the new HVS-based NSCT. Moreover, we define two nonlinear mapping functions. The first one is used to manipulate the HVS-based NSCT contrast coefficients to enhance the edges. The second one is a gain function which modifies the lowpass subband coefficients to adjust the global dynamic range. As a result, our algorithm can achieve contrast enhancement, image denoising and edge sharpening automatically and simultaneously. Experimental results illustrate that our proposed algorithm has better enhancement performance than state-of-the-art algorithms both in subjective evaluation and quantitative assessment. In addition, our algorithm can automatically achieve underwater image enhancement without any parameter tuning.