• 산업공학
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• 제24권1호
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• pp.71-77
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• 2011

Design works consist of essential works and subsidiary works. Essential design works means designing creative ideas and productive ideas, while subsidiary design works means helping essential works those are making data tables and specification sheets, checking CAD data's integrity. Subsidiary design works forms the bulk of the whole design process and affects the time limit of delivery. Therefore we propose the automatic data matching system for CAD data's integrity. Proposed system is automatic system supporting subsidiary design works. The data matching system consists of three parts; 1) automatic generation of data tables 2) supporting module for checking CAD data's integrity between Drawings 3) automatic generation of spec. sheets. Developed system was tested in LCD equipment manufacture company and was found to be useful system.

• Spatial Information Research
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• 제15권2호
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• pp.181-187
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• 2007

수치고도자료를 생성하기 위해서, 항공기 혹은 위성에 탑재된 센서로부터 획득한 입체영상으로부터 자동상관매칭기법에 의해 고도값을 획득하는 연구가 수행되어 왔다. 자동상관매칭에 의한 결과값은 센서의 각도 및 수목 등에 의해 지표고도를 직접 추출하는데는 한계가 있고 영상내 지형지물 분포에 의해 고도값의 수정, 편집량이 결정된다. 본 연구는 수목차폐율과 수목고 자료가 자동상관매칭 고도 결과값에 미치는 영향을 분석하였다.

• 대한원격탐사학회지
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• 제40권2호
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• pp.219-228
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• 2024

Vessels can operate with their Automatic Identification System (AIS) turned off, prompting the development of strategies to identify them. Among these, utilizing satellites to collect radio frequency (RF) data in the absence of AIS has emerged as the most effective and practical approach. The purpose of this study is to develop a matching algorithm for RF with AIS data and find the RF's applicability to classify a suspected ship. Thus, a matching procedure utilizing three RF datasets and AIS data was employed to identify ships in the Yellow Sea and the Korea Strait. The matching procedure was conducted based on the proximity to AIS points, ensuring accuracy through various distance-based sections, including 2 km, 3 km, and 6 km from the AIS-based estimated points. Within the RF coverage, the matching results from the first RF dataset and AIS data identified a total of 798 ships, with an overall matching rate of 78%. In the cases of the second and third RF datasets, 803 and 825 ships were matched, resulting in an overall matching rate of 84.3% and 74.5%, respectively. The observed results were partially influenced by differences in RF and AIS coverage. Within the overlapped region of RF and AIS data, the matching rate ranged from 80.2% to 98.7%, with an average of 89.3%, with no duplicate matches to the same ship.

• ETRI Journal
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• 제28권2호
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• pp.162-174
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• 2006

Several photogrammetric and geographic information system applications such as surface matching, object recognition, city modeling, environmental monitoring, and change detection deal with multiple versions of the same surface that have been derived from different sources and/or at different times. Surface registration is a necessary procedure prior to the manipulation of these 3D datasets. This need is also applicable in the field of medical imaging, where imaging modalities such as magnetic resonance imaging (MRI) can provide temporal 3D imagery for monitoring disease progression. This paper will present a general automated surface registration procedure that can establish correspondences between conjugate surface elements. Experimental results using light detection and ranging (LIDAR) and MRI data will verify the feasibility, robustness, and accuracy of this approach.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2004년도 Proceedings of ISRS 2004
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• pp.220-223
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• 2004

Automatic image registration is an essential element of remote sensing because remote sensing system generates enormous amount of data, which are multiple observations of the same features at different times and by different sensor. The general process of automatic image registration includes three steps: 1) The extraction of features to be used in the matching process, 2) the feature matching strategy and accurate matching process, 3) the resampling of the data based on the correspondence computed from matched feature. For step 2) and 3), we have developed an algorithms for automated registration of satellite images with RANSAC(Random Sample Consensus) in success. However, for step 1), There still remains human operation to generate GCP Chips, which is time consuming, laborious and expensive process. The main idea of this research is that we are able to automatically generate GCP chips with comer detection algorithms without GPS survey and human interventions if we have systematic corrected satellite image within adaptable positional accuracy. In this research, we use SUSAN(Smallest Univalue Segment Assimilating Nucleus) algorithm in order to detect the comer. SUSAN algorithm is known as the best robust algorithms for comer detection in the field of compute vision. However, there are so many comers in high-resolution images so that we need to reduce the comer points from SUSAN algorithms to overcome redundancy. In experiment, we automatically generate GCP chips from IKONOS images with geo level using SUSAN algorithms. Then we extract reference coordinate from IKONOS images and DEM data and filter the comer points using texture analysis. At last, we apply automatically collected GCP chips by proposed method and the GCP by operator to in-house automatic precision correction algorithms. The compared result will be presented to show the GCP quality.

• 대한의용생체공학회:의공학회지
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• 제18권1호
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• pp.9-16
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• 1997

We develop an automatic imaging matching technique for combining portal image and simulator image for improvements in localization of treatment in radiation therapy. Fusion of images from two imaging modalities is treated as follows. We archive images thxough a frame-yabber. The simulator and portal images are edge detected and enhanced with interpolated adaptive histouam equalization and combined using geometrical parameters relating the coordinates of two image data sets which are calculated using Fourier descriptors. We don't use any kind of imaging markers for patient's convenience. clinical use of this image matching technique for treatment planning will result in improvements in localization of treatment volumes and critical structures. These improvements will allow greater sparing of normal tissues and more precise delivery of energy to the desired irradiation volume.

• 대한원격탐사학회지
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• 제26권1호
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• pp.39-45
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• 2010

본 연구는 지상라이다 자료의 점군간 자동정합을 위해 인접한 두 점군 자료와 함께 획득되는 2차원의 강도영상 자료로부터, 2개 영상에서 동시에 관측되는 특징점들을 이용하여 SIFT 알고리즘에 의해 공액점을 선정하였다. 또한 매칭 오류점 배제를 위해 RANSAC 알고리즘을 적용하여 정합 정확도 향상을 도모하였다. 두 점군간의 변환식 매개변수인 3차원 회전변환 각과 수직/수평 이동량을 계산, 그 결과를 기존 수작업에 의한 결과와 비교하였다. 건국대학교 이과대학 건물을 대상으로 실험한 결과, 자동매칭을 통한 변환매개변수와 수작업으로 한 변환매개변수의 차이는 X, Y, Z, 방향으로 각각 0.011m, 0.008m, 0.052m로서 자동정합 자료의 활용이 가능하다고 판단하였다.

• 한국측량학회지
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• 제33권1호
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• pp.45-52
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• 2015

공간정보 제작의 다원화로 인하여 다양한 수치지도들이 여러 공공기관 및 기업에서 제작됨에 따라 데이터의 상호 운용성이 점점 중요해지고 있다. 이에 본 연구에서는 계층적 매칭 기법을 활용한 이종 수치지도의 건물 데이터 자동 정합기법을 제안하였다. 먼저 수치지도를 가구계 기반으로 분할한 후 ICP 알고리즘을 활용한 건물 기하보정을 1차적으로 수행하였다. 대응 가능한 건물쌍의 중첩면적 유사도를 평가하여 대응 건물을 결정하고 Otsu 이진 임계화를 수행하여 매칭 비매칭에 대한 임계값을 자동으로 설정하였다. 1차 매칭이 완료된 후 임계값과 비슷한 유사도를 가지는 건물들을 오매칭 후보군으로 추출하여 개별 건물에 대한 ICP 알고리즘 기반의 기하보정을 다시 수행하고 형태학적 인자인 회전각 함수분석을 추가 적용하여 정합여부를 재판단하였다. 실험평가를 위해 제안된 알고리즘을 대표적인 공공분야 수치지도인 도로명주소지도와 수치지형도 2.0의 건물 데이터에 적용하고 활용성을 평가하였다. 정확도 평가결과 매칭 건물 및 비매칭 건물에 대한 F 측정치가 각각 2%와 17% 향상되었으며 이를 통해 본 연구에서 제안한 알고리즘이 이종 수치지도 건물 정합에 효과적으로 적용될 수 있음을 확인하였다.

• 한국ITS학회 논문지
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• 제16권5호
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• pp.109-120
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• 2017

자동차 운전면허 시험에서 객관적인 평가가 중요하다. 특히 도로 주행시험은 실제 도로에서 운전능력, 규칙준수, 상황판단능력 등을 종합적으로 시험하는 것이다. 이를 위하여 본 논문에서는 GPS와 센서 데이터 및 기기조작 정보를 활용하여 운전면허 시험의 자동채점시스템을 제안한다. 자동채점 시스템은 차량탑재장치, 채점용단말, 데이터 제어장치, 데이터 저장 및 처리를 위한 서버로 구성되어 있다. 차량탑재장치는 차량에 설치된 센서 데이터를 수집한다. 채점 단말은 차량탑재장치로부터 받은 데이터를 활용하여 기준에 따라 자동채점 한다. 또한 이동 중에 GPS 오차로 인하여 차량이 도로를 벗어나 표현되므로 지도매칭 기법과 경로이탈 및 복귀 알고리즘을 적용하였다. 이 시스템은 기존 시험 채점 방식과 달리 자동 채점이 가능하며, 시험 결과에서 정확한 차량위치 표시와 GPS 음영지역을 벗어났을 때 10초 이내로 경로 복귀를 하였다. 이 시스템은 도로 주행 교육에도 활용될 수 있을 것으로 기대된다.

• 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.