• 제목/요약/키워드: classification boundaries

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화성암에서의 결정경계: 성인적 분류와 기하학적 특성 (Cystal Boundaries in Igneous Roks: Genetic Classification and Geometric Features)

  • Park, Youngdo
    • 암석학회지
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    • 제4권2호
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    • pp.168-177
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    • 1995
  • Crystal boundaries in igneous rocks are genetically classified in order to predict the geometric patterns of the boundaries which may aid deciphering the textural code in igneous rocks. Crystal boundaries may be formed by two end-member processes;(1) mechanical and (2) chemical removal of interstitial melt. Mechanical removal of the melt will form displacement impingement boundaries, while chemical removal of the melt will form growth impingement boundaries. The positions of boundaries relative to the material points may be affected by secondary processes such as (1) migration and (2) dissolution. The geometric features of crystal boundaries, suggested in this study, may be useful when studying igneous textures and processes, although it may be impossible to determine the suggested features with the analytical techniques currently avilable.

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퍼지 분할을 위한 분류 경계의 추출과 패턴 분류에의 응용 (Extraction of Classification Boundary for Fuzzy Partitions and Its Application to Pattern Classification)

  • 손창식;서석태;정환묵;권순학
    • 한국지능시스템학회논문지
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    • 제18권5호
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    • pp.685-691
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    • 2008
  • 퍼지 규칙기반 분류 시스템에서 위한 퍼지 분할 경계들의 선택은 중요하고 어려운 문제이다. 그래서 이들을 효과적으로 결정하기 위해서 신경망, 유전자알고리즘 등과 같은 학습과정에 기반을 둔 다양한 방법들이 제안되었고, 이전 연구에서는 이들 방법에 대한 문제점을 지적하고 이를 개선하기 위하여 중첩 형태에서 퍼지 분할을 결정할 수 있는 방법에 대해서 논의하였다. 본 논문에서는 이전 연구의 방법을 3가지 형태의 분류 경계들, 즉 비중첩, 중첩, 1점 인접 형태로 확장하였다. 또한 이들을 학습에 의존하지 않고 주어진 데이터로부터 얻어진 통계적 정보만을 사용하여 결정하는 방법을 제안하고, 이를 패턴 분류 문제에 적용하여 제안된 방법의 효용성을 보인다.

퍼지 규칙기반 분류시스템에서 퍼지 분할의 선택방법 (Selection Method of Fuzzy Partitions in Fuzzy Rule-Based Classification Systems)

  • 손창식;정환묵;권순학
    • 한국지능시스템학회논문지
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    • 제18권3호
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    • pp.360-366
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    • 2008
  • 퍼지 규칙기반 분류 시스템에서 초기의 퍼지 분할은 주어진 데이터가 가진 속성들의 도메인을 고려함으로서 결정되어지고, 최적의 분류 경계면은 초기에 정의된 퍼지 분할의 파라미터들을 조정함으로서 찾을 수 있다. 본 논문에서는 학습과정들을 사용하지 않고 패턴분류의 성능을 최대화하기 위해 통계적 정보에 기반을 둔 퍼지 분할의 선택방법을 제안한다. 제안된 방법에서 통계적 정보는 주어진 수치적인 데이터로부터 각 입력 속성의 '불확실성 영역', 즉 패턴분류문제에서 분류 경계면이 결정되는 영역을 추출하기 위해 사용되었다. 또한 통계적인 정보에 의해서 생성된 퍼지 분할구간에 대응하는 후보 규칙들을 추출하기 위한 방법과 그 후보 규칙들 간의 커플링 문제를 최소화하기 위한 방법도 추가적으로 논의하였다. 실험에서는 제안된 방법의 효용성을 보이기 위해 IRIS와 New Thyroid Cancer 데이터를 사용한 기존 패턴분류 방법들과의 분류 정확성을 비교하였고, 그 결과들로부터 제안된 방법이 기존의 방법들보다 더 좋은 분류 정확성을 제공함을 확인할 수 있었다.

2차원 자동요소분할 프로그램 개발에 관한 연구 (A Study on the Two-Dimensional Automatic Mesh Generation Programming)

  • 조명철;유형선
    • 한국정밀공학회지
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    • 제9권2호
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    • pp.44-51
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    • 1992
  • This paper is concerned with the propram of the automatic mesh generation for 2-dimensional domain which contains the curved boundaries and holes. This program treats a new vertical-line drawing method. This method starts with 4-subdivisions of problem domain and the classification of the cross points of grid lines and boundaries. The new node is generated by the vertical line to the line connecting the two intersections of a boundary and two grid lines in gereral. And the node very close to the boundary is moved to the boundary. The automatic mesh generation composed of only rectangular elements is achieved by this procedure. The boundaries are piecewise-curves composed of lines, circles, arcs, and free curves. The free curves are generated by B-Spline form. Although there were some bad elements for the complex boundary, it was possible to obtain the acceptible rectangular elements for the given boundaries.

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2차원 자동요소분할 프로그램 개발에 관한 연구 (A study on the two-dimensional automatic mesh generation programming)

  • 조명철;유형선
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1991년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 22-24 Oct. 1991
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    • pp.720-725
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    • 1991
  • This paper is concerned with the program of the automatic mesh generation for 2-dimensional domain which contains the curved boundaries and holes. This program treats a new vertical - line drawing method. This method starts with 4-subdivisions of problem domain and the classification of the cross points of grid lines and boundaries. And the new node is generated by the vertical line to the line connecting the two intersections of a boundary and two grid lines in general. The boundaries are piecewise-curves composed of lines, circles, arcs, and free curves. The free curves are generated by B-Spline form. Although there were some bad elements for the complex boundary, it was possible to obtain the acceptable elements for the given boundaries. The results of automatic mesh generation can be verified directly by drawing on the computer monitor in executing the program. And it is possible to add the processes - that is, editing, hard copying, etc - using the script file in Auto-CAD.

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무감독 SVM 분류 기법을 통한 드론 영상 경계 박스 내 차량 자동 추출 연구 (A Study on Automatic Vehicle Extraction within Drone Image Bounding Box Using Unsupervised SVM Classification Technique)

  • 염준호
    • 토지주택연구
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    • 제14권4호
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    • pp.95-102
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    • 2023
  • 도시 지역에서 객체를 탐지하기 위해 드론 고해상도 영상에 기계 학습 알고리즘을 적용하는 다양한 연구가 진행되었다. 그러나 대부분의 차량 추출 연구는 인스턴스 세그멘테이션 대신 경계 박스로 차량을 탐지하여 차량의 방향이나 정확한 경계를 알 수 없다는 한계점이 있다. 인스턴스 세그멘테이션은 개별 개체를 훈련하기 위한 노동 집약적인 레이블링 작업을 필요로 하므로, 차량 추출을 위해 자동 무감독 인스턴스 세그멘테이션을 수행하는 방법에 대한 연구가 필요하다. 따라서 본 연구에서는 드론 영상의 차량 경계 박스에 대해 무감독 SVM 분류 기반의 차량 추출 기법을 제안하였다. 연구 결과, 차량을 89% 정확도로 추출할 수 있음을 확인하였으며 차량 내의 분광 특성이 크게 다른 경우에도 차량을 추출할 수 있음을 확인하였다.

TECHNIQUE OF EXTRACTING BUILDING BOUNDARIES FROM SEGMENTED ALS POINTS

  • Lee, Jeong-Ho;Kim, Yong-II
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2008년도 International Symposium on Remote Sensing
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    • pp.141-144
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    • 2008
  • Many studies have been conducted on extracting buildings from ALS(Airborne Laser Scanning) data. After segmentation or classification of building points, additional steps such as generalization is required to get straight boundary lines that better approximate the real ones. In much research, orthogonal constraints are used to improve accuracies and qualities. All the lines of the building boundaries are assumed to be either parallel or perpendicular mutually. However, this assumption is not valid in many cases and more complex shapes of buildings have been increased. A new algorithm is presented that is applicable to various complex buildings. It consists of three steps of boundary tracing, grouping, and regularization. The performance of our approach was evaluated by applying the algorithm to some buildings and the results showed that our proposed method has good potential for extracting building boundaries of various shapes.

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Evaluation of DoP-CPD Classification Technique and Multi Looking Effects for RADARSAT-2 Images

  • Lee, Kyung-Yup;Oh, Yi-Sok;Kim, Youn-Soo
    • 대한원격탐사학회지
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    • 제28권3호
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    • pp.329-336
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    • 2012
  • This paper give further assessment on the original DoP-CPD classification scheme. This paper provides some additional comparative study on the DoP-CPD with H/A/alpha classifier in terms of multi look effects and classification performances. The statistics and multi looking effects of the DoP and CPD were analyzed with measured polarimetric SAR data. DoP-CPD is less sensitive to the number of averaging pixels than the entropy-alpha technique. A DoP-CPD diagram with appropriate boundaries between six different classes was then developed based on the data analysis. A polarimetric SAR image DoP-CPD classification technique is verified with C-band polarimetric RADARSAT-2 images.

Object-oriented Classification of Urban Areas Using Lidar and Aerial Images

  • Lee, Won Hee
    • 한국측량학회지
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    • 제33권3호
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    • pp.173-179
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    • 2015
  • In this paper, object-based classification of urban areas based on a combination of information from lidar and aerial images is introduced. High resolution images are frequently used in automatic classification, making use of the spectral characteristics of the features under study. However, in urban areas, pixel-based classification can be difficult since building colors differ and the shadows of buildings can obscure building segmentation. Therefore, if the boundaries of buildings can be extracted from lidar, this information could improve the accuracy of urban area classifications. In the data processing stage, lidar data and the aerial image are co-registered into the same coordinate system, and a local maxima filter is used for the building segmentation of lidar data, which are then converted into an image containing only building information. Then, multiresolution segmentation is achieved using a scale parameter, and a color and shape factor; a compactness factor and a layer weight are implemented for the classification using a class hierarchy. Results indicate that lidar can provide useful additional data when combined with high resolution images in the object-oriented hierarchical classification of urban areas.

New Unsupervised Classification Technique for Polarimetric SAR Images

  • Oh, Yi-Sok;Lee, Kyung-Yup;Jang, Ge-Ba
    • 대한원격탐사학회지
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    • 제25권3호
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    • pp.255-261
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    • 2009
  • A new polarimetric SAR image classification technique based on the degree of polarization (DoP) and the co-polarized phase-difference (CPD) is presented in this paper. Since the DoP and the CPD of a scattered wave provide information on the randomness of the scattering and the type of scattering mechanisms, at first, the statistics of the DoP and CPD are examined with measured polarimetric SAR image data. Then, a DoP-CPD diagram with appropriate boundaries between six different classes is developed based on the SAR image. The classification technique is verified using the JPL AirSAR and ALOS PALSAR polarimetric data. The technique may have capability to classify an SAR image into six major classes; a bare surface, a village, a crown-layer short vegetation canopy, a trunk-layer short vegetation canopy, a crown-layer forest, and a trunk-dominated forest.