• 제목/요약/키워드: Global curvature

검색결과 68건 처리시간 0.023초

AUTOMATIC SCALE DETECTION BASED ON DIFFERENCE OF CURVATURE

  • Kawamura, Kei;Ishii, Daisuke;Watanabe, Hiroshi
    • 한국방송∙미디어공학회:학술대회논문집
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    • 한국방송공학회 2009년도 IWAIT
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    • pp.482-486
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    • 2009
  • Scale-invariant feature is an effective method for retrieving and classifying images. In this study, we analyze a scale-invariant planar curve features for developing 2D shapes. Scale-space filtering is used to determine contour structures on different scales. However, it is difficult to track significant points on different scales. In mathematics, curvature is considered to be fundamental feature of a planar curve. However, the curvature of a digitized planar curve depends on a scale. Therefore, automatic scale detection for curvature analysis is required for practical use. We propose a technique for achieving automatic scale detection based on difference of curvature. Once the curvature values are normalized with regard to the scale, we can calculate difference in the curvature values for different scales. Further, an appropriate scale and its position are detected simultaneously, thereby avoiding tracking problem. Appropriate scales and their positions can be detected with high accuracy. An advantage of the proposed method is that the detected significant points do not need to be located in the same contour. The validity of the proposed method is confirmed by experimental results.

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ECG 신호의 global curvature를 이용한 ST-T 에피소드 검출 (Detection of ST-T Episode Based on the Global Curvature of Isoelectric Level in ECG)

  • 강동원;전대근;이경중;윤형로
    • 대한전기학회논문지:시스템및제어부문D
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    • 제50권4호
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    • pp.201-207
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    • 2001
  • This paper describes an automated detection algorithm of ST-T episodes using global curvature which can connect the isoelectric level in ECG and can eliminate not only the slope of ST segment, but also difference of the baseline and global curve. This above method of baseline correction is very faster than the classical baseline correction methods. The optimal values of parameters for baseline correction were found as the value having the highest detection rate of ST episode. The features as input of backpropagation Neural Network were extracted from the whole ST segment. The European ST-T database was used as training and test data. Finally, ST elevation, ST depression and normal ST were classified. The average ST episode sensitivity and predictivity were 85.42%, 80.29%, respectively. This result shows the high speed and reliability in ST episode detection. In conclusion, the proposed method showed the possibility in various applications for the Holter system.

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A NOTE ON SURFACES IN THE NORMAL BUNDLE OF A CURVE

  • Lee, Doohann;Yi, HeungSu
    • 충청수학회지
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    • 제27권2호
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    • pp.211-218
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    • 2014
  • In 3-dimensional Euclidean space, the geometric figures of a regular curve are completely determined by the curvature function and the torsion function of the curve, and surfaces are the fundamental curved spaces for pioneering study in modern geometry as well as in classical differential geometry. In this paper, we define parametrizations for surface by using parametric functions whose images are in the normal plane of each point on a given curve, and then obtain some results relating the Gaussian curvature of the surface with curvature and torsion of the given curve. In particular, we find some conditions for the surface to have either nonpositive Gaussian curvature or nonnegative Gaussian curvature.

Effects of geometric shape of LWSCR (lazy-wave steel catenary riser) on its global performance and structural behavior

  • Kim, Seungjun;Kim, Moo-Hyun
    • Ocean Systems Engineering
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    • 제8권3호
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    • pp.247-279
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    • 2018
  • This study aims to investigate the behavioral characteristics of the LWSCR (lazy-wave steel catenary riser) for a turret-moored FPSO (Floating Production Storage Offloading) by using fully-coupled hull-mooring-riser dynamic simulation program in time domain. In particular, the effects of initial geometric profile on the global performance and structural behavior are investigated in depth to have an insight for optimal design. In this regard, a systematic parametric study with varying the initial curvature of sag and arch bend and initial position of touch down point (TDP) is conducted for 100-yr wind-wave-current (WWC) hurricane condition. The FPSO motions, riser dynamics, constituent structural stress results, accumulated fatigue damage of the LWSCR are presented and analyzed to draw a general trend of the relationship between the LWSCR geometric parameters and the resulting dynamic/structural performance. According to this study, the initial curvature of the sag and arch bend plays an important role in absorbing transferred platform motions, while the position of TDP mainly affects the change of static-stress level.

Boundary Extraction Using Statistical Edge and Curvature Model

  • Park, Hae-Chul;Lee, J. S.;H. C. Shin;J. H. Cho;Kim, S. D.
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2001년도 제14회 신호처리 합동 학술대회 논문집
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    • pp.403-406
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    • 2001
  • We propose an algorithm for extracting the boundary of an object. In order to take full advantage of global shape, our approach uses global shape parameters derived from Point Distribution Model (PDM). Unlike PDM, the proposed method models global shape using curvature as well as edge. The objective function of applying the shape model is formulated using Bayesian rule. We can extract the boundaries of an object by evaluating iteratively the solution maximizing the objective function. Experimental results show that the proposed method can reduce computation cost than the PDM and it is robust to noise, pose variation, and some occlusion.

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SAR 위성 영상을 이용한 수계탐지의 최적 머신러닝 밴드 조합 연구 (Selection of Optimal Band Combination for Machine Learning-based Water Body Extraction using SAR Satellite Images)

  • 전현균;김덕진;김준우;수레시 크리쉬난;김재언;김택인;정승환
    • 한국지리정보학회지
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    • 제23권3호
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    • pp.120-131
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    • 2020
  • 인공위성 영상을 기반으로 한 기계판독(machine interpretation) 원격탐사 수계 탐지는 효율적인 수자원 관리, 가뭄 탐지, 홍수 모니터링 등에 큰 도움이 된다. 따라서 본 연구에서는 머신러닝을 기반으로 한 SAR 위성 영상 기반 수계 탐지를 시행하였다. 그러나 SAR 위성 영상만을 사용하였을 경우 음영 효과 또는 도로 등의 수계와 비슷한 산란특성을 가지는 물체로 인하여 비수계가 수계로 오탐지 될 수 있다. 이러한 오탐지를 줄이기 위하여 목포 지역을 촬영한 Cosmo-SkyMed SAR 위성 영상에 모폴로지(Morphology)의 open 연산을 거친 밴드와 DEM(수치표고모델) 밴드, Curvature(곡률) 밴드를 조합하여 중첩한 8가지 경우에 대하여 의미 분할 기법 머신러닝 모델을 학습시켰다. 8가지 머신러닝 모델에 대한 최종 테스트 결과인 Global Accuracy를 구하였으며, 목포 지역의 토지피복지도와의 일치율 역시 비교하였다. 그 결과 SAR 위성 영상과 모폴로지 open 필터를 적용한 밴드, DEM 밴드, Curvature 밴드를 모두 사용한 경우가 Global Accuracy뿐만 아니라 토지피복지도와의 일치율 역시 가장 높음을 확인할 수 있었다. 이때 Global Accuracy는 95.07%였으며, 토지피복지도와의 일치율은 89.93%로 나타났다.

Multimodal Curvature Discrimination of 3D Objects

  • Kim, Kwang-Taek;Lee, Hyuk-Soo
    • 융합신호처리학회논문지
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    • 제14권4호
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    • pp.212-216
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    • 2013
  • As virtual reality technologies are advanced rapidly, how to render 3D objects across modalities is becoming an important issue. This study is therefore aimed to investigate human discriminability on the curvature of 3D polygonal surfaces with focusing on the vision and touch senses because they are most dominant when explore 3D shapes. For the study, we designed a psychophysical experiment using signal detection theory to determine curvature discrimination for three conditions: haptic only, visual only, and both haptic and visual. The results show that there is no statistically significant difference among the conditions although the threshold in the haptic condition is the lowest. The results also indicate that rendering using both visual and haptic channels could degrade the performance of discrimination on a 3D global shape. These results must be considered when a multimodal rendering system is designed in near future.

다중 스케일 평균곡률 기반 전역 희소치를 이용한 메쉬 돌출 정의 (Mesh Saliency using Global Rarity based on Multi-Scale Mean Curvature)

  • 전지영;권영수;최유주
    • 한국정보처리학회:학술대회논문집
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    • 한국정보처리학회 2015년도 추계학술발표대회
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    • pp.1579-1580
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    • 2015
  • 본 논문에서는 3차원 메쉬 모델의 중요 영역을 표현하는 메쉬 돌출맵(mesh saliency map)을 생성하기 위하여 다중 스케일 평균 곡률 (multi-scale mean curvature)을 기반으로 정의된 전역 희소치(global rarity)를 이용하는 방법을 제안한다. 제안 방법에서는 우선, 메쉬 모델의 지역 영역 특성을 정의하기 위하여 기존 관련 연구들에서 많이 사용하고 있는 가우시안 가중치 평균곡률(Gaussian-weighted mean curvature)을 5단계 서로 다른 스케일에서 정의하고, 메쉬의 각 정점(vertex)에 대하여 중심주변 연산자(center-surround operator)를 적용하여 5단계 지역 돌출특성(local saliency)을 정의한다. 주어진 메쉬 모델의 전역 희소치를 구하기 위하여 메쉬의 모든 정점쌍 (vertex pair)에 대하여 5단계 지역 돌출 특성 공간에서의 거리를 계산하고, 각 정점별로 5단계 지역 돌출 특성 공간에서의 다른 정점과의 거리의 합으로 전역 희소치를 정의한다. 이러한 전역 희소치를 각 정점의 메쉬 돌출치로 정의한다. 서로 다른 형태의 3차원 모델에 대하여 제안방법에 의한 메쉬 돌출맵과 지역 특성만을 고려한 기존 메쉬 돌출맵을 생성하여 중요 영역 표현 결과를 비교 분석한다.