• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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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.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.50 no.4
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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.

• Journal of the Chungcheong Mathematical Society
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• v.27 no.2
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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.

• Honam Mathematical Journal
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• v.43 no.3
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• pp.561-570
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• 2021

In this paper, applying the bifurcation method and topological analysis, we investigate the global structures of solutions for one-dimensional Minkowski-curvature problems under certain behavior of nonlinear term near zero.

• Ocean Systems Engineering
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• v.8 no.3
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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.

• Proceedings of the IEEK Conference
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• 2001.09a
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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.

• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.3
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• pp.120-131
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• 2020

Water body detection using remote sensing based on machine interpretation of satellite image is efficient for managing water resource, drought and flood monitoring. In this study, water body detection with SAR satellite image based on machine learning was performed. However, non water body area can be misclassified to water body because of shadow effect or objects that have similar scattering characteristic comparing to water body, such as roads. To decrease misclassifying, 8 combination of morphology open filtered band, DEM band, curvature band and Cosmo-SkyMed SAR satellite image band about Mokpo region were trained to semantic segmentation machine learning models, respectively. For 8 case of machine learning models, global accuracy that is final test result was computed. Furthermore, concordance rate between landcover data of Mokpo region was calculated. In conclusion, combination of SAR satellite image, morphology open filtered band, DEM band and curvature band showed best result in global accuracy and concordance rate with landcover data. In that case, global accuracy was 95.07% and concordance rate with landcover data was 89.93%.

• Journal of the Korean Mathematical Society
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• v.53 no.4
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• pp.769-780
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• 2016

In this paper, we first prove some Liouville type theorems for elliptic inequalities on weighted manifolds which support a weighted Sobolev-type inequality. Secondly, applying the Liouville type theorems to self-shrinkers, we obtain some global rigidity theorems.

• Journal of the Institute of Convergence Signal Processing
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• v.14 no.4
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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.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.10a
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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.