• Title/Summary/Keyword: 3점 근사화

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Visualization of Geographic Information Using Contour Simplification (등고선 간략화에 의한 지리정보의 복원 가시화)

  • Kim, Jong-Bok;Koh, Chan
    • Proceedings of the Korean Information Science Society Conference
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    • 1998.10c
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    • pp.647-649
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    • 1998
  • 본 논문에서는 다각 근사화 방법과 래스터 기반 연산 알고리즘을 이용하여 평면 지도상에 나타난 등고선을 3차원 가시화(Visualization)하여 보여준다. 다각 근사화 방법은 입력한 등고선에 대한 특징을 반영할 수 있는 최소한의 선형구분 오차 임계값을 이용하여 등고선에 근사화 시킨 것으로 저장 데이터의 양을 축소할 수 있다. 래스터 기반 알고리즘은 이웃한 두 개의 등고선 내부점의 높이 값을 그 점에서 두 등고선까지의 최단거리 및 등고선의 높이값을 변수로 하는 선형보간식으로 정의하고, 거리변환 연산을 도입하여 계산하는 알고리즘으로 구현이 용이하며, 간단한 계산만을 수행하기 때문에 처리 방법이 간단하다는 장점을 갖는다. 본 논문에서는 래스터 방법만을 이용한 복원보다 자료의 양이 감소함을 보였고, 전체 처리과정의 간단함과, 3차원 가시화된 등고선을 그래프 좌표상의 X, Y, Z축으로 원하는 각도만큼씩 회전시키며 관찰 할 수 있도록 하였다. 본 연구를 통해 지형의 특징을 원형 등고선과 유사하게 유지하면서, 데이터 양을 축소하고 계산식을 간략화된 효과적인 지형정보 시각화를 보여주었다.

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Implementation of a 3D Mesh Editor for Smooth Surface Fitting (부드러운 곡면 근사를 위한 3차원 메쉬 편집기의 구현)

  • 신복숙;우영운
    • Proceedings of the Korea Multimedia Society Conference
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    • 2001.06a
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    • pp.425-428
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    • 2001
  • 본 논문에서 구현한 메쉬 편집기는 편집할 메쉬의 몇몇 점을 편집할 경우, 편집 정보가 그 점에 이웃한 점들에게도 영향을 미치게 되어, 편집 결과가 근사된 부드러운 곡면으로 표현하도록 하는 데 있다. 그러기 위해서는 3차원의 메쉬를 2차원 평면으로 매핑할 때, 매핑되는 원래의 메쉬의 모양이 크게 변형되지 않도록 하여야 하는데, 여기에 모양 유지 매개 변수화 방법을 사용하고 있다. 편집에 사용된 점의 편집 정보는 2차원 평면 다각형 안에 있는 서로 대응되는 점으로 매핑 되고, B-스플라인 보간으로 편집 정보는 2차 평면 안에 있는 다른 점들에게도 영향을 주게 된다. 이런 결과는 3차원 메쉬로 환원되어 부드럽게 근사된 곡면으로 표현된다.

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High Precision Logarithm Converters for Binary Floating Point Approximation Operations (고속 부동소수점 근사연산용 로그변환 회로)

  • Moon, Sang-Ook
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2010.05a
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    • pp.809-811
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    • 2010
  • In most floating-point operations related with 3D graphic applications for mobile devices, properly approximated data calculations with reduced complexity and low power are preferable to exactly rounded floating-point operations with unnecessary preciseness with cost. Among all the sophisticated floating-point arithmetic operations, multiplication and division are the most complicated and time-consuming, and they can be transformed into addition and subtraction repectively by adopting the logarithmic conversion. In this process, the most important factor for performance is how high we can make an approximation of the logarithm conversion. In this paper, we cover the trends in studying the logarithm conversion circuit designs. We also discuss the important factor in design issues and the applicable fields in detail.

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Geometric Model Decimation Method for Salient Features (돌출된 특징을 위한 기하 모델 단순화 방법)

  • Kim, Soo-Kyun;An, Sung-Og
    • The Journal of Korean Association of Computer Education
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    • v.11 no.4
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    • pp.85-93
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    • 2008
  • This paper proposes a method for generating low-level geometric models with retaining salient features during decimation. Our method employs feature extraction technique for extracting feature lines defined via curvature derivatives on the model (we divide features into ridges and valleys). We add the extraction method to simplification technique (Feature Quadric Error Metric) for making coarse model with features. This paper clearly shows that experimental results have better quality and smaller geometric error than previous methods.

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Three-Dimensional Shape Measurement of a Specular Object by LED Array Reflection (LED Array의 반사영상에 의한 경면체의 3차원 형상 측정)

  • Kim, Jee Hong
    • Korean Journal of Optics and Photonics
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    • v.27 no.1
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    • pp.41-46
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    • 2016
  • An optical method to measure the three-dimensional (3D) shape of a surface with specular reflection is proposed. The proposed method is based on the analysis of the geometric path of the light from a point source, and the relative displacements of points in the reflection image. The 3D shape of a concave mirror is shown to be determined approximately via experiments, where the vision system consists of LED array illumination, a half-mirror, and an imaging sensor.

On a robust analysis of variance based on winsorization (윈저화를 이용한 로버스트 분산분석)

  • 성내경
    • The Korean Journal of Applied Statistics
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    • v.8 no.1
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    • pp.119-131
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    • 1995
  • Based on Monte-Carlo simulation results we propose a robust analysis of variance procedure by utilizing trimmed mean and Winsorized variance. We deal with mainly the one-way classification case. We evaluate the empirical distribution of a pseudo-F statistic based on symmetrically Winsorized sum of squares when the population is normally distributed.

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Accuracy Analysis of Fixed Point Arithmetic for Hardware Implementation of Binary Weight Network (이진 가중치 신경망의 하드웨어 구현을 위한 고정소수점 연산 정확도 분석)

  • Kim, Jong-Hyun;Yun, SangKyun
    • Journal of IKEEE
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    • v.22 no.3
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    • pp.805-809
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    • 2018
  • In this paper, we analyze the change of accuracy when fixed point arithmetic is used instead of floating point arithmetic in binary weight network(BWN). We observed the change of accuracy by varying total bit size and fraction bit size. If the integer part is not changed after fixed point approximation, there is no significant decrease in accuracy compared to the floating-point operation. When overflow occurs in the integer part, the approximation to the maximum or minimum of the fixed point representation minimizes the decrease in accuracy. The results of this paper can be applied to the minimization of memory and hardware resource requirement in the implementation of FPGA-based BWN accelerator.

Edge-based Surface Segmentation Algorithm of 3-D Image using Curvature (곡률을 이용한 3차원 영상의 에지 기반 표면 분할 알고리즘)

  • Seol, Seong-Uk;Lee, Jae-Chul;Nam, Gi-Gon;Jeon, Gye-Rok;Ju, Jae-Heum
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.38 no.2
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    • pp.199-207
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    • 2001
  • In this paper, we suggest an edge-based surface segmentation algorithm of 3D image using curvature. For the first, in this proposed method, we approximate 3D depth data to second order curves by each scan line and decide splitting points of 3D edges by curvature of the approximated curves. And finally make a group as 3D surface with the region of input image by the 3D edges. In the conventional algorithms, there are some difficulties in detecting 3D edge with the separated processes for the jump edge and the crease edge and especially, in deciding the ambiguous discontinuity of surface directions about the crease edge. The proposed algorithm decides curvature discontinuity using curvature which is simply calculated by a geometrical approximation. Furthermore, the algorithm has a cooperated process to calculate the jump and crease edges. The results of computer simulations with several 3D images show that the proposed method yields better performance as comparing with the conventional methods.

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The Coordinate Conversion for Flight Dynamics Simulation (비행 운동 시뮬레이션을 위한 좌표계 변환)

  • Baek, Joong-Hwan;Hwang, Soo-Chan;Kim, Chil-Yong
    • Journal of Advanced Navigation Technology
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    • v.3 no.2
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    • pp.139-146
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    • 1999
  • A flight simulator is composed of engine, navigation systems and instrument modules. However, two problems exist here. First, the coordinate of each independent module is not same. To solve this problem, we design a method that mutual coordinates are capable of transformation each other. Second, the distance and bearing between two points on the earth are computed in a sphere shape using the spherical trigonometry. However, the computing time is very severe. In this paper, we project the sphere into the planar to reduce the computing time. An experimental result shows that the performance of the proposed method is excellent to both distance and bearing calculations in close region. Also, the computing time is reduced from $4.95{\times}10^{-4}$ seconds to $1.648{\times}10^{-4}$ seconds.

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An Efficient Composite Image Separation by Using Independent Component Analysis Based on Neural Networks (신경망 기반 독립성분분석을 이용한 효율적인 복합영상분리)

  • Cho, Yong-Hyun;Park, Yong-Soo
    • Journal of the Korean Institute of Intelligent Systems
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    • v.12 no.3
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    • pp.210-218
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    • 2002
  • This paper proposes an efficient separation method of the composite images by using independent component analysis(ICA) based on neural networks of the approximate learning algorithm. The Proposed learning algorithm is the fixed point(FP) algorithm based on Secant method which can be approximately computed by only the values of function for estimating the root of objective function for optimizing entropy. The secant method is an alternative of the Newton method which is essential to differentiate the function for estimating the root. It can achieve a superior property of the FP algorithm for ICA due to simplify the composite computation of differential process. The proposed algorithm has been applied to the composite signals and image generated by random mixing matrix in the 4 signal of 500-sample and the 10 images of $512{\times}512-pixel$, respectively The simulation results show that the proposed algorithm has better performance of the learning speed and the separation than those using the conventional algorithm based method. It also solved the training performances depending on initial points setting and the nonrealistic learning time for separating the large size image by using the conventional algorithm.