• The Journal of Korean Institute of Communications and Information Sciences
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• v.17 no.2
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• pp.187-195
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• 1992

This paper propose on the determination of threshold values for extracting shape information of the objects. First, surface curvatures such as mean curvature and gaussian curvature is calculated from given range data. And then local surface regions are classified into the one of 8 primitives by using the sign of mean curvature H and gaussian curvature K. Also from the statistical viewpoint. the range of the zero of H and K in the range is obtained through the analysis of the relation between mean curvature and gaussian curvature. Finally, the effectiveness of the proposed mithod in this paper is demonstrated by comparing with a case, where the zero threshold is arbitrarily obtained.

• Proceedings of the Korea Contents Association Conference
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• 2003.05a
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• pp.426-429
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• 2003

This paper proposes the threshold value selection for surface classification of 3-dimensional objects. Pre-existing method which uses the H-curvature and K-curvature has limitation in the practical threshold value selection. For this, this paper proposes the threshold value selection by the statistical method. Finally, the effectiveness of this paper demonstrated by experiment.

• The KIPS Transactions:PartB
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• v.11B no.3
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• pp.297-302
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• 2004

In this paper, the 3-D shape description for the objects with the cone ridge and valley surfaces, and the corresponding threshold value selection for surface classification are considered. The existing method based on the mean and Gaussian curvatures(H and K) of differential geometries cannot properly describe cone primitives, which are some of the most common objects in the real world. Also the existing method for surface classification based on the sign values of H and K has Problems in practical applications. For this, cone surface shapes are classified cone ridges and cone valleys are derived from surfaces using the fact that H values are constant case of cylinder surfaces and variable for cone surfaces, respectively. Also threshold value selection for surface classification from a statistical point of view is proposed. The effectiveness of the proposed methods are verified through experiments.

• Journal for History of Mathematics
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• v.20 no.4
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• pp.49-60
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• 2007

In this article, the concept of rigidity of smooth surfaces in the three dimensional Euclidean space which naturally arises in elementary geometry is introduced, and the natural process of the development of rigidity theory for compact surfaces and its generalizations are investigated.

• Proceedings of the Korean Institute of Communication Sciences Conference
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• 2004.07a
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• pp.219-219
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• 2004

• Journal of Ocean Engineering and Technology
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• v.20 no.4 s.71
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• pp.24-30
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• 2006

Different methods exist for the estimation of thermaldeformation of plates in the line heating process. These are based on the assumption of residual strains in the heat-affected zone, known as the method of inherent strains, or simulated relations between heating conditions and residual deformations. The purpose of this paper is to develop a simulator of thermal deformation in the line heating, using the artificial neural network. Curvature deformations for the plate-forming are investigated, which can be used as a prime deformation parameter in the process. The curvature of plates are calculated using the approximation of plate surface by NURBS. Line heating experiments for 11 specimens of different thickness and heating conditions were performed. Two neural networks predicting the maximum temperature and curvature deformations at the heating line are studied. It was concluded that the thermal deformations predicted by the neural network can be used in a line heating simulator, which is considered an attractive and practical alternative to the existing methods.

• Convergence Security Journal
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• v.8 no.4
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• pp.161-166
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• 2008

This paper proposes a new approach to align 3D data sets by using curvatures of feature surface. We use the Gaussian curvatures and the covariance matrix which imply the physical characteristics of the model to achieve registration of unaligned 3D data sets. First, the physical characteristics of local area are obtained by the Gaussian curvature. And the camera position of 3D range finder system is calculated from by using the projection matrix between 3D data set and 2D image. Then, the physical characteristics of whole area are obtained by the covariance matrix of the model. The corresponding points can be found in the overlapping region with the cross-projection method and it concentrates by removed points of self-occlusion. By the repeatedly the process discussed above, we finally find corrected points of overlapping region and get the optimized registration result.

• Korean Journal of Optics and Photonics
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• v.17 no.5
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• pp.420-429
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• 2006

In the zoom lens of digital still cameras with the variation of the image plane generated by various symmetric error factors such as curvature, thickness and refractive index error of each lens surface about the optic axis, we induce a theoretical condition to fix constantly the image plane by translating the compensator group of the zoom lens by using the Gaussian bracket. We confirm the validity of this condition by using three examples of general zoom lens types with 3, 4, and 5 groups, respectively. When these error factors are randomly changed within the range of tolerance according to the Monte Carlo method, we verify that the distributions of the degree of moving of the compensator are normal distributions at three zoom lens types. From capability analysis using these results, we theoretically propose the method estimating the standard deviation, that is, sigma-level, as a function of the maximum movement of the compensator.

• Korean Journal of Optics and Photonics
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• v.33 no.6
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• pp.275-286
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• 2022

As a first step in the optical design process, we derive a recursive numerical calculation method that can give a solution to the Gaussian equation that the paraxial rays satisfy. Given the refractive power, the angle of incidence to the first principal plane of the lens, the angle of exit to the second principal plane of the lens, and the distance between the principal planes, the radii of curvature of the front and back surfaces of a lens can be obtained by applying the recursive numerical calculation method proposed in this paper according to the thickness of the lens. If a module consists of two or more lenses, the thickness and radius of curvature of each lens can be similarly determined after selecting the distance between the principal planes of the lens under the condition of the design specification while increasing the number of lenses one by one.

• The Journal of the Acoustical Society of Korea
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• v.19 no.3
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• pp.20-25
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• 2000

This paper proposes the method of surface classification and threshold value selection for surface classification of the three-dimensional object recognition. The processings of three-dimensional image processing system consist of three steps, i.e, acquisition of range data, feature extraction and matching process. This paper proposes the method of shape feature extraction from the acquired rage data in the entire three-dimensional image processing system. In order to achieve these goals, firstly, this article proposes the surface classification method by using the distribution characteristics of sign value from range values. Also pre-existing method which uses the K-curvature and K-curvature has limitation in the practical threshold value selection. To overcome this, this article proposes the selection of threshold value for surface classification. Finally, the effectiveness of this article is demonstrated by the several experiments.