• Journal of the Korea Computer Graphics Society
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• v.18 no.4
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• pp.1-8
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• 2012

We present improved deformation energy to enhance the visual quality of a shape deformation technique, where we preserve the local structure of an input planar shape. The deformation energy, in general, consists of several constraints such as Laplacian coordinate constraint to preserve the quality of deformed silhouette edges, mean value coordinates and edge length constraints to preserve the quality of deformed internal shape, and user-specified position constraints to control the shape deformation. When the positions of user-specified vertices change, shape deformation techniques compute the positions of the other vertices by means of nonlinear least squares optimization to minimize the deformation energy. When a user-specified vertex changes its position rapidly, it is frequently observed that the visual quality of the deformed shape decrease rapidly, which is mainly caused by unnecessary enlargement of the Laplacian vectors and unnecessary change of the edge directions along the boundary of the shape. In this paper, we propose improved deformation energy by prohibiting the Laplacian and edge length constraints from changing unnecessarily. The proposed deformation energy incorporated with well-known optimization technique can enhance the visual quality of shape deformation along the silhouette and within the interior of the planar shape while sacrificing only a little execution time.

• Journal of the Korea Computer Graphics Society
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• v.12 no.2
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• pp.35-38
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• 2006

우리는 3차원 개체로 표현된 옷의 주름을 라플라시안 맵과 옷 주름 맵을 사용하여 실시간에 비사실적으로 표현하는 방법을 제안한다. 옷의 주름을 표현하기 위해, 옷의 주름을 디자이너가 직접 그린 옷 주름 맵과 옷이 변형된 상태에 대한 정보가 계산된 라플라시안 맵을 사용하여, 단순한 GPU연산을 통해 최종적으로 옷의 주름을 표현한다. 실험 결과 우리가 제안한 방법은 옷의 주름을 실시간에 비사실적으로 표현할 수 있으며, 디자이너의 의도한 바대로 주름을 그릴 수 있다는 장점이 있음을 알 수 있었다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.5
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• pp.611-617
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• 2018

The application of health monitoring, including a fault detection technique, is needed to secure the structural safety of large structures. A 2-step crack identification method for detecting the crack location and size of the beam structure is presented. First, a crack occurrence region was estimated using the modified Laplacian operator for the strain mode shape obtained from the distributed local strain data. The crack location and size were then identified based on the natural frequencies obtained from the acceleration data and the neural network technique for the pre-estimated crack occurrence region. The natural frequencies of a cracked beam were calculated based on an equivalent bending stiffness induced by the energy method, and used to generate the training patterns of the neural network. An experimental study was carried out on an aluminum cantilever beam to verify the present method for crack identification. Cracks were produced on the beam, and free vibration tests were performed. A crack occurrence region was estimated using the modified Laplacian operator for the strain mode shape, and the crack location and size were assessed using the natural frequencies and neural network technique. The identified crack occurrence region agrees well with the exact one, and the accuracy of the estimation results for the crack location and size could be enhanced considerably for 3 damage cases. The presented method could be applied effectively to the structural health monitoring of large structures.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2014.11a
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• pp.88-89
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• 2014

본 논문에서는 미리 모델링된 실객체에 대한 3차원 모델을 변형하면서 애니메이션을 정의하고, 실사 객체를 추적하면서 카메라 뷰 상의 실사 객체에 애니메이션을 적용하는 방법을 제안한다. 애니메이션 정의는 라플라시안 기반 메쉬 변형 방법으로 3차원 모델을 변형시키며 키프레임을 지정함으로써 이루어진다. 정의된 애니메이션은 실제 환경에서 추적된 실사 객체의 영상으로부터 모델에 텍스처를 입힌 뒤, 카메라 포즈를 이용하여 객체 위치에 객체 모델을 렌더링할 때 적용된다. 제안된 방법을 통해 사용자가 원하는 대로 실제 환경에 대한 카메라 뷰 상에서 실사 객체가 변형되는 모습을 용이하게 보여줄 수 있다.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2000.04a
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• pp.127-132
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• 2000

Though the increment of using computer vision system, there are lots of difficulties to measure precisely because of measurement error or distortion phenomenon. Among these reasons, the distortion of edge is dominant reason which is occurred by the blurred image. So, the problem of clear judgment about image focal point is very important. We must fix the discrimination criteria which is collected by image recognition of precise focus. To solve these problems, we compare with make processing methods using image intensity gradient, laplacian, and sum -modified laplacian operator. These experimental results showed modified mask processing method is effective.

• Journal of the Korean Society for Precision Engineering
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• v.24 no.11
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• pp.134-143
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• 2007

A new approach based on mean value coordinate combined with Laplacian coordinate is proposed for shape deformation of a large polygon model composed of triangular net. In the method, the spherical mean value coordinates for closed control meshes is introduced to describe a vertex in the triangle meshes to be deformed. Furthermore, the well known quardratic least square method for the Laplacian coordinates is employed in order to deform the control meshes. Because the mean value coordinates are continuous and smooth on the interior of control meshes, deforming operation of control meshes change the shape of polygon model while preserving the intrinsic surface detail. The effectiveness and validity of this novel approach was demonstrated by using it to deform large and complex polygon models with arbitrary topologies.

• Journal of KIISE:Software and Applications
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• v.32 no.9
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• pp.878-887
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• 2005

The passive focusing method finds the in-focus position by analyzing images captured by a camera. In this paper, we propose an efficient passive auto-focusing algorithm for video measuring systems. The sum of modified Laplacian of Gaussian is used to calculate focus values from images and Gaussian curve fitting is applied to estimate the optimal in-focus position. The Proposed method is tested for various objects and illuminations. The test result is compared with other methods to verify accuracy and efficiency of the proposed algorithm.

• Journal of the Korea Computer Graphics Society
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• v.27 no.1
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• pp.1-8
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• 2021

This paper proposes a simple deformation method for editing the trajectory of a walking motion with preserving its style. To this end, our method analyzes the trajectory of the root joint into the graph and deforms it by applying the graph Laplace operator. The trajectory of the root joint is presented as a graph with a vertex defined the position and direction at each time frame on the motion dataThe graph transforms the trajectory into the differential coordinate, and if the constraints are set on the trajectory vertex, the solver iterative approaches to the solution. By modifying the root trajectory, we can continuously vary the walking motion, which reduces the cost of capturing a whole motion that is required. After computes the root trajectory, other joints are copied on the root and post-processed as a final motion. At the end of our paper, we show the application that the character continuously walks in a complex environment while satisfying user constraints.

• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.9
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• pp.901-908
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• 2016

Edge is the basic characteristic of image, edge detection is very important in image processing applications and computer vision area. Many studies are being performed to detect these edges by domestic and foreign researchers. The conventional edge detection methods such as Roberts, Sobel, Prewitt, and Laplacian etc, which are using a fixed value of mask are widely used and morphological gradient which uses dilation and erosion among morphology process techniques is also widely used. But these methods does not detect edges well in the diagonal direction or gradually changing image parts. Accordingly, in this paper, the modified top-hat and bottom-hat transform algorithms which are detecting edges well in the parts of diagonal direction or gradually changing image are proposed. The proposed algorithms present the detected edge images compared with the conventional methods and are evaluated performance by using cosine similarity.

• Journal of Korea Multimedia Society
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• v.12 no.7
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• pp.929-940
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• 2009

This paper presents multipurpose watermarking scheme in coutourlet transform domain for copyright protection, authentication and transform detection. Since contourlet transform can detect more multi direction edge and smooth contour than wavelet transform, the proposed scheme embeds multi watermarks in contourlet domain based on 4-level Laplacian pyramid and 2-level directional filter bank. In the first stage of the robust watermarking scheme for copyright protection, we generates the sequence of circle patterns according to watermark bits and projects these patterns into the average of magnitude coefficients of high frequency directional subbands. Then the watermark bit is embedded into variance distribution of the projected magnitude coefficients. In the second stage that is the semi-fragile watermarking scheme for authentication and transform detection, we embed the binary watermark image in the low frequency subband of higher level by using adaptive quantization modulation scheme. From the evaluation experiment using Checkmark 2.1, we verified that the proposed scheme is superior to the conventional scheme in a view of the robustness and the invisibility.