• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2006년도 춘계학술대회 논문집
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• pp.439-440
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• 2006

This research proposes a novel method of shape display to present 3-dimensional objects. Shape displays allow us to feel the actual volume of the object, unlike conventional 2D visual displays of 3D objects. The proposed method employs a wire frame structure to present 3D objects. The wire frame is composed of small units driven by shape memory alloy(SMA) actuators. The drive unit is analogous to the agonist-antagonist system of animal musculoskeletal systems, where the SMA actuators serve as agonist and antagonist muscles. The force in the SMA actuator is controlled by electrical current. The drive unit is equipped with the locking mechanism so that it can sustain the external force exerted by the user as well as the own weight of the wire frame structure. By controlling the current into the SMA actuator and locking mechanism, we call control the angle of the drive unit. A chain of drive units enables presentation of 2 dimensional objects. 3 dimensional presentations are possible by collecting the chains of drive units.

• 한국정밀공학회지
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• 제25권5호
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• pp.82-88
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• 2008

This paper proposes a novel method of 2 dimensional shape display. Shape displays allow us to feel tile actual volume of the object, unlike conventional 2D visual displays of 3D objects. The proposed method employs a wireframe structure to present 2D or 3D objects. The wireframe is composed of small units driven by shape memory alloy (SMA) actuators. The drive unit is analogous to the agonist-antagonist system of animal musculoskeletal systems, where the SMA actuators serve as agonist and antagonist muscles. The force in the SMA actuator is controlled by electrical current. The drive unit is equipped with the locking mechanism so that it can sustain the external force exerted by the user as well as the own weight of the wireframe structure. By controlling the current into the SMA actuator and locking mechanism, we can control the angle of the drive unit. A chain of drive units enables presentation of 2 dimensional objects. 3 dimensional presentations are possible by collecting the chains of drive units.

• 반도체디스플레이기술학회지
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• 제12권2호
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• pp.27-32
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• 2013

Shape From Focus (SFF) is a passive optical technique to recover 3D structure of an object that utilizes focus information from 2D images of the object taken at different focus levels. Mostly, SFF methods use a single focus measure to compute image focus quality of each pixel in the image sequence. However, it is difficult to recover accurate 3D shape using a single focus measure, as different focus measures perform differently in diverse conditions. In this paper, a nonlinear Total Variation (TV) based approach is proposed for 3D shape recovery. To improve the result of surface reconstruction, several initial depth maps are obtained using different focus measures and the resultant 3D shape is obtained by diffusing them through TV. The proposed method is tested and evaluated by using image sequences of synthetic and real objects. The results and comparative analysis demonstrate the effectiveness of our method.

• 반도체디스플레이기술학회지
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• 제18권3호
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• pp.66-71
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• 2019

In shape from focus (SFF) methods, the quality of image focus volume plays a vital role in the quality of 3D shape reconstruction. Traditionally, a linear 2D filter is applied to each slice of the image focus volume to rectify the noisy focus measurements. However, this approach is problematic because it also modifies the accurate focus measurements that should ideally remain intact. Therefore, in this paper, we propose to enhance the focus volume adaptively by applying 3-dimensional weighted least squares (3D-WLS) based regularization. We estimate regularization weights from the guidance volume extracted from the image sequences. To solve 3D-WLS optimization problem efficiently, we apply a technique to solve a series of 1D linear sub-problems. Experiments conducted on synthetic and real image sequences demonstrate that the proposed method effectively enhances the image focus volume, ultimately improving the quality of reconstructed shape.

• 반도체디스플레이기술학회지
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• 제19권4호
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• pp.59-64
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• 2020

In this paper, we found the solution using data based machine learning regression method to check the pore shape, to solve the problem of the experiment quantity occurring when producing scaffold with the 3d printer. Through experiments, we learned secured each print condition and pore shape. We have produced the scaffold from scaffold pore shape defect prediction model using multiple linear regression method. We predicted scaffold pore shapes of unsecured print condition using the manufactured scaffold pore shape defect prediction model. We randomly selected 20 print conditions from various predicted print conditions. We print scaffold five times under same print condition. We measured the pore shape of scaffold. We compared printed average pore shape with predicted pore shape. We have confirmed the prediction model precision is 99 %.

• 반도체디스플레이기술학회지
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• 제11권3호
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• pp.19-25
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• 2012

The accuracy of Shape From Focus (SFF) technique depends on the quality of the focus measurements which are computed through a focus measure operator. In this paper, we introduce a new approach to estimate 3D shape of an object based on Gaussian process regression. First, initial depth is estimated by applying a conventional focus measure on image sequence and maximizing it in the optical direction. In second step, input feature vectors consisting of eginvalues are computed from 3D neighborhood around the initial depth. Finally, by utilizing these features, a latent function is developed through Gaussian process regression to estimate accurate depth. The proposed approach takes advantages of the multivariate statistical features and covariance function. The proposed method is tested by using image sequences of various objects. Experimental results demonstrate the efficacy of the proposed scheme.

• 방송공학회논문지
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• 제14권2호
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• pp.210-218
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• 2009

자연 3D 환경에서와 달리 3D 디스플레이를 통해 제시되는 대상의 깊이와 모양은 관찰거리에 따라서 체계적으로 왜곡되어 지각된다. 동일한 3D 디스플레이를 시청하는 다수의 시청자가 상이한 3D 깊이감과 모양감을 지각하는 것은 바람직하지 않은데, 이와 같은 3D 깊이감/모양감 왜곡 문제를 해결하기 위해서는 3D 깊이감과 모양감의 왜곡정도를 측정하는 정교한 도구가 필요하다. 본 연구는 3D 깊이감과 모양감 왜곡의 문제를 해결하기 위한 기반연구로서 3D 깊이감과 모양감 왜곡정도를 측정할 수 있는 깊이감/모양감 왜곡 측정도구를 제안한다.

• 제어로봇시스템학회논문지
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• 제19권2호
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• pp.171-176
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• 2013

X-ray cross-sectional image-based inspection technique is one of the most useful methods to inspect the brazing joints of heat exchanger. Through X-ray cross-sectional image acquisition, image processing, and defect inspection, the defects of brazing joints can be detected. This paper presents a method to judge the type of detected defects automatically, and to display them three-dimensionally. The defect type is classified as unconnected defect, void, and so on, based on location, size, and shape information of defect. Three-dimensional display which is realized using OpenGL (Open Graphics Library) will be helpful to understand the overall situation including location, size, shape of the defects in a test object.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2006년도 춘계학술대회 논문집
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• pp.295-296
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• 2006

We developed wire frame drive unit based on SMA for the 3D Shape display. Our basic concept is wire frame combination connected with a chain form which can create various shapes and it compared with pin array mechanism which is not able to display mushroom shape. It imitates antagonist mechanism of human musculoskeletal system. we create similar motion using repair-relaxation mechanism and locking mechanism by SMA. Therefore, in this paper, we propose SMA control solution for actuating repair-relaxation mechanism and locking mechanism. In our control system. we use optical sensor and quantitative angle between wire frames for closed loop control. And we supply amplified current for SMA by circuit composed of transistor and apply PWM signal to circuit for efficient control. So, wire frame drive unit enable diversity angle control based on sensor data. And then combination of wire frame drive units will create various objects.

• 반도체디스플레이기술학회지
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• 제13권2호
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• pp.23-28
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• 2014

For the reconstruction of three-dimensional (3D) shape of microscopic objects through shape from focus (SFF) methods, usually a single focus measure operator is employed. However, it is difficult to compute accurate depth map using a single focus measure due to different textures, light conditions and arbitrary object surfaces. Moreover, real images with diverse types of illuminations and contrasts lead to the erroneous depth map estimation through a single focus measure. In order to get better focus measurements and depth map, we have combined focus measure operators by using genetic algorithm. The resultant focus measure is obtained by weighted sum of the output of various focus measure operators. Optimal weights are obtained using genetic algorithm. Finally, depth map is obtained from the refined focus volume. The performance of the developed method is then evaluated by using both the synthetic and real world image sequences. The experimental results show that the proposed method is more effective in computing accurate depth maps as compared to the existing SFF methods.