• 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.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2008년도 하계종합학술대회
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• pp.907-908
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• 2008

Estimation of surface roughness is an important quality measure for many applications including optics, polymers, semiconductor etc. In this paper, we propose to estimate surface roughness using image focus. We use polymers as test objects. The proposed method is an inexpensive and fast method based on Shape From Focus (SFF). We show that the results from SFF are encouraging for comparison of polymers using surface roughness.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2008년도 하계종합학술대회
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• pp.1007-1008
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• 2008

This paper introduces a new focus measure using Principal Component Analysis (PCA) for Shape from Focus (SFF). A neighborhood consisting of seven pixels is taken and the focus quality is computed over the whole sequence. The experimental results demonstrate effectiveness and robustness of the proposed method.

• 대한기계학회논문집A
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• 제28권6호
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• pp.867-875
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• 2004

In order to inspect burr geometry and hole quality in micro-drilling processes, a cost-effective method using an image processing and shape from focus (SFF) methods on the machine tool is proposed. A CCD camera with a zoom lens and a novel illumination unit is used in this paper. Since the on-machine vision unit is incorporated with the CNC function of the machine tool, direct measurement and condition monitoring of micro-drilling processes are conducted between drilling processes on the machine tool. Stainless steel and hardened tool steel are used as specimens, as well as twist drills made of carbide are used in experiments. Validity of the developed system is confirmed through experiments.

• 대한기계학회논문집A
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• 제30권6호
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• pp.713-721
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• 2006

Micro-drill wear deteriorates accuracy and productivity of the micro components. In order to improve productivity and qualify of micro components, it is required to investigate micro-drill wear exactly. In this study, a machine vision system is proposed to measure the wear of micro-drills using a precision servo stage. Calibration experiments are conducted to compensate for the machine vision system. In this paper, worn volume, area and length are defined as wear amounts. Micro-drill wear is reconstructed as the 3D topography and the quantized wear amount by using the shape from focus (SFF) method and wear parameters. Experiments have been conducted with HSS twist micro-drills and SM45C carbon steel workpieces. Validity of the proposed machine vision system is confirmed through experiments.

• 한국정보전자통신기술학회논문지
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• 제13권2호
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• pp.113-122
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• 2020

Noise affects the accuracy of three-dimensional shape recovery. Its occurrence is unpredictable and depends on several mechanical, environmental, and other factors. When two-dimensional image sequences are obtained for shape from focus (SFF), mechanical vibration occurs in the translational stage, causing an error in the three-dimensional shape recovery. To address this issue, mechanical vibration is modeled using Newton's second law and the principle of the rack and pinion gear. Then, an optimal sampling step size considering the mechanical vibration is suggested through theoretical demonstration. Experiments conducted with real objects verify the effectiveness of the proposed sampling step size. In this paper, in a realistic environment with noise, the potential of obtaining more accurate three-dimensional reconstruction results of the objects is explored by acquiring the optimal sampling step size, which improves the sampling step size relative to those reported in a previous study performed under similar conditions.

• 대한기계학회논문집A
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• 제30권5호
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• pp.496-504
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• 2006

Wear of engine valves and seat inserts is a major factor affecting engine performance. In order to improve quality and life of valve assemblies, wear mechanism and 3-D surface topography should be analyzed according to operating conditions of the engine. After developing an engine simulator that generates valve speed up to 90Hz and temperature up to $900^{\circ}C$ as well as controls test load, wear experiments have been conducted for two different engine speeds as 10Hz and 25Hz. In order to observe the wear characteristics and monitor surface conditions of the valve assemblies, a cost-effective 3-D wear analysis system based on the shape from focus(SFF) and machine vision has been fabricated in this paper. 3-D surface topography of the valve assemblies has been analyzed to understand the wear behavior according to operating conditions of the engine. Consequently, wear volume of the valve assemblies is quantized by using the developed 3-D wear analysis system.

• 방송공학회논문지
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• 제17권4호
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• pp.625-633
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• 2012

카메라로부터 획득한 여러 장의 영상에서 3차원 정보를 얻어내기 위한 Extended Depth of Focus(EDF) 알고리듬은 최근 많은 연구가 이루어지고 있다. 피사물체의 깊이정보에 따른 제한된 초점으로 인해 초점이 일부분 맞는 여러 장의 이미지를 가지고 EDF알고리듬은 각 영상들의 focus 영역에서 하나의 focused 영상과 depth영상을 취득한다. 대부분의 영상처리 알고리듬이 그렇듯, EDF 알고리듬에 사용되는 파라메타들의 초기설정에 따라 결과에 큰 영향을 준다. 본 논문에서는 EDF알고리듬을 적용하기 전 입력영상의 기반으로 pyramid, wavelet transform, complex wavelet transform을 사용하였으며 EDF알고리즘에서 사용되는 파라메타들의 설정에 따른 각 알고리즘의 성능을 분석하였다. 본 논문에서 제시한 파라메타들은 입력영상의 크기에 따른 down sampling의 단계, 영상의 기반 알고리듬의 영상 복원에 사용되는 최하위 레벨의 이미지에 대한 취득 형태, 연산에 쓰이는 window size의 크기이다. 우리는 실험을 통해 제시한 입력영상에 따라 각 파라메타들이 미치는 영향에 대해 분석하였고, 기존에 사용되었던 일반적인 파라메타 선정방식보다 최적화된 파라메타 선정방식을 통해 얻어진 결과영상이 3dB ~ 19dB정도 개선된 것을 확인하였다.