• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.9
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• pp.1782-1792
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• 1994

Ti : $LiNbO_3$ traveling-wave phase optical modulators at wavelength 1.3㎛ have been designed and fabricated, focusing on the optical waveguide and asymmetric coplanar electrode structure. To improve the phase-mismatch of traveling-wave ACPS electrode, the characteristic impedance, effective microwave index, and electrode loss have been presented as a function of geometric parameters including electrode and buffer layer thickness. Low-loss channel optical waveguides on $LiNbO_3$ were fabricated by the Ti diffusion method with $O_2$ water-vapor environment. $2.5{\mu}m$ thick electrode was successfully fabricated by double-spin image reversal process. Modulation bandwidth was limited by a resonance at 2.9 GHz and modulation bandwidth up to 2.5GHz was approxirnately measured.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1617-1620
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• 1997

This paper describes the camera caliberation based-neural network with a camera modeling that accounts for major sources of camera distortion, namely, radial, decentering, and thin prism distortion. Radial distoriton causes an inward or outward displacement of a given image point from its ideal location. Actual optical systems are subject to various degrees of decentering, that is the optical centers of lens elements are not strictly collinear. Thin prism distortion arises from imperfection in lens design and manufacturing as well as camera assembly. It is our purpose to develop the vision system for the pattern recognition and the automatic test of parts and to apply the line of manufacturing. The performance of proposed camera aclibration is illustrated by simulation and experiment.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2002.04a
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• pp.179-183
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• 2002

This paper presents a new approach to the calibration of a SCARA robot orientation with a camera modeling that accounts for major sources of camera distortion, namely, radial, decentering, and thin prism distortion. radial distortion causes an inward or outward displacement of a given Image point from its ideal location. Actual optical systems are subject to various degrees of decentering, that is, the optical centers of lens elements are not strictly collinear. Thin prism distortion arises from imperfection in lens design and manufacturing as well as camera assembly It is our purpose to develop the vision system for the pattern recognition and the automatic test of parts and to apply the line of manufacturing.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1997.10a
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• pp.225-229
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• 1997

This paper describes the camera calibration based-neural network with a camera modeling that accounts for major sources of camera distortion, namely, radial, decentering, and thin prism distortion. Radial distortion causes and inward or outward displacement of a given image point from its ideal location. Actual optical systems are subject to various degrees of decentering, that is, the optical centers of lens elements are not strictly collinear. Thin prism distortion arises from imperfection in lens design and manufacturing as well as camera assembly. It is our purpose to develop the vision system for the pattern recognition and the automatic test of parts and to apply the line of manufacturing. The performance of proposed camera calibration is illustrated by simulation and experiment.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1997.10a
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• pp.65-69
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• 1997

This paper presents a new approach to the calibration of a SCARA robot orientation with a camera modeling that accounts for major sources of camera distortion, namely, radial, decentering, and thin prism distortion. Radial distortion causes an inward or outward displacement of a given image point from its ideal location. Actual optical systems are subject to various degrees of decentering, that is, the optical centers of lens elements are not strictly collinear. Thin prism distortion arises from imperfection in lens design and manufacturing as well as camera assembly. It is our purpose to develop the vision system for the pattern recognition and the automatic test of parts and to apply the line of manufacturing.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2001.10a
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• pp.117-121
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• 2001

This paper presents a new approach to the calibration of a SCARA robot orientation with a camera modeling that accounts for major sources of camera distortion, namely, radial, decentering, and thin prism distortion. Radial distortion causes an inward or outward displacement of a given image point from its ideal location. Actual optical systems are subject to various degrees of decentering, that is, the optical centers of lens elements are not strictly collinear. Thin prism distortion arises from imperfection in lens design and manufacturing as well as camera assembly. It is our purpose to develop the vision system for the pattern recognition and the automatic test of parts and to apply the line of manufacturing.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.806-809
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• 2003

In this paper, extracting design information from arbitrary aspherical lens shape in reverse engineering is introduced. Deformation terms and sphere data equation with various variables compose asphere equation. Aspherical lens shape is expressed with complicated polynomial expression that includes deformation terms and sphere data. Deformation term and vertex curvature have direct influence on a geometric shape and an optical characteristics of aspherical lens. Hence, extracting these information mean that design information could be derived and analyzed from shape data of arbitrary aspherical lens. Furthermore, sharing designer's experience and knowledge for aspherical lens design could be expected.

• International Journal of Precision Engineering and Manufacturing
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• v.8 no.2
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• pp.20-25
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• 2007

This paper describes a second-generation dual sine-grid surface encoder for 2-D position measurements. The surface encoder consisted of a 2-D grid with a 2-D sinusoidal pattern on its surface, and a 2-D angle sensor that detected the 2-D profile of the surface grid The 2-D angle sensor design of previously developed first-generation surface encoders was based on geometric optics. To improve the resolution of the surface encoder, we fabricated a 2-D sine-grid with a pitch of $10{\mu}m$. We also established a new optical model for the second-generation surface encoder that utilizes diffraction and interference to generate its measured values. The 2-D sine-grid was fabricated on a workpiece by an ultra precision lathe with the assistance of a fast tool servo. We then performed a UV-casting process to imprint the sine-grid on a transparent plastic film and constructed an experimental setup to realize the second-generation surface encoder. We conducted tests that demonstrated the feasibility of the proposed surface encoder model.

• International Journal of Precision Engineering and Manufacturing
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• v.3 no.3
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• pp.37-43
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• 2002

Electronic speckle contouring(ESC) based on electronic speckle pattern interferometry is the optical method for measuring object shape by using fringe-projection techniques. This method has the advantages of being non-contact, non-destructive and a whole-field measurement of the surface under investigation. Fringes in ESC represent the difference in depth along the view direction between the master wavefront and the test component. The contour maps of three-dimensional diffuse objects can be obtained by small shifts of optical fiber carrying the dual-object-beams and 4-frame phase shifting. In this study we proposed the contouring method by shifting the collimated illumination beams through optical fiber in order to obtain the contour fringe patterns. And also, we performed the addition of incremental images through the geometrical analysis to obtain the contour fringe interval when we performed the incremental addition of images and experiments based on this method. We obtained both quantitative increment without decorrelation effect and qualitative improvement by reducing the noise of contour fringes.

• Current Optics and Photonics
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• v.7 no.3
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• pp.237-247
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• 2023

In middle- and long-distance imaging systems, due to the atmospheric turbulence caused by temperature, wind speed, humidity, and so on, light waves propagating in the air are distorted, resulting in image-quality degradation such as geometric deformation and fuzziness. In remote sensing, astronomical observation, and traffic monitoring, image information loss due to degradation causes huge losses, so effective restoration of degraded images is very important. To restore images degraded by atmospheric turbulence, an image-restoration method based on improved compound multibranch feature fusion (CMFNetPro) was proposed. Based on the CMFNet network, an efficient channel-attention mechanism was used to replace the channel-attention mechanism to improve image quality and network efficiency. In the experiment, two-dimensional random distortion vector fields were used to construct two turbulent datasets with different degrees of distortion, based on the Google Landmarks Dataset v2 dataset. The experimental results showed that compared to the CMFNet, DeblurGAN-v2, and MIMO-UNet models, the proposed CMFNetPro network achieves better performance in both quality and training cost of turbulent-image restoration. In the mixed training, CMFNetPro was 1.2391 dB (weak turbulence), 0.8602 dB (strong turbulence) respectively higher in terms of peak signal-to-noise ratio and 0.0015 (weak turbulence), 0.0136 (strong turbulence) respectively higher in terms of structure similarity compared to CMFNet. CMFNetPro was 14.4 hours faster compared to the CMFNet. This provides a feasible scheme for turbulent-image restoration based on deep learning.