• Proceedings of the KIEE Conference
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• 1990.11a
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• pp.460-464
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• 1990

Texture provides an important source of information about the local orientation of visible surfaces. An important task that arises in many computer vision systems is the reconstruction of three-dimensional depth information from two-dimensional images. The surface orientation of texel is classified by the Artificial Neural Network. The classification method to recognize the shape of 3D object with artificial neural network requires less developing time comparing to conventional method. The segmentation problem is assumed to be solved. The surface in view is smooth and is covered with repeated texture elements. In this study, 3D shape reconstruct using interpolation method.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.330-330
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• 2002

The combination of Multi-Beam Echo Sounder swath bathymetry and high-resolution towed Sidescan sonar provides a powerful method of examination about hydrographic survey results. In this paper, we investigate the fast method of 3D bathymetric reconstruction with the Digital Sidescan sonar(Benthos SIS 1500) and Shallow Multi-Beam Echo Sounder(Reson Seabat 8125). The Seabat 8125 is a 455KHz high resolution focused Multibeam echo sounder(MBES) system which measures the relative water depth across a wide swath perpendicular to a vessel's track. The Benthos SIS1500 is a chirp(nominal fq. 200KHz) sonar which map the topographical features & sediment texture of ocean bottom using backscattered amplitude. We generates the very large 3D bathymetric texture mapping model with the Helical System's HHViewer and describes additional benefits of combining MBES and Sidescan Sonar imagery, the removal of geometric distortions in the model and a deterministic sounding noise.

• Proceedings of the KIEE Conference
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• 2007.10c
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• pp.207-208
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• 2007

높은 효율의 태양전지의 개발은 태양전지 상용화에 꼭 필요한 일이다. 고효율 태양전지 개발을 위해 태양전시 시뮬레이션 프로그램인 PC1D를 이용하여 현재 많이 사용되고 있는 p-n 접합형 실리콘 태양전지의 변환효율에 영향을 주는 요소들, 특히 웨이퍼 표면의 texturing과 doping 농도를 변화시켜 최적의 요건을 찾고자하였다. texture depth = 3um, texture angle=$80^{\circ}$, base의 비저항=$0.1{\ell}{\cdot}cm$, emitter doping 농도=$5e+18cm^{-3}$에서 20.37%의 고효율을 얻을 수 있다.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2006.05a
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• pp.565-566
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• 2006

High speed machining experiment on the inclined surfaces of hardened mold steel(STAVAX at hardness HRC 53) is carried out using the long-neck type ball endmill. Surface texture and roughness are compared fur various cutting conditions. Tool overhang length greatly affects the roughness of machined surface. It is found that, fur this type of long-neck endmill, the chip load should be carefully selected by reducing either the axial depth of cut or feedrate to avoid tool vibration. Feedrate adjustment is more appropriate method in terms of tool wear.

• Journal of Broadcast Engineering
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• v.21 no.6
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• pp.878-888
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• 2016

This paper proposes an efficient method to remove the boundary artifacts of rendered views caused by damaged depth maps in the 3D video system. First, characteristics of boundary artifacts with the compression noise in depth maps are carefully studied. Then, the artifacts suppression method is proposed by the iterative projection onto convex sets (POCS) algorithm with setting the convex set in pixel and frequency domain. The proposed method is applied to both texture and depth maps separately during view rendering. The simulation results show the boundary artifacts are greatly reduced with improving the quality of synthesized views.

• Journal of Broadcast Engineering
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• v.19 no.2
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• pp.140-147
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• 2014

In this paper, we propose a method for real-time depth image refinement. In order to improve the quality of the depth map acquired from Kinect camera, we employ constant memory and texture memory which are suitable for a 2D image processing in the graphics processing unit (GPU). In addition, we applied the joint bilateral filter (JBF) in parallel to accelerate the overall execution. To enhance the quality of the depth image, we applied the JBF hierarchically using the compute unified device architecture (CUDA). Finally, we obtain the refined depth image. Experimental results showed that the proposed real-time depth image refinement algorithm improved the subjective quality of the depth image and the computational time was 260 frames per second.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.2
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• pp.139-146
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• 2016

Recently, popularity of 3D technology has been growing significantly and it has many application parts in the various fields of industry. In order to overcome the limitations of 2D machine vision technologies based on 2D image, we need the 3D measurement technologies. There are many 3D measurement methods as such scanning probe microscope, phase shifting interferometry, confocal scanning microscope, white-light scanning interferometry, and so on. In this paper, we have used the extended depth of focus (EDF) algorithm among 3D measurement methods. The EDF algorithm is the method which extracts the 3D information from 2D images acquired by short range depth camera. In this paper, we propose the EDF algorithm using the edge informations of images and the average values of all pixel on z-axis to improve the performance of conventional method. To verify the performance of the proposed method, we use the various synthetic images made by point spread function(PSF) algorithm. We can correctly make a comparison between the performance of proposed method and conventional one because the depth information of these synthetic images was known. Through the experimental results, the PSNR of the proposed algorithm was improved about 1 ~ 30 dB than conventional method.

• Journal of Internet Computing and Services
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• v.21 no.3
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• pp.113-121
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• 2020

Human Pose Estimation (HPE) which localizes the human body joints becomes a high potential for high-level applications in the field of computer vision. The main challenges of HPE in real-time are occlusion, illumination change and diversity of pose appearance. The single RGB image is fed into HPE framework in order to reduce the computation cost by using depth-independent device such as a common camera, webcam, or phone cam. However, HPE based on the single RGB is not able to solve the above challenges due to inherent characteristics of color or texture. On the other hand, depth information which is fed into HPE framework and detects the human body parts in 3D coordinates can be usefully used to solve the above challenges. However, the depth information-based HPE requires the depth-dependent device which has space constraint and is cost consuming. Especially, the result of depth information-based HPE is less reliable due to the requirement of pose initialization and less stabilization of frame tracking. Therefore, this paper proposes a new method of HPE which is robust in estimating self-occlusion. There are many human parts which can be occluded by other body parts. However, this paper focuses only on head self-occlusion. The new method is a combination of the RGB image-based HPE framework and the depth information-based HPE framework. We evaluated the performance of the proposed method by COCO Object Keypoint Similarity library. By taking an advantage of RGB image-based HPE method and depth information-based HPE method, our HPE method based on RGB-D achieved the mAP of 0.903 and mAR of 0.938. It proved that our method outperforms the RGB-based HPE and the depth-based HPE.

• Smart Media Journal
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• v.3 no.4
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• pp.28-34
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• 2014

Recently the depth-image-based rendering (DIBR) method is usually used in 3D image application filed. Virtual view image is created by using a known view with associated depth map to make a virtual view point which did not taken by the camera. But, disocclusion area occur because the virtual view point is created using a depth image based image 3D warping. To remove those kind of disocclusion region, many hole filling methods are proposed until now. Constant color region searching, horizontal interpolation, horizontal extrapolation, and variational inpainting techniques are proposed as a hole filling methods. But when using those hole filling method some problem occurred. The different types of annoying artifacts are appear in texture region hole filling procedure. In this paper to solve those problem, the multi-directional extrapolation method is newly proposed for efficiency of expanded hole filling performance. The proposed method is efficient when performing hole filling which complex texture background region. Consideration of directionality for hole filling method use the hole neighbor texture pixel value when estimate the hole pixel value. We can check the proposed hole filling method can more efficiently fill the hole region which generated by virtual view synthesis result.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.42 no.5 s.305
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• pp.19-26
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• 2005

In this paper, a new method for obtaining three-dimensional shape of an object by measuring relative blur between images using wavelet analysis has been described. Most of the previous methods use inverse filtering to determine the measure of defocus. These methods suffer from some fundamental problems like inaccuracies in finding the frequency domain representation, windowing effects, and border effects. Besides these deficiencies, a filter, such as Laplacian of Gaussian, that produces an aggregate estimate of defocus for an unknown texture, can not lead to accurate depth estimates because of the non-stationary nature of images. We propose a new depth from defocus (DFD) method using wavelet analysis that is capable of performing both the local analysis and the windowing technique with variable-sized regions for non-stationary images with complex textural properties. We show that normalized image ratio of wavelet power by Parseval's theorem is closely related to blur parameter and depth. Experimental results have been presented demonstrating that our DFD method is faster in speed and gives more precise shape estimates than previous DFD techniques for both synthetic and real scenes.