• ETRI Journal
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• v.23 no.4
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• pp.190-198
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• 2001

The performance of Motion Compensated Discrete Cosine Transform (MC-DCT) video coding is improved by using the region adaptive subband image coding [18]. On the assumption that the video is acquired from the camera on a moving platform and the distance between the camera and the scene is large enough, both the motion of camera and the motion of moving objects in a frame are compensated. For the compensation of camera motion, a feature matching algorithm is employed. Several feature points extracted using a Sobel operator are used to compensate the camera motion of translation, rotation, and zoom. The illumination change between frames is also compensated. Motion compensated frame differences are divided into three regions called stationary background, moving objects, and newly emerging areas each of which is arbitrarily shaped. Different quantizers are used for different regions. Compared to the conventional MC-DCT video coding using block matching algorithm, our video coding scheme shows about 1.0-dB improvements on average for the experimental video samples.

• Electronics and Telecommunications Trends
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• v.33 no.4
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• pp.1-13
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• 2018

Deep learning (DL) models have been widely applied to AI applications such image recognition and language translation with big data. Recently, DL models have becomes larger and more complicated, and have merged together. For the accelerated training of a large-scale deep learning model, model parallelism that partitions the model parameters for non-shared parallel access and updates across multiple machines was provided by a few distributed deep learning frameworks. Model parallelism as a training acceleration method, however, is not as commonly used as data parallelism owing to the difficulty of efficient model parallelism. This paper provides a comprehensive survey of the state of the art in model parallelism by comparing the implementation technologies in several deep learning frameworks that support model parallelism, and suggests a future research directions for improving model parallelism technology.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.6
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• pp.2115-2127
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• 2021

Although significant progress has been made in synthesizing visually realistic face images by Generative Adversarial Networks (GANs), there still lacks effective approaches to provide fine-grained control over the generation process for semantic facial attribute editing. In this work, we propose a novel cross channel self-attention based generative adversarial network (CCA-GAN), which weights the importance of multiple channels of features and archives pixel-level feature alignment and conversion, to reduce the impact on irrelevant attributes while editing the target attributes. Evaluation results show that CCA-GAN outperforms state-of-the-art models on the CelebA dataset, reducing Fréchet Inception Distance (FID) and Kernel Inception Distance (KID) by 15~28% and 25~100%, respectively. Furthermore, visualization of generated samples confirms the effect of disentanglement of the proposed model.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2023.05a
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• pp.285-286
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• 2023

The visualization of information serves as a valuable tool for facilitating communication and exchange of opinions among stakeholders by conveying information in an intuitive and clear manner. As a preliminary study of visualization for construction field, this study proposed a model for generating three-dimensional floor layout using 360-degree panoramic cameras. The model integrates the layouts by calculating normal vectors of the plane which has openings, and applying translation and rotation matrices between the normal vectors. The results of this study can contribute to improving communication in construction sites by incorporating visualization, and further to the digital transformation of the construction industry.

• Progress in Medical Physics
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• v.9 no.1
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• pp.47-53
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• 1998

Nuclear Medicine Images have comparatively poor spatial resolution, making it difficult to relate the functional information which they contain to precise anatomical structures. Anatomical structures useful in the interpretation of SPECT /PET Images were radiolabelled. PET/SPECT Images Provide functional information, whereas MRI mainly demonstrate morphology and anatomical. Fusion or Image Registration improves the information obtained by correlating images from various modalities. Brain Scan were studied on one or more occations using MRI and SPECT. The data were aligned using a point pair methods and surface matching. SPECT and MR Images was tested using a three dimensional water fillable Hoffman Brain Phantom with small marker and PET and MR Image was tested using a patient data. Registration of SPECT and MR Images is feasible and allows more accurate anatomic assessment of sites of abnormal uptake in radiolabeled studies. Point based registration was accurate and easily implemented three dimensional registration of multimodality data set for fusion of clinical anatomic and functional imaging modalities. Accuracy of a surface matching algorithm and homologous feature pair matching for three dimensional image registration of Single Photon Emission Computed Tomography Emission Computed Tomography (SPECT), Positron Emission Tomography (PET) and Magnetic Resonance Images(MRD was tested using a three dimensional water fill able brain phantom and Patients data. Transformation parameter for translation and scaling were determined by homologous feature point pair to match each SPECT and PET scan with MR images.

• Proceedings of the IEEK Conference
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• 2001.09a
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• pp.209-212
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• 2001

오늘날, 디지털 워터마크에 대하여 기하학적 변환에 대한 강인성이 요구되고 있다. 본 논문에서는 회전, 이동 및 크기변화에 강인한 워터마킹 방법을 제안한다. 영상의 푸리에 변환 계수를 이용하여 이동에 대한 강인한 속성을 가지도록 하며, 입력 마스크의 상호 관계가 회전, 크기 변화에 강인하도록 워터마크 마스크를 생성한 후 영상에 삽입한다. 삽입된 워터마크의 검출은 영상의 주파수 영역의 radial projection 에 대한 워터마크 신호의 상관도를 이용하여 검출한다. 실험을 통하여 제안된 방법이 여러 가지 기하학적 변환에 강인함을 보여준다.

• 한국전산유체공학회:학술대회논문집
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• 2007.10a
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• pp.67-72
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• 2007

A post-processing program based on the OOP(Object-Oriented Programming) concept has been developed for visualization of MRI. User-friendly GUl(Graphic User Interface) has been built on the base of MFC(Microsoft Foundation Class). The program is organized as modules by classes based on VTK-library, and these classes are made to function through inheritance and cooperation which are an important and valuable concept of object-oriented programming. The major functions of this post-processor program are introduced and demonstrated, which include contour plot, surface plots, cut plot and clip plot as well as view manipulation (translation, rotation, scaling etc).

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.13 no.2
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• pp.28-34
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• 2014

A non-contact type measurement system is specially devised to measure the width of a piston ring groove in the grinding process. This system comprises a line camera with an imaging lens, collimated white light source, and a one axis translation stage. When the measurement system movesalong the diagonal direction of the cylinder, the line camera captures an image. By analyzing such images, the width of the piston ring groove can be determined. The experimental results prove that the proposed system is useful, especially as a monitoring system in grinding piston ring grooves on cylinders with accuracy of several micrometers in an area of dozens of millimeters.

• Journal of computational fluids engineering
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• v.19 no.2
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• pp.30-39
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• 2014

We report in this paper the analysis of the motion of a needle and a spring in a viscous fluid under the influence of gravitational force. Lateral shift as well as vertical motion of a needle falling in a viscous fluid has been observed from a simple experiment. We also observed the combined rotation and translation of a falling spring. The trajectory and velocity of the falling needle and the spring were obtained by using an image processing technique. We also conducted numerical simulation for both problems. For the falling-needle problem, we employed a theory; but it turns out that significant correction is required for the solutions to match the numerical and experimental data. For the falling spring problem various theoretical formula were tested for their justification, but none of the existing theories can successfully predict the numerical and experimental results.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.3053-3055
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• 2000

The Cellular Nonlinear Networks structure for Distance Transform (DT) and the robust optical flow detection algorithm based on the DT are proposed. The proposed algorithm is for detecting the optical flows on the trajectories only of the feature points. The translation lengths and the directions of feature movements are detected on the trajectories of feature points on which Distance Transform Field is developed. The robustness caused from the use of the Distance Transform and the easiness of hardware implementation with local analog circuits are the properties of the proposed structure, To verify the performance of the proposed structure and the algorithm, simulation has been done about zooming image.