• Journal of Korea Society of Industrial Information Systems
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• v.6 no.2
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• pp.16-22
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• 2001

In this paper we mose a new scheme for recognition of deformed letters by extracting feature vectors based on Gibbs distributions which are well suited for representing the spatial continuity. The extracted feature vectors are comprised of 2-D conditional moments which are invariant under translation, rotation, and scale of an image. The Algorithm for pattern recognition of deformed letters contains two parts: the extraction of feature vector and the recognition process. (i) We extract feature vector which consists of an improved 2-D conditional moments on the basis of estimated conditional Gibbs distribution for an image. (ii) In the recognition phase, the minimization of the discrimination cost function for a deformed letters determines the corresponding template pattern. In order to evaluate the performance of the proposed scheme, recognition experiments with a generated document was conducted. on Workstation. Experiment results reveal that the proposed scheme has high recognition rate over 96%.

• Journal of The Korean Digital Architecture Interior Association
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• v.8 no.1
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• pp.65-74
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• 2008

Light creates ambiance that affects our impression of space. Before the modern age, the role of light is a religious factor and a primitive state to see. In the modern space design, light is used to achieve the continuous transformation and translation of building's image. Ever-changing space is a flexible corresponding of space to its environment, caused by certain dynamic light. The space turn into some other thing from what it was before, or just changing its character. approaching men and society with different meanings. The purpose of this study is to explore the relation between light(natural and artificial) and ever-changing space through the case study. The impacts of light on ever-changing in today's space design can be summarized as follows. 1) Materialization of light in space design. Nowadays light becomes a form itself. The geometric properties of the space form playa secondary role as compared to the importance assigned to light. 2) Pixelization of space by a light effect. The impacts of digital technology on the space design have come through enhancing the 'pixelization' of the surface from which buildings are made their responsiveness and adaptability to changing needs. The surface with ever-changing lights that blur the boundary of space and expand the image of space.

• Journal of the Korean Society for Nondestructive Testing
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• v.10 no.1
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• pp.47-55
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• 1990

This paper presents experimental results which explore the capability of a CW laser speckle photography for tile measurement of in-plane displacement at high temperature. The serious restrictions on the application of the method seem to be the ambient air turbulence and the change of surface texture caused by the oxidation, as they tend to decorrelate the double exposured speckle patterns. In order to assess only the effect of air turbulence, a ceramics-coated stainless steel plate is heated in air and Ar-laser specklegrams are made with combination of temperature and lateral translation displacement. The slight reduction in visibility of Young's fringes is observed at $1000^{\circ}C$. The analyses of Young's fringes are carried out by a image processing system using a TV-camera and computers, and the result agrees well with the micrometer reading. Futhermore, uncoated stainless steel and Hastelloy X plates are tested and the effect of oxidation is also evaluated. The experimental results demonstrate that a CW laser speckle photography is applicable at temperatures up to $1000^{\circ}C$.

• The Bulletin of The Korean Astronomical Society
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• v.44 no.1
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• pp.81.2-81.2
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• 2019

We develop an image-to-image translation model, which is a popular deep learning method based on conditional Generative Adversarial Networks (cGANs), to generate solar magnetograms and EUV images from sunspot drawings. For this, we train the model using pairs of sunspot drawings from Mount Wilson Observatory (MWO) and their corresponding SDO/HMI magnetograms and SDO/AIA EUV images (512 by 512) from January 2012 to September 2014. We test the model by comparing pairs of actual SDO images (magnetogram and EUV images) and the corresponding AI-generated ones from October to December in 2014. Our results show that bipolar structures and coronal loop structures of AI-generated images are consistent with those of the original ones. We find that their unsigned magnetic fluxes well correlate with those of the original ones with a good correlation coefficient of 0.86. We also obtain pixel-to-pixel correlations EUV images and AI-generated ones. The average correlations of 92 test samples for several SDO lines are very good: 0.88 for AIA 211, 0.87 for AIA 1600 and 0.93 for AIA 1700. These facts imply that AI-generated EUV images quite similar to AIA ones. Applying this model to the Galileo sunspot drawings in 1612, we generate HMI-like magnetograms and AIA-like EUV images of the sunspots. This application will be used to generate solar images using historical sunspot drawings.

• The Bulletin of The Korean Astronomical Society
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• v.44 no.1
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• pp.51.2-51.2
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• 2019

Multi-wavelength observations become very popular in astronomy. Even though there are some correlations among different sensor images, it is not easy to translate from one to the other one. In this study, we apply a deep learning method for image-to-image translation, based on conditional generative adversarial networks (cGANs), to solar images. To examine the validity of the method for scientific data, we consider several different types of pairs: (1) Generation of SDO/EUV images from SDO/HMI magnetograms, (2) Generation of backside magnetograms from STEREO/EUVI images, (3) Generation of EUV & X-ray images from Carrington sunspot drawing, and (4) Generation of solar magnetograms from Ca II images. It is very impressive that AI-generated ones are quite consistent with actual ones. In addition, we apply the convolution neural network to the forecast of solar flares and find that our method is better than the conventional method. Our study also shows that the forecast of solar proton flux profiles using Long and Short Term Memory method is better than the autoregressive method. We will discuss several applications of these methodologies for scientific research.

• The Bulletin of The Korean Astronomical Society
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• v.44 no.1
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• pp.81.3-81.3
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• 2019

In this study, we apply conditional Generative Adversarial Network, which is one of the deep learning method, to the image-to-image translation from solar magentograms to solar UV and EUV images. For this, we train a model using pairs of SDO/AIA 9 wavelength UV and EUV images and their corresponding SDO/HMI line-of-sight magnetograms from 2011 to 2017 except August and September each year. We evaluate the model by comparing pairs of SDO/AIA images and corresponding generated ones in August and September. Our results from this study are as follows. First, we successfully generate SDO/AIA like solar UV and EUV images from SDO/HMI magnetograms. Second, our model has pixel-to-pixel correlation coefficients (CC) higher than 0.8 except 171. Third, our model slightly underestimates the pixel values in the view of Relative Error (RE), but the values are quite small. Fourth, considering CC and RE together, 1600 and 1700 photospheric UV line images, which have quite similar structures to the corresponding magnetogram, have the best results compared to other lines. This methodology can be applicable to many scientific fields that use several different filter images.

• The Bulletin of The Korean Astronomical Society
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• v.44 no.2
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• pp.43.1-43.1
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• 2019

In this study, we apply a deep learning model to denoising solar magnetograms. For this, we design a model based on conditional generative adversarial network, which is one of the deep learning algorithms, for the image-to-image translation from a single magnetogram to a denoised magnetogram. For the single magnetogram, we use SDO/HMI line-of-sight magnetograms at the center of solar disk. For the denoised magnetogram, we make 21-frame-stacked magnetograms at the center of solar disk considering solar rotation. We train a model using 7004 paris of the single and denoised magnetograms from 2013 January to 2013 October and test the model using 1432 pairs from 2013 November to 2013 December. Our results from this study are as follows. First, our model successfully denoise SDO/HMI magnetograms and the denoised magnetograms from our model are similar to the stacked magnetograms. Second, the average pixel-to-pixel correlation coefficient value between denoised magnetograms from our model and stacked magnetogrmas is larger than 0.93. Third, the average noise level of denoised magnetograms from our model is greatly reduced from 10.29 G to 3.89 G, and it is consistent with or smaller than that of stacked magnetograms 4.11 G. Our results can be applied to many scientific field in which the integration of many frames are used to improve the signal-to-noise ratio.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.11
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• pp.79-88
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• 1999

In this paper we address the tracking method which tracks only target object in image sequence including moving object. We use a contour tracking algorithm based on intensity and motion boundaries. The motion of the moving object contour in the image is assumed to be well describable by an affine motion model with a translation, a change in scale and a rotation. The moving object contour is represented by B-spline, the position and motion of which is estimated along the image sequence. we use pattern recognition to identify target object. In order to use linear Kalman Filters we decompose the estimation process into two filters. One is estimating the affine motion parameters and the other the shape of moving object contour. In some experiments with dial plate we show that this method enables us to obtain the robust motion estimates and tracking trajectories even in case of including obstructive object.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.38 no.4
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• pp.434-441
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• 2001

We present an image retrieval method for improving retrieval performance by the effective fusion of spatial histogram and wavelet moments. In this method, the similarity for spatial histograms and the similarity for wavelet moment are effectively fused in the computation of the similarity between a query image and DB image. That is, the wavelet moments feature represented in multi-resolution and the spatial histogram feature robust to translation and rotation are used to improve retrieval performance. In order to evaluate the performance of the proposed method, we use Brodatz texture DB, MPEG-7 T1 DB, and Corel Draw Photo DB. Experimental results show that the proposed method yields 5.3% and 13.8% better Performances for Brodatz DB, and 15.5% and 3.2% better Performances for Corel Draw Photo DB over the histogram method and the wavelet moment method, respectively.

• Journal of Korea Multimedia Society
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• v.7 no.7
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• pp.956-966
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• 2004

The Korean animation has enjoyed the brisk formation and establishment of its world-class infra for the last several years without unified titles or concepts, under the name of a national strategic project in the age of digital image. It also enjoys its new evaluation as digital animation that it's one of the greatest money making business in the non-education and frivolous culture and has the closest relations with the modern time. A great portion of popular image media has been taken by animation for the last 30 years. In this paper we propose a motion algorithm using an animation technology. It was developed for education purposed and accessible through the internet. For instance, in Cyber Clam Museum, 1000 gesture contents, the visual processes were used to design a screen with a realistic image and create an animation that makes possible show at 360 and every such transformation as translation, rotation, and scaling can be applied in the image interactively for the convenient and effective viewing.