• Journal of KIISE:Computer Systems and Theory
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• v.27 no.3
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• pp.235-244
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• 2000

This paper addresses a new method for constructing surface representation of 3D structures from a sequence of tomographic cross-sectional images, Firstly, we propose cell-boundary representation by transforming the cuberille space into cell space. A cell-boundary representation consists of a set of boundary cells with their 1-voxel configurations, and can compactly describe binary volumetric data. Secondly, to produce external surface from the cell-boundary representation, we define 19 modeling primitives (MP) including volumetric, planar and linear groups. Surface polygons are created from those modeling primitives using a simple table look-up operation. Comparing with previous method such as Marching Cube or PVP algorithm, our method is robust and does not make any crack in resulting surface model. Hardware implementation is expected to be easy because our algorithm is simple(scan-line), efficient and guarantees data locality in computation time.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.40 no.4
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• pp.227-236
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• 2003

This paper proposes a modified jointly-blue noise mask (MJBNM) method using the S-CIELAB color measure as digital color halftoning method. Based on an investigation of the relation between the pattern visibility and the chromatic error, of a blue noise pattern, a halftoning method is proposed that reduces the chromatic error, while preserving a high quality blue noise pattern. Accordingly, to reduce the chrominance error, the low-pass filtered error and S-CIELAB chrominance error are both considered during the mask generation procedure and calculated for single and combined patterns. Using the calculated low-pass filtered error, the patterns are then updated by either adding or removing dots from the multiple binary patterns. Finally, the pattern exhibiting the lower S-CIELAB chrominance error is selected. Experimental results demonstrated that the proposed algorithm can produce a visually pleasing half toned image with a lower chrominance error than the JBNM method.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.6
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• pp.61-71
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• 2004

Recently, various techniques for face detection are studied, but most of them still have problems on processing in real-time. Therefore, in this paper, we propose novel techniques for real-time detection of human faces in sequential images using motion and chroma information. First, background model is used to find a moving area. In this procmoving area. edure, intensity values for reference images are averaged, then skin-color are detected in We use HCr color-space model and adaptive threshold method for detection. Second, binary image labeling is applied to acquire candidate regions for faces. Candidates for mouth and eyes on a face are obtained using differences between green(G) and blue(B), intensity(I) and chroma-red(Cr) value. We also considered distances between eye points and mouth on a face. Experimental results show effectiveness of real-time detection for human faces in sequential images.

• Journal of the Korea Fashion and Costume Design Association
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• v.17 no.3
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• pp.135-148
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• 2015

The purpose of this study was to research into TV makeup types focusing on Korean aesthetics with recognizing importance of Korean thought amid what the global interest pays attention to South Korea thanks to the recent influence of Hanryu(Korean wave). The following are summary and result of this study. The non-dual beauty is an integrative concept of including ambivalence on the categorical difference in sex, culture and class by transcending the extreme binary division. As this is what reflected the open thought of pursuing balance of yin and yang in Korean people, it is being shown in the form of transcendence and far-outness through TV entertainment programs. Transcendence coexisted with maintaining relative relationship beyond separation in sex. Far-outness was pursuing free sensitivity immanent in the non-separated thought of transcending the past, the present and future. This trend is being indicated similarly to a change in its paradigm from separation to convergence these days. Accordingly, even makeup was showing similarity to the recent trend with being paid attention to the makeup of focusing on identity in sex and to the makeup of being coexisted the past, the present and future with the aspect of being mixed space time. The Korean aesthetics has been feeble in its influence compared to the Oriental image of focusing on China and Japan in the meantime. Hence, this study can be said to have significance in a sense of being the first consideration that compared TV makeup types of focusing on Korean aesthetics and suggested its developmental direction.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.2A
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• pp.95-104
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• 2012

Pattern recognition using ensemble classifiers is composed of strong classifier which consists of many weak classifiers. In this paper, we used feature extraction to organize strong classifier using static camera sequence. The strong classifier is made of weak classifiers which considers environmental factors. So the strong classifier overcomes environmental effect. Proposed method uses binary foreground image by frame difference method and the boosting is used to train crowdedness model and recognize crowdedness using features. Combination of weak classifiers makes strong ensemble classifier. The classifier could make use of potential features from the environment such as shadow and reflection. We tested the proposed system with road sequence and subway platform sequence which are included in "AVSS 2007" sequence. The result shows good accuracy and efficiency on complex environment.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.47 no.1
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• pp.1-14
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• 2010

With the rapid growth of 3D content industry fields, 3D content-based hashing (or hash function) has been required to apply to authentication, trust and retrieval of 3D content. A content hash can be a random variable for compact representation of content. But 3D content-based hashing has been not researched yet, compared with 2D content-based hashing such as image and video. This paper develops a robust 3D content-based hashing based on key-dependent 3D surface feature. The proposed hashing uses the block surface coefficient using shape coordinate of 3D SSD and curvedness for 3D surface feature and generates a binary hash by a permutation key and a random key. Experimental results verified that the proposed hashing has the robustness against geometry and topology attacks and has the uniqueness of hash in each model and key.

• Korean Journal of Optics and Photonics
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• v.12 no.1
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• pp.61-66
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• 2001

Defocused Fourier plane holograms are stored in disk-type holographic memories where thin recording media are used, the areal storage density per hologram and the intensity uniformity of the signal beam at the recording plane are studied. As the pixel pitch of the spatial light modulator that represents binary data increases, the storage density per hologram increases if exact Fourier holograms are stored. When defocused Fourier plane holograms are stored, however, we show that there exists an optimal pixel pitch that maximizes the area storage density per hologram in general, to increase the areal storage density per hologram, f/# of the Fourier transform lens that focuses the data image should be as small as possible. In this case, not only the intensity distribution at the recording plane but also the recording area becomes very sensitive to the degree of defocusing. Therefore, even if the exact Fourier plane holograms are stored, the defocusing effect owing to the medium thickness should be taken into account to achieve the maximal areal storage density per hologram.logram.

• Journal of The Korean Astronomical Society
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• v.52 no.6
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• pp.217-225
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• 2019

We apply a modified Convolutional Neural Network (CNN) model in conjunction with transfer learning to predict whether an active region (AR) would produce a ≥C-class or ≥M-class flare within the next 24 hours. We collect line-of-sight magnetogram samples of ARs provided by the SHARP from May 2010 to September 2018, which is a new data product from the HMI onboard the SDO. Based on these AR samples, we adopt the approach of shuffle-and-split cross-validation (CV) to build a database that includes 10 separate data sets. Each of the 10 data sets is segregated by NOAA AR number into a training and a testing data set. After training, validating, and testing our model, we compare the results with previous studies using predictive performance metrics, with a focus on the true skill statistic (TSS). The main results from this study are summarized as follows. First, to the best of our knowledge, this is the first time that the CNN model with transfer learning is used in solar physics to make binary class predictions for both ≥C-class and ≥M-class flares, without manually engineered features extracted from the observational data. Second, our model achieves relatively high scores of TSS = 0.640±0.075 and TSS = 0.526±0.052 for ≥M-class prediction and ≥C-class prediction, respectively, which is comparable to that of previous models. Third, our model also obtains quite good scores in five other metrics for both ≥C-class and ≥M-class flare prediction. Our results demonstrate that our modified CNN model with transfer learning is an effective method for flare forecasting with reasonable prediction performance.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.38 no.10
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• pp.721-727
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• 2001

In this paper, we propose a two-dimensional interleaving structure of holographic digital data storage. In this storage, many of the digital binary data are recorded, retrieved and processed in a two-dimensional data image (1000$\times$1000 bits). Therefore, burst errors in this digital device also have two-dimensional characteristics and it is required to use effective two-dimensional interleaving to overcome them. Bits of every code word should be distributed in an equilateral triangular lattice structure when they are scattered considering the random shape and occurrence of burst errors. We deal with factors and algorithm to construct this interleaving structure of equilateral triangular lattice.

• Smart Media Journal
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• v.4 no.4
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• pp.18-23
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• 2015

In this paper, we propose a method for detecting the number of clusters. This method can improve the performance of a gaussian mixture model function in conventional markov random field method by using the tensor voting. The key point of the proposed method is that extracts the number of the center through the continuity of saliency map of the input data of the tensor voting token. At first, we separate the foreground and background region candidate in a given natural images. After that, we extract the appropriate cluster number for each separate candidate regions by applying the tensor voting. We can make accurate modeling a gaussian mixture model by using a detected number of cluster. We can return the result of natural binary text image by calculating the unary term and the pairwise term of markov random field. After the experiment, we can confirm that the proposed method returns the optimal cluster number and text binarization results are improved.