• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.3
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• pp.623-638
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• 2017

Application fields of cloud technologies have been gradually expanded with development of technology development and diversification of services. Cloud technology is used for investment efficiency, operation efficiency and service competitive advantage in digital broadcasting platform. Recently, Cloud broadcasting platform commercialized for UI(User Interface) and data broadcasting in Korea, and broadcasting service competition becomes fierce. Cloud technology of broadcasting provides remove a service dependency hardware resource and software architecture on STB device, and unified operation of user interface and service using cloud server without legacy separating management of STB types. In this paper, we explain application effects in image based cloud broadcasting service platform.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.6
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• pp.57-63
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• 2008

In this paper, we present an efficient noise reduction method using bivariate Gaussian density function in the wavelet domain. In our method, the probability model for the interstate dependency in the wavelet domain is modeled by bivariate Gaussian function, and then, the noise reduction is performed by Bayesian estimation. The statistical parameter for Bayesian estimation can be approximately obtained by the $H{\ddot{o}}lder$ inequality. The simulation results show that our method outperforms the previous methods using bivariate probability models.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.4C
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• pp.533-540
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• 2004

This paper proposes a new multispectral image data compression algorithm that can efficiently reduce spatial and spectral redundancies by applying classified prediction, a Karhunen-Loeve transform (KLT), and the three-dimensional set partitioning in hierarchical trees (3-D SPIHT) algorithm in the wavelet transform (WT) domain. The classification is performed in the WT domain to exploit the interband classified dependency, while the resulting class information is used for the interband prediction. The residual image data on the prediction errors between the original image data and the predicted image data is decorrelated by a KLT. Finally, the 3-D SPIHT algorithm is used to encode the transformed coefficients listed in a descending order spatially and spectrally as a result of the WT and KLT. Simulation results showed that the reconstructed images after using the proposed algorithm exhibited a better quality and higher compression ratio than those using conventional algorithms.

• Fashion & Textile Research Journal
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• v.16 no.2
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• pp.218-227
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• 2014

In this study, we ran a collage fashion illustration program. We used in depth personal interviews to find if there are any change in self-image by psychologically analyzing the features of self-images expressed in the pieces of fashion illustration. The total number of objects were five females students majoring in fashion design in Busan. They were hoping to have a psychology consultation to resolve their concerns about the future, family affairs, appearance, and careers. Collage fashion illustration program was used as a experimental tool to find the psychological features shown in the formats and content of collage fashion illustration. We then figure out how pre and post diagnosis were different from each other in terms of ego-identity and DAP. As a result, the formats in collage fashion illustration are related to the self images such as psychological energy, incompetency, suppression, and tendency of self-centered. Also, the contents of the fashion expression are related to the self-images such as dependency, avoidance, wariness, and self-regard. All of the participants have improved self-regard and active action due to improvements in subjectivity, initiative, and goal orientation. Therefore, they could change from pessimistic self-images to optimistic ones.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.2
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• pp.771-789
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• 2019

Text detection has been a popular research topic in the field of computer vision. It is difficult for prevalent text detection algorithms to avoid the dependence on datasets. To overcome this problem, we proposed a novel unsupervised text detection algorithm inspired by bootstrap learning. Firstly, the text candidate in a novel form of superpixel is proposed to improve the text recall rate by image segmentation. Secondly, we propose a unique text sample selection model (TSSM) to extract text samples from the current image and eliminate database dependency. Specifically, to improve the precision of samples, we combine maximally stable extremal regions (MSERs) and the saliency map to generate sample reference maps with a double threshold scheme. Finally, a multiple kernel boosting method is developed to generate a strong text classifier by combining multiple single kernel SVMs based on the samples selected from TSSM. Experimental results on standard datasets demonstrate that our text detection method is robust to complex backgrounds and multilingual text and shows stable performance on different standard datasets.

• Korean Journal of Remote Sensing
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• v.25 no.2
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• pp.95-105
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• 2009

Irregular temporal sampling is a common feature of geophysical and biological time series in remote sensing. This study proposes an on-line system for reconstructing observation image series including bad or missing observation that result from mechanical problems or sensing environmental condition. The surface parameters associated with the land are usually dependent on the climate, and many physical processes that are displayed in the image sensed from the land then exhibit temporal variation with seasonal periodicity. An adaptive feedback system proposed in this study reconstructs a sequence of images remotely sensed from the land surface having the physical processes with seasonal periodicity. The harmonic model is used to track seasonal variation through time, and a Gibbs random field (GRF) is used to represent the spatial dependency of digital image processes. In this study, the Normalized Difference Vegetation Index (NDVI) image was computed for one week composites of the Advanced Very High Resolution Radiometer (AVHRR) imagery over the Korean peninsula, and the adaptive reconstruction of harmonic model was then applied to the NDVI time series from 1996 to 2000 for tracking changes on the ground vegetation. The results show that the adaptive approach is potentially very effective for continuously monitoring changes on near-real time.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.2
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• pp.74-79
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• 2011

HDR(high dynamic range) imaging techniques supports wider dynamic range than normal images captured from general still camera. These usually need several shots to obtain LDR(low dynamic range) images, causing ghosting artifacts. Accordingly, this paper suggests a method to generate new LDR images from a single Bayer image using Exposure LUT(look-up table) by considering channel dependency. We prior construct exposure LUT for each RGB channel, showing the relationship between input and average output luminance values. In the process, by applying the average luminance of input image and current exposure to LUT, new exposures which are determined by user choice are first estimated. Next, LDR images which are corresponded to new exposures are generated based on each LUT. Saturated areas are improved by considering channel dependency in the last procedure. In the experimental comparison, high PSNR values are obtained between estimated and captured images. Also, we have similar appearance on displayed images.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.24 no.3
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• pp.382-389
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• 2000

The instantaneous and ensemble averaged flow characteristics of a round jet issuing normally into a crossflow was studied using a flow visualization technique and Particle Image Velocimetry measurements. Experiments were performed at a jet-to-crossflow velocity ratio, 3.3, and two Reynolds numbers, 1050 and 2100, based on crossflow velocity and jet diameter. Instantaneous laser tomographic images of the vertical center plane of the crossflow jet showed that there exist very different natures in the flow structures of the near field jet even though the velocity ratio is the same. It was found that the shear layer becomes much thicker when the Reynolds number is 2100 due to the strong entrainment of the inviscid fluid by turbulent interaction between the jet and crossflow. The mean and second order statistics were calculated by ensemble averaging over 1000 realizations of instantaneous velocity fields. The detail characteristics of mean flow field, stream wise and vertical r.m.s. velocity fluctuations, and Reynolds shear stress distributions were presented. The new PlV results were compared with those from previous experimental and LES studies.

• Journal of Biomedical Engineering Research
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• v.17 no.3
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• pp.365-372
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• 1996

The researches to acquire diagnostic parameters from ultrasonic images are advanced with the progress of the digital image processing technique. Especially, the detection of endocardial boundary is very important in ultrasonic images, because endocardial boundary is used as a clinical parameter to estimate both the cardiac area and the variation of cardiac volume. Various methods to detect cardiac boundary are proposed, but these are insufficient to detect boundary. In this paper, an algorithm that detects the endocardial boundary, expanding the cavity region from the center using statistical information, is proposed The value of mean and sty:nd, wd deviation in cavity region is lower than those in muscle re- gion. Therefore, if we define the multiplication of mean and standard deviation as homogeneous coefficient, it can lead to conclusion that the pixels with small variation of these coefficleno are cavity region, and extraction of endocardial boundary from cavity region is possible. The proposed method detected endocardial boundary more effectively than edge based or threshold based method and is robuster to noise than radial searching method that has high dependency for center position.

• Journal of the Optical Society of Korea
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• v.17 no.3
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• pp.262-268
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• 2013

We study the focusing properties of a two-dimensional square-lattice photonic crystal (PC) comprising silica and germanium partitioned cylinders in air background. The finite difference time domain (FDTD) method with periodic boundary condition is utilized to calculate the dispersion band diagram and the FDTD method incorporating the perfectly matched layer boundary condition is employed to simulate the image formation. In contrast to the common square PCs in which the negative refraction effect occurs in the first photonic band without negative phase propagation, in our suggested model system, the frequency with negative refraction exists in the second band and in near-infrared region. In this case, the wave propagates with a negative phase velocity and the evanescent waves can be supported. We also discuss the dependency of the image resolution and its location on surface termination, source location, and slab thickness. According to the simulation results, spatial resolution of the proposed PC lens is below the radiation wavelength.