• Journal of Information Processing Systems
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• v.19 no.6
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• pp.858-869
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• 2023

As one of the pivotal techniques of image restoration, single-channel blind source separation (SCBSS) is capable of converting a visual-only image into multi-source images. However, image degradation often results from multiple mixing methods. Therefore, this paper introduces an innovative SCBSS algorithm to effectively separate source images from a composite image in various mixed modes. The cornerstone of this approach is a novel triple generative adversarial network (TriGAN), designed based on dual learning principles. The TriGAN redefines the discriminator's function to optimize the separation process. Extensive experiments have demonstrated the algorithm's capability to distinctly separate source images from a composite image in diverse mixed modes and to facilitate effective image restoration. The effectiveness of the proposed method is quantitatively supported by achieving an average peak signal-to-noise ratio exceeding 30 dB, and the average structural similarity index surpassing 0.95 across multiple datasets.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.5
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• pp.623-629
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• 2004

In this paper, a Efficient method for the mixed image separation is presented using independent component analysis and the new fast expectation-maximization(EM) algorithm. In general, the independent component analysis (ICA) is one of the widely used statistical signal processing scheme in various applications. However, it has been known that ICA does not establish good performance in source separation by itself. So, Innovation process which is one of the methods that were employed in image separation using ICA, which produces improved the mixed image separation. Unfortunately, the innovation process needs long processing time compared with ICA or EM. Thus, in order to overcome this limitation, we proposed new method which combined ICA with the New fast EM algorithm instead of using the innovation process. Proposed method improves the performance and reduces the total processing time for the Image separation. We compared our proposed method with ICA combined with innovation process. The experimental results show the effectiveness of the proposed method by applying it to image separation problems.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.26 no.3
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• pp.156-184
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• 2022

In this article, we propose a novel variational model for restoring color images corrupted by mixed multiplicative Gamma noise and additive Gaussian noise. The model involves a data-fidelity term that characterizes the mixed noise as an infimal convolution of two noise distributions and the saturation-value total variation (SVTV) regularization. The data-fidelity term facilitates suitable separation of the multiplicative Gamma and Gaussian noise components, promoting simultaneous elimination of the mixed noise. Furthermore, the SVTV regularization enables adequate denoising of homogeneous regions, while maintaining edges and details and diminishing the color artifacts induced by noise. To solve the proposed nonconvex model, we exploit an alternating minimization approach, and then the alternating direction method of multipliers is adopted for solving subproblems. This contributes to an efficient iterative algorithm. The experimental results demonstrate the superior performance of the proposed model compared to other existing or related models, with regard to visual inspection and image quality measurements.

• Journal of KIISE:Information Networking
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• v.30 no.1
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• pp.24-29
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• 2003

In this paper, a new method for the mixed image separation is presented using the independent component analysis, the innovation process, and the expectation-maximization. In general, the independent component analysis (ICA) is one of the widely used statistical signal processing schemes, which represents the information from observations as a set of random variables in the from of linear combinations of another statistically independent component variables. In various useful applications, ICA provides a more meaningful representation of the data than the principal component analysis through the transformation of the data to be quasi-orthogonal to each other. which can be utilized in linear projection.. However, it has been known that ICA does not establish good performance in source separation by itself. Thus, in order to overcome this limitation, there have been many techniques that are designed to reinforce the good properties of ICA, which improves the mixed image separation. Unfortunately, the innovation process still needs to be studied since it yields inconsistent innovation process that is attached to the ICA, the expectation and maximization process is added. The results presented in this paper show that the proposed improves the image separation as presented in experiments.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.3
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• pp.294-299
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• 2005

This paper presents the separation performance of the linearly mixed image signals with additive noises by using an independent component analyses(ICAs) of the fixed-point(FP) algorithm based on Newton and secant method, respectively. The Newton's FP-ICA uses the slope of objective function, and the secant's FP-ICA also uses the tangent line of objective function. The 2 kinds of ICA have been applied to the 2 dimensional 2-image with $512\times512$ pixels. Then Gaussian noise and Laplacian noise are added to the mixed images, respectively. The experimental results show that the Newton's FP-ICA has better the separation speed than secant FP-ICA and the secant's FP-ICA has also the better separation rate than Newton's FP-ICA. Especially, the Newton and secant method gives relatively larger improvement degree in separation speed and rate as the noise increases.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.96.2-96
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• 2002

In this paper, a new method for the mixed image separation is presented using the independent component analysis, the innovation process, and the expectation-maximization. In general, the independent component analysis (ICA) is one of the widely used statistical signal processing scheme that represents the information from observations as a set of random variables in the form of linear combinations of another statistically independent component variables. In various useful applications, ICA provides a more meaningful representation of the data than the principal component analysis through the transformation of the data to be quasi-orthogonal to each other, which can be utilized in linear p...

• Membrane Journal
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• v.26 no.1
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• pp.38-42
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• 2016

Polyvinylpyrrolidone (PVP), which is glassy polymer to have amide functional group, was induced to fabricate the facilitated olefin transport membranes for olefin/paraffin separation. Separation performance for the mixed gas consisting of propylene and propane (50 : 50 vol%) was measured by gas chromatography and bubble flow meter. The properties of membranes were confirmed by scanning electron microscope and FT-IR. The results of long-term separation tests showed the selectivity of 15 and permeance of 1.3 GPU. The membranes was compared with poly(2-ethyl-2-oxazoline) $(POZ)/AgBF_4/Al(NO_3)_3$ membranes and the characteristics were confirmed as polymer matrix for facilitated transport membranes.

• The KIPS Transactions:PartB
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• v.13B no.6 s.109
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• pp.591-600
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• 2006

This paper describes the development and implementation of a algorithm to decompose word images from image regions mixed text/graphics in document images using statistical analyses. To decompose word images from image regions, the character components need to be separated from graphic components. For this process, we propose a method to separate them with an analysis of box-plot using a statistics of structural components. An accuracy of this method is not sensitive to the changes of images because the criterion of separation is defined by the statistics of components. And then the character regions are determined by analyzing a local crowdedness of the separated character components. finally, we devide the character regions into text lines and word images using projection profile analysis, gap clustering, special symbol detection, etc. The proposed system could reduce the influence resulted from the changes of images because it uses the criterion based on the statistics of image regions. Also, we made an experiment with the proposed method in document image processing system for keyword spotting and showed the necessity of studying for the proposed method.

• 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.

• Journal of Conservation Science
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• v.34 no.2
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• pp.107-118
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• 2018

This report does studied for making the method of conserving bracket murals in Daeungjeon of Jikjisa Temple, through the scientific way. Results of evaluated the conservation status at the braket mural paintings, most serious damage is structural damage like cracks, breakage, and delamination. After optical investigation, a characteristic point wasn't found such as underdrawing or traces of a coat of paint. The ultrasonic examination speed by each wall painting was measured from about 195.8 m/s to 392.7 m/s, according to the location of the surface, and it was able to compare the surface properties according to the location. In Infrared-thermal image measurement shows that wall layer separation and paint layer delamination are closely detected, therefore it was able to judge of damage on the objective way. Material analysis revealed that the walls were made by sand and weathering soil. The wall layer combined sand with less than fine sand size by nearly 5:5, and the finishing layer was found to have mixed medium sand and fine sand at approximately 6:4 rates. However, In case of finishing layer, mixing ratios of sizes less than very fine sand were found to be significantly lower than wall. Therefore, it is estimated that the plysical damage such as the separation between the layers of the walls created in the braket mural paintings, is continuously caused by changes in the internal stresses and volume ratio caused by the density differences between the wall and the finishing layers.