• Textile Coloration and Finishing
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• v.32 no.1
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• pp.57-64
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• 2020

In this study, alginate-gelatin/silk wet-laid nonwoven fabrics were prepared by using alginate gelatin fiber and silk fiber, as the main fiber, and PVA fiber as binder fiber. The characterization of pore size and mechanical property was carried out on the various weight ratios of alginate gelatin fiber and silk fibers, or the adding binder fibers. As the content of silk or binder fiber increases, the tensile strength increases from 0.70 kgf/㎠ to 5.08 kgf/㎠ and the pore size decreases 111.6 ㎛ to 51.00 ㎛. As the weight of the silk increased, the density increased, and binder fiber was added to enhance the cohesion between fibers, thereby increasing the wet-laid nonwoven fabric strength. We studied on wet-laid nonwoven fabrics that can be applied to mask sheet with adjustable pore size.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.207-209
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• 2021

In recent years, with the development of artificial intelligence and IoT technology, automation and unmanned technology are in progress in various fields, and the importance of image processing such as object tracking, medical images and object recognition, which are the basis of this, is increasing. In particular, in systems requiring detailed data processing, noise reduction is used as a pre-processing step, but the existing algorithm has a disadvantage that blurring occurs in the filtering process. Therefore, in this paper, we propose a filter algorithm using modified spatial weights to minimize information loss in the filtering process. The proposed algorithm uses mask matching to remove AWGN, and obtains the output of the filter by adding or subtracting the output of the modified spatial weight. The proposed algorithm has superior noise reduction characteristics compared to the existing method and reconstructs the image while minimizing the blurring phenomenon.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.121-123
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• 2021

Image processing is being used in various forms in important fields of the 4th industrial revolution, such as artificial intelligence, smart factories, and the IoT industry. In particular, in systems that require data processing such as object tracking, medical images, and object recognition, noise removal is used as a preprocessing step, but the existing algorithm has a drawback in that blurring occurs in the filtering process. Therefore, in this paper, we propose a filter algorithm using switching fuzzy weights. The proposed algorithm switches the fuzzy function by dividing the low-frequency region and the high-frequency region by the standard deviation of the filtering mask, and obtains the final output according to the fuzzy weight. The proposed algorithm showed improved results compared to the existing method, and showed excellent characteristics in the region where the high-frequency component is strong.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.250-252
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• 2022

Recently, with the development of IoT technology and AI, unmanned and automated systems are progressing in various fields, and various application technologies are being studied in systems using algorithms such as object detection, recognition, and tracking. In the case of a system operating based on an image, noise removal is performed as a pre-processing process, and precise noise removal is sometimes required depending on the environment of the system. In this paper, we propose a modified central weight filter algorithm using pixel division of local regions to minimize the blurring that tends to occur in the filtering process and to emphasize the details of the resulting image. In the proposed algorithm, when a pixel of a local area is divided into two areas, the center of the dominant area among the divided areas is set as a criterion for the weight filter algorithm. The resulting image is calculated by convolving the transformed center weight with the pixel value inside the filtering mask.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.6
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• pp.867-873
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• 2018

Recently, interests in the field of image processing have increased with the increased demand for digital imaging devices. However, digital images are damaged by the noise generated by various causes during image processing. Generally in digital imaging devices, noise such as AWGN, etc. is generated and performance and reliability are deteriorated, and various researches are in progress to remove it. Accordingly in the present paper, an algorithm to protect the high frequency components of the images and to efficiently remove AWGN is proposed. The proposed algorithm calculates the final output by adjusting estimate values applied with Gaussian mask and weight values applied according to the local mask distribution. And for performance evaluation of the proposed algorithm, simulations were performed with the existing methods, and the characteristics were compared through PSNR and the processed, enlarged images.

• 전자공학회논문지 IE
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• v.45 no.4
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• pp.47-53
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• 2008

A new intra-field deinterlacing algorithm with edge direction vector (EDV) in the image block is introduced. This proposed filter is suitable to the region with high motion or scene change. We first introduce an EDV, which is computed by Sobel mask used edge map, so that filer resolution of the edge direction can be acquired. The proposed EDV oriented deinterlacing system operates by identifying small pixel variations in five orientations, $26.5^{\circ}$, $45^{\circ}$, $90^{\circ}$, $135^{\circ}$, and $153.5^{\circ}$. The EDV values work as inputs of Sobel mask and return edge direction degree and confidence parameters. Based on edge direction degree and confidence parameters the missing pixel is computed. The results of computer simulations demonstrate that the proposed method outperforms a number of intra-field deinterlacing methods in the literature.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.9
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• pp.179-190
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• 1999

To automate the polishing process, a polishing robot with two axes which is attached to a machining center with three axes has been developed by our previous research. This automatic polishing robot is able to keep the polishing tool normal to the curved surface of die and is able to maintain a constant pneumatic pressure. Therefore, in the case of a curved surface die, the surface roughness to be polished by the system with five axes is improved superior than the surface by a three-axis machining center. However, because the polishing robot was big and heavy, a polishing workspace was limited and then it was difficult to attach the robot to machining center. In this study, the smaller and lighter polishing robot than the previous has been designed to improve defects due to the magnitude and weight of the robot. And the sliding mode control ins applied to polishing robot to improve the tracking performance. To obtain switching parameters of sliding mode control, the signal compression method is used. Code separation program to separate the date for a three-axis machining center and a two-axis polishing robot from a five-axis NC data is improved for users to check conveniently the separated trajectory and to handle many data by using the graphic user interface. To evaluate the polishing performance of the developed robot, the polishing experiment for shadow mask was carried out. The result shows the automatic polishing robot has a good trajectory tracking performance and obtains a good polished workpiece efficiently under recommended polishing conditions.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 1999.08a
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• pp.10-21
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• 1999

Recent progress in manufacture of hot and cold rolled steel strip products and their applications were reviewed. The main trend in the technological development has been to meet the customers' requests for quality improvement and cost reduction. The weight reduction to reduce the fuel consumption is the main issue in the automotive industry and, therefore, various steels have been developed to improve formability as well as strength. The steels include super-EDDQ steels, bainitic steels, TRIP steels, etc. In the oil industry, efforts have been focused to improve strength together with either low temperature toughness or HIC/SSCC resistance. The packaging industry is also a highly competitive market, and steel and canmaking companies have worked cooperatively to develop cost-effective canmaking processes as well as high performance steels. This type of cooperation has also been found important in other industries such as the appliance and electronic industries for the benefits of both steelmakers and customers.

• Publications of The Korean Astronomical Society
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• v.30 no.2
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• pp.671-673
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• 2015

Before analyzing the images taken with a Mosaic CCD imager, the images have to reach a state which can be used for further scientific analysis. The transformation of raw images into calibrated images is called data reduction. Transforming HEavely Light into Images (THELI) is a nearly fully automated reduction pipeline software (Erben et al., 2005). This pipeline works on raw images to remove instrumental signatures, mask unwanted signals, and perform photometric and astrometric calibration. Finally THELI constructs a deep co-added mosaic image and a weight map. In this poster, THELI data reduction procedures will be reviewed and the reduction process for raw images of seven X-ray bright groups, extracted from GEMS groups (Osmond & Ponman, 2004) obtained by the Wide Field Imager (WFI) mounted on MPG/ESO telescope at La Silla in March 2006 will be discussed.

• Journal of information and communication convergence engineering
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• v.19 no.1
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• pp.54-60
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• 2021

Various digital devices were supplied throughout the Fourth Industrial Revolution. Accordingly, the importance of data processing has increased. Data processing significantly affects equipment reliability. Thus, the importance of data processing has increased, and various studies have been conducted on this topic. This study proposes a modified Gaussian filter algorithm based on a fuzzy membership function. The proposed algorithm calculates the Gaussian filter weight considering the standard deviation of the filtering mask and computes an estimate according to the fuzzy membership function. The final output is calculated by adding or subtracting the Gaussian filter output and estimate. To evaluate the proposed algorithm, simulations were conducted using existing additive white Gaussian noise removal algorithms. The proposed algorithm was then analyzed by comparing the peak signal-to-noise ratio and differential image. The simulation results show that the proposed algorithm has superior noise reduction performance and improved performance compared to the existing method.