• The Research Journal of the Costume Culture
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• v.29 no.2
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• pp.289-306
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• 2021

The study aims to define the Korean Wave as global attention to Korea's unique culture and consider the specificity of traditional Korean fashion images in Korean Wave content. The research method of this study is a case study through literature research. In order to collect Korean Wave content on YouTube, 24 channels with the highest number of views were selected from among content uploaded from 2018 to the present through keyword search, and up to two channels with high views showing traditional Korean fashion images. As a result of selecting the analysis target, 41 Korean Wave videos and 368 costumes were selected and analyzed based on fashion style elements, including item, color, detail, motif, styling, silhouette, and accessory. As a result of the study, music, broadcast, fashion, and other content were found in the Korean Wave content fields in which Korean fashion style appeared, and the characteristics of each field were derived. Music content was characterized by fashion style excluding stereotypes about traditional Korean costume, broadcast and fashion content was characterized by fashion style inherited from traditional costume, and other content was characterized by symbolic fashion style of traditional culture. This study is meaningful in revealing the formative characteristics of traditional Korean design elements recently shared online through the study of Korean traditional fashion images in Korean Wave content.

• Journal of KIBIM
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• v.12 no.1
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• pp.55-61
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• 2022

Recently, demand for designing own space is increasing as the rapid growth of home furnishing market. However, there is a limitation that it is not easy to compare the style between before construction view and after view. This study aims to translate real image into another style with GAN model learned with interior images. To implement this, first we established style criteria and collected modern, natural, and classic style images, and experimented with ResNet, UNet, Gradient penalty concept to CycleGAN algorithm. As a result of training, model recognize common indoor image elements, such as floor, wall, and furniture, and suitable color, material was converted according to interior style. On the other hand, the form of furniture, ornaments, and detailed pattern expressions are difficult to be recognized by CycleGAN model, and the accuracy lacked. Although UNet converted images more radically than ResNet, it was more stained. The GAN algorithm allowed us to represent results within 2 seconds. Through this, it is possible to quickly and easily visualize and compare the front and after the interior space style to be constructed. Furthermore, this GAN will be available to use in the design rendering include interior.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.4
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• pp.173-180
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• 2022

In the naked eye observation, the health of livestock can be controlled by the range of activity, temperature, pulse, cough, snot, eye excrement, ears and feces. In order to confirm the health of livestock, this paper uses calf face image data to classify the health status by image shape, color and texture. A series of images that have been processed in advance and can judge the health status of calves were used in the study, including 177 images of normal calves and 130 images of abnormal calves. We used GLCM calculation and Convolutional Neural Networks to extract 6 texture attributes of GLCM from the dataset containing the health status of calves by detecting the image of calves and learning the composite image of Convolutional Neural Networks. In the research, the classification ability of GLCM-CNN shows a classification rate of 91.3%, and the subsequent research will be further applied to the texture attributes of GLCM. It is hoped that this study can help us master the health status of livestock that cannot be observed by the naked eye.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.3
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• pp.268-274
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• 2023

Image mosaicking is one of the basic and important technologies in the field of application using images. The key of image mosaicking is to extract seamlines from a joint image. The method proposed in this paper for image mosaicking is as follows. The feature points of the images to be joined are extracted and the joining form between the two images is identified. A reference position for detection the seamlines were selected according to the joint form, and an image pyramid was created for efficient image processing. The outlines of the image including buildings and roads are extracted from the overlapping area with low resolution, and the seamlines are determined by considering the components of the outlines. Based on this, the seamlines in the high-resolution image was re-searched and finally the seamline for image mosaicking was determined. In addition, in order to minimize color distortion of the image with the determined seamline, a method of improving the quality of the mosaic image by fine correction of the mosaic area was applied. It was confirmed that the quality of the seamline extraction results applying the method proposed was reasonable.

• Journal of the Korea Society of Computer and Information
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• v.29 no.10
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• pp.89-96
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• 2024

In this paper, we propose a deep learning model and inference pipeline that can process high-resolution fog video in real-time, addressing limitations found in classical defogging algorithms and existing deep learning-based defogging models. The key idea is separating the tasks of inferring fog color and estimating the amount of fog into two distinct models, allowing for a more efficient, lightweight design that improves inference speed. While many deep defogging models perform well on synthetic fog images, they suffer from reduced effectiveness on real-world fog images with diverse fog colors and backgrounds. We solve this problem by introducing a synthetic fog dataset generation method tailored for real-world conditions. Through experiments, we demonstrate the increase in visible distance achieved by proposed model and compare its inference speed and defogging performance against pre-trained models on real-world CCTV fog images.

• The Journal of the Korea Contents Association
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• v.5 no.4
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• pp.150-159
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• 2005

With the increase of interest in ubiquitous computing, image code is attracting attention in various areas. Image code is important in ubiquitous computing in that it can complement or replace RFID (radio frequency identification) in quite a few areas as well as it is more economical. However, because of the difficulty in reading precise colors due to the severe distortion of colors, its application is quite restricted by far. In this paper, we present an efficient method of image code recognition including automatically locating the image code using the hue and saturation values. In our experiments, we use an image code whose design seems most practical among currently commercialized ones. This image code uses six safe colors, i.e., R, G, B, C, M, and Y. We tested for 72 true-color field images with the size of $2464{\times}1632$ pixels. With the color calibration based on the histogram, the localization accuracy was about 96%, and the accuracy of color classification for localized codes was about 91.28%. It took approximately 5 seconds to locate and recognize the image code on a PC with 2 GHz P4 CPU.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.46 no.1
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• pp.85-91
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• 2009

Recently, the LCD has high market share in TV market. The use of motion images in portable devices like DMB, PMP and Cell Phone is growing rapidly. One of the technique of enhancing the LCD's characteristic which is the slow response time. But, the technique requires a lot of memory usage, because of the requirement of frame memory. In this paper, we propose a reduction method for the frame memory that is required for LCD overdrive. Proposed overdrive architecture based on modified DWT-Inverse DWT and Color Conversion. The proposed architecture has a considerable PSNR. At once, it uses 50% of frame memory size and reduces 15% of frame memory size compare with previous architecture. The design was implemented using Xilinx Vertex4 and had 2172 Slice except Memory.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.2
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• pp.48-55
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• 2008

In this paper we propose a novel method for image retrieval system using image segmentation and salient points. The proposed method consists of four steps. In the first step, images are segmented into several regions by JSEG algorithm. In the second step, for the segmented regions, dominant colors and the corresponding color histogram are constructed. By using dominant colors and color histogram, we identify candidate regions where objects may exist. In the third step, real object regions are detected from candidate regions by SIFT matching. In the final step, we measure the similarity between the query image and DB image by using the color correlogram technique. Color correlogram is computed in the query image and object region of DB image. By experimental results, it has been shown that the proposed method detects multi-object very well and it provides better retrieval performance compared with object-based retrieval systems.

• Journal of the Korean Society of Costume
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• v.53 no.2
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• pp.35-55
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• 2003

The purpose of the study is to get some pieces of prior information to eventually develop competitive swimming suit designs with Korean traditional images. The study has been accomplished in following steps. First, as theoretical research, the history of swimming suit design and the requirements in designing competitive swimming suits were studied. Second, as practical research, at first, the trend of the competitive swimming suit designs in the national swimming suit market was examined. And then. the questionnaire surveys of both professional and amateur swimmers about their design preferences with purchasing and fabric-related tendencies were conducted for understanding professionals' characters more exactly. This data were analyzed through cross-analysis and multi-response analysis and x 2 was used. The results of this study can be summarized as follows : First, athletes' preferential design tendency for the swimming suit designs were examined in the aspects of style, color, pattern, logo, and accessary. In style, female athletes preferred an athletic one-piece style and male ones preferred a brief style. In color. neutral, mostly black was preferred most and cold color group like dark blue and navy blue next, regardless of sex. In addition, they preferred similar color coordination. In pattern, though solid fabrics were mostly preferred in both sexes, especially Taeguk motive were considered the most appropriate pattern to show Korean image. Besides, logo was considered importantly, and swimming caps and goggles of accessaries were generally used. Second, athletes' swimming suit purchasing tendency was as a following. the number of swimming suits possessed was more than 4 pieces. the durable period was less than 3 months. and the most important point considered in purchasing was an easy fitting for men and a design with an easy fitting for women. And most of swimming athletes preferred foreign products than domestic ones, which was attributed to excellent quality, easy fitting, and good design. and so on. Third, in fabric-related tendency, food touch, easy fitting. and opaqueness were considered importantly. and durability to chlorine, elasticity, color fastness, easy draining, lightness, and so on were demanded forward.

• Journal of the Korean Society of Fashion and Beauty
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• v.4 no.4 s.10
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• pp.87-99
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• 2006

This research has the purpose to examine the images sought for, makeup Consciousness, and behavioral aspects during makeup by the college girls in their 20s in the region of Daeieon and Chungnam that have strong interest in appearance and start color makeup in full scale, who form the main consumer layers in cosmetics market, and to analyze their preference on colors and feelings by the kinds of cosmetics, and their cosmetics purchase behavior. A questionnaire survey on the college girls in Daejeon and Chungnam region has shown the following results. The biggest reason college girls do the makeup was for a refined and pure image as well as protection of skin and covering defects. Their greatest concern was skin protection, and as for color selection, harmonizations of skin color and hair color were the largest consideration. In addition, the type of makeup they do most was foundation makeup, while pink was the most frequent lipstick color, and lip glow was mostly normal colors. However, they mostly answered that they do not use eye shadow, eye runner, and foundation. It was shown that their cosmetics purchase p]aces were specialized discount stores for about 47% nearly half of them, and they consider colors the most for lipsticks and eye shadows, and affinity to skin for foundations and basic cosmetics.