• Journal of the Korea Fashion and Costume Design Association
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• v.10 no.1
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• pp.135-144
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• 2008

The reason that we are familiar with fashion from the 1950s is because of the work such as New Look done by a french fashion designer, Christian Dior who had taken on an almost mythical significance by his name. Moreover, in the sense of popularity, the appearance of Marilyn Monroe and Audrey Hepburn, two typical Hollywood actresses who each has directly-opposed image, is the symbol of youthful America of the 1950s and represents the remarkable start of the American fashion. Still, these days designers and mass medias recall the fashion from the 50s remaking and parodying it to suit public's taste. Being due to the World War II, Europe suffered not only the loss of its national tradition and reputation but also got a fatal blow politically and economically. On the other hand, the United States of America occupied a primary position in the world and outstandingly became the most powerful country. The American fashion of the 1950s represents youth and newness and rejects outdated and outmoded style. In this period, appears the indication which announces previously the youth culture. Poodle skirt is the fashion item that acquired popularity among young american women and girls in the late 1950s. In effect, it is the fashion as American as apple pie. A costly A-line skirt had been transformed into a cheap felt skirt. Instead of a real poodle dog which was carried by French women like an accessory, they embroidered a poodle dog on the lower edge of their skirt. As deriding the snobbish gait, they swayed themselves frantically to the rhythm of Rock n' Roll which swept those days. This was an attitude of young Americans against the existing trend of Europe. Poodle skirt showed the free spirit and intention of young people unbound to custom and established vogue. In addition, in the aspect of comprising the American spirit of independent, pioneer, and subjective American people, it goes beyond the bounds of common concept of fad. Poodle skirt is an unique symbol of the 1950s' American fashion which prognosticates the advent of the United States and the success in modern fashion world which was changing after 1950s.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.12B
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• pp.2369-2381
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• 1999

In this paper, we propose an iterative algorithm for reducing the blocking artifact in block transform-coded images by using a wavelet transform. In the proposed method, an image is considered as a set of one-dimensional horizontal and vertical signals and one-dimensional wavelet transform is utilized in which the mother wavelet is the first order derivative of a Gaussian like function. The blocking artifact is reduced by removing the blocking component, that causes the variance at the block boundary position in the first scale wavelet domain to be abnormally higher than those at the other positions, using a minimum mean square error (MMSE) filter in the wavelet domain. This filter minimizes the MSE between the ideal blocking component-free signal and the restored signal in the neighborhood of block boundaries in the wavelet domain. It also uses local variance in the wavelet domain for pixel adaptive processing. The filtering and the projection onto a convex set of quantization constraint are iteratively performed in alternating fashion. Experimental results show that the proposed method yields not only a PSNR improvement of about 0.56-1.07 dB, but also subjective quality nearly free of the blocking artifact and edge blur.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.6
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• pp.285-294
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• 2004

Median Filters in the Signal Processing have been most widely used and have demonstrated the most strongest effects. This paper proposes the Adaptive Median Filters by using noise detection. The basic algorithm of the proposed filters is to determine whether noise or not by the each noise judgement standards, and then take the Median Filter if it satisfies the conditions as a result of judgement and returns to the original image(No Filters) if not. This paper presented Noise Detection by Local Variance and Local Central Variance for noise judgement, compared and analyzed the features and performance of existing [5]∼[10] Filters. Filter improved on the result of executing the existing filters at the same condition and showed the effects over that when it was judged with naked eyes. Accordingly, the Adaptive Median Filters by Local Variance and Local Central Variance was proven to have reinforced edge preservation ability and have the strong features for removing the Impulse Noise of the Median Filter.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.367-370
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• 2015

This paper proposes an improve method of the detection performance of traffic lights for autonomous driving cars. Earlier detection methods used to adopt color thresholding, template matching and based learning maching methods, but its have some problems such as recognition rate decreasing, slow processing time. The proposed method uses both detection mask and morphological preprocessing. Firstly, input color images are converted to YCbCr image in order to strengthen its illumination, and horizontal edge components are extracted in the Y Channel. Secondly, the region of interest is detected according to morphological characteristics of the traffic lights. Finally, the traffic signal is detected based on color distributions. The proposed method showed that the detection rate and processing time improved rather than the conventional algorithm about some surrounding environments.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.4
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• pp.381-390
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• 2010

This paper describes a procedure of the map-based localization for mobile robots by using a sensor fusion technique in structured environments. A combination of various sensors with different characteristics and limited sensibility has advantages in view of complementariness and cooperation to obtain better information on the environment. In this paper, for robust self-localization of a mobile robot with a monocular camera and a laser structured light sensor, environment information acquired from two sensors is combined and fused by a Bayesian sensor fusion technique based on the probabilistic reliability function of each sensor predefined through experiments. For the self-localization using the monocular vision, the robot utilizes image features consisting of vertical edge lines from input camera images, and they are used as natural landmark points in self-localization process. However, in case of using the laser structured light sensor, it utilizes geometrical features composed of corners and planes as natural landmark shapes during this process, which are extracted from range data at a constant height from the navigation floor. Although only each feature group of them is sometimes useful to localize mobile robots, all features from the two sensors are simultaneously used and fused in term of information for reliable localization under various environment conditions. To verify the advantage of using multi-sensor fusion, a series of experiments are performed, and experimental results are discussed in detail.

• Journal of the Korean Society of Costume
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• v.66 no.4
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• pp.128-145
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• 2016

Unlike the past, when fashion brands adopted unilateral communication with their consumers, the brands today have recognized the importance of bi-lateral communication. This has led to the companies producing fashion films as a means to elicit a consensus in opinion between the brands and the consumers. Such fashion films should be understood as films using fashion that transcends time, and also as a type of fashion media. This study, which is based upon the understanding that fashion films are a part of strategic marketing for enhancing the value of brands, used domestic and international literature in order to define fashion films, and establish a theoretical basis for these films. Corroborative study was also conducted for the purpose of practical categorization. This study aims to investigate the characteristics of fashion films, and to suggest a new approach to the study of fashion films. The study adopted the research methodology used in Dudley Andrew's film theory in order to create a theoretical frame that can be used to categorize fashion films. The theory is of significance because it is the basis for the category of motion picture fashion film and media technology fashion film. The study on the categorization and the characteristics of fashion films based upon 6 sub-categories shows a consistent trend of fashion films. From the results, it can be inferred that the films contribute, in part, to the enhancement of brand value. Fashion films have shown rapid growth with the mixture of other media, and with the introduction of cutting-edge technology. Fashion films can be used as new marketing methods for the fashion brands in this digital age.

• Journal of Korean Society for Geospatial Information Science
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• v.13 no.3 s.33
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• pp.87-94
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• 2005

3D positional information of lane can be automatically calculated tv combining GPS data, IMU data if coordinates of lane centers are given. The Road Safety Survey and Analysis Vehicle(RoSSAV) is currently under development to analyze three dimensional safety and stability of roads. RoSSAV has GPS and IMU sensors to get positional information of the vehicle and two road-facing CCD cameras for extraction of lane coordinates. In this paper, we develop technology that automatically detects centers of lanes from the road-facing cameras of RoSSAV. The proposed algorithm defines line-support regions by grouping pixels with similar edge orientation and magnitude together and extracts a line from each line support region by planar fitting. Then if extracted lines and the region in-between satisfy the criteria of brightness and width, we decide this region as lane. The proposed algorithm was more precise and stable than the previously proposed algorithm based on brightness threshold method. Experiments with real road scenes confirmed that lane was effectively extracted by the proposed algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.8
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• pp.3312-3327
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• 2020

Plant diseases are a significant yield and quality constraint for farmers around the world due to their severe impact on agricultural productivity. Such losses can have a substantial impact on the economy which causes a reduction in farmer's income and higher prices for consumers. Further, it may also result in a severe shortage of food ensuing violent hunger and starvation, especially, in less-developed countries where access to disease prevention methods is limited. This research presents an investigation of Directional Local Quinary Patterns (DLQP) as a feature descriptor for plants leaf disease detection and Support Vector Machine (SVM) as a classifier. The DLQP as a feature descriptor is specifically the first time being used for disease detection in horticulture. DLQP provides directional edge information attending the reference pixel with its neighboring pixel value by involving computation of their grey-level difference based on quinary value (-2, -1, 0, 1, 2) in 0°, 45°, 90°, and 135° directions of selected window of plant leaf image. To assess the robustness of DLQP as a texture descriptor we used a research-oriented Plant Village dataset of Tomato plant (3,900 leaf images) comprising of 6 diseased classes, Potato plant (1,526 leaf images) and Apple plant (2,600 leaf images) comprising of 3 diseased classes. The accuracies of 95.6%, 96.2% and 97.8% for the above-mentioned crops, respectively, were achieved which are higher in comparison with classification on the same dataset using other standard feature descriptors like Local Binary Pattern (LBP) and Local Ternary Patterns (LTP). Further, the effectiveness of the proposed method is proven by comparing it with existing algorithms for plant disease phenotyping.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.40 no.5
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• pp.303-311
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• 2003

Since the MPEG-4 visual standard enables content-based functionalities, it is necessary to extract video object from natural video sequences. Segmentation algorithms can largely be classified into automatic segmentation and user-assisted segmentation. In this paper, we propose a user-assisted VOP generation method based on the geometric active contour. Since the geometric active contour, unlike the parametric active contour, employs the level set method to evolve the curve, we can draw the initial curve independent of the shape of the object. In order to generate the edge function from a smoothed image, we propose a vector-valued diffusion process in the LUV color space. We also present a discrete 3-D diffusion model for easy implementation. By combining the curve shrinkage in the vector field space with the curve expansion in the empty vector space, we can make accurate extraction of visual objects from video sequences.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.9
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• pp.137-142
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• 2016

When injecting intravenously of CT inspection, the effusion of the contrast meium can induce the tissue damage with the blood vessel outside. We detect extravasation which is generated in the course where we inject the contrast medium into the blood vessel. And we use the bolus tracking system for the detection of that. By using MPR and VR images, moreover we detected the extravasation in order to prevent the tissue damage. In order to detect the effusion of the contrast medium, we used 16-MDCT and 64-MDCT. Three dimensional images about the outflow of the blood vessel can provide the treatment information which is important in the patient treatment. Moreover we applied the image processing technique in order to improve sharpness between contrast media and organization. And sharpness and contrast was improved.