• Journal of the Korean Society of Clothing and Textiles
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• v.27 no.11
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• pp.1318-1329
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• 2003

The purpose of this study was to examine the effects of the structural characteristics of men's suit fabrics on the texture image and the preference, and to analyze the relationship between the preference and the practical sales ratio. In addition, the texture images and the preference of fabric and jackets made of the same fabrics were compared. As specimen, jackets for men's suit of 2002' S/S and their fabrics were collected. Questionnaires composed of 22 sensibility related and 21 fabric image related adjectives were developed. For the subjective evaluation of the texture image, both jackets and fabric samples were tested. Tests were performed with 100 female subjects in clothing department and apparel industry. For the objective evaluation, structural characteristics such as fiber contents, yarn twist, fabric count, thickness and weight were analyzed. Total Hand Value were calculated from mechanical properties determined by the KES-FB system. Factor analysis showed sensibilities were classified into 6 categories; "surface roughness", "weight", "density", "stiffness", "elasticity" and "wetness". Fabric images were classified into 4 categories; "classic", "original", "practical", and "stuffy". Depending on the method to show the specimen to the subjects, whether it is suit or fabric, statistically significant differences were observed with a number of adjectives for sensibilities and fabric images. The results of THV of KES did not agree with the preference of subjects, which suggests that we should be careful when using the KES system, which was developed for Japanese people. Price was considered to be another factor besides the texture image that influenced on purchase.

• Journal of radiological science and technology
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• v.23 no.1
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• pp.39-47
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• 2000

In this study, we showed a comparison and analysis making use of DWI(diffusion weighted image) using early diagnosis of cerebral Infarction and with the classified T2 weighted image, FLAIR images signal intensity for brain infarction period. period of cerebral infarction after the condition of a disease by ischemic stroke. To compare 3 types of image, we performed polynomial warping and affined transform for image matching. Using proposed algorithm, calculated signal intensity difference between T2WI, DWI, FLAIR and DWI. The quantification values between hand made and calculated data are almost the same. We quantified the each period and performed pseudo color mapping by comparing signal intensity each other according to previously obtained hand made data, and compared the result of this paper according to obtained quantified data to that of doctors decision. The examined mean and standard deviation for each brain infarction stage are as follows ; the means and standard deviations of signal intensity difference between DWI and T2WI for each period are $197.7{\pm}6.9$ in hyperacute, $110.2{\pm}5.4$ in acute, and $67.8{\pm}7.2$ in subacute. And the means and standard deviations of signal intensity difference between DWI and FLAIR for each period are $199.8{\pm}7.5$ in hyperacute, $115.3{\pm}8.0$ in acute, and $70.9{\pm}5.8$ in subacute. We can quantificate and decide cerebral infarction period objectively. According to this study, DWI is very exact for early diagnosis. We classified the period of infarction occurrence to analyze the region of disease and normal region in DW, T2WI, FLAIR images.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.1
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• pp.40-48
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• 2018

This paper proposes a license-plate recognition algorithm for automobile black-box image which is obtained from the camera moving with the automobile. The algorithm intends to increase the overall recognition-rate of the license-plate by increasing the Korean character recognition-rate using multi-stage neural network for automobile black-box image where there are many movements of the camera and variations of light intensity. The proposed algorithm separately recognizes the vowel and consonant of Korean characters of automobile license-plate. First, the first-stage neural network recognizes the vowels, and the recognized vowels are classified as vertical-vowels('ㅏ','ㅓ') and horizontal-vowels('ㅗ','ㅜ'). Then the consonant is classified by the second-stage neural networks for each vowel group. The simulation for automobile license-plate recognition is performed for the image obtained by a real black-box system, and the simulation results show the proposed algorithm provides the higher recognition-rate than the existing algorithms using a neural network.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.1D
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• pp.153-160
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• 2009

In relation to digital elevation model(DEM) production using high resolution satellite imagery, existing studies present that DEM accuracy differently show according to land cover property. This study therefore proposes auto-selection method of window size for correlation matching according to land cover property of IKONOS Geo-level stereo image. For this, land cover classified image is obtained by IKONOS color image with four bands. In addition, correlation-coefficients are computed at regular intervals in pixels of the window-search area to shorten of matching time. As the results, DEM by the proposed method showed more accurate than DEM using the fixed window-size matching. We estimate that accuracy of the proposed DEM improved more than DEM by digital map and ERDAS in agricultural land.

• International Journal of Automotive Technology
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• v.6 no.1
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• pp.53-63
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• 2005

We propose a fuzzy neural network (FNN) theory capable of deciding the quality of a road image prior to extracting lane-related information. The accuracy of lane-related information obtained by image processing depends on the quality of the raw images, which can be classified as good or bad according to how visible the lane marks on the images are. Enhancing the accuracy of the information by an image-processing algorithm is limited due to noise corruption which makes image processing difficult. The FNN, on the other hand, decides whether road images are good or bad with respect to the degree of noise corruption. A cumulative distribution function (CDF), a function of edge histogram, is utilized to extract input parameters from the FNN according to the fact that the shape of the CDF is deeply correlated to the road image quality. A suitability analysis shows that this deep correlation exists between the parameters and the image quality. The input pattern vector of the FNN consists of nine parameters in which eight parameters are from the CDF and one is from the intensity distribution of raw images. Experimental results showed that the proposed FNN system was quite successful. We carried out simulations with real images taken in various lighting and weather conditions, and obtained successful decision-making about $99\%$ of the time.

• Journal of the Korean Society of Costume
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• v.50
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• pp.23-32
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• 2000

This study was performed to investigate the mothers' preferences for their children's clothing images and color images. Questionaries were analysed by factor analysis cluster analysis one way ANOVA x2 -test. The results are as follow: First the preferred clothing images for children have no differences across gender. The preferred images are active tidy and fashionable. Second the preferred clothing images are according to season. In the case of clothing color images the preferences in spring and summer seasons are differed from fall and winter seasons. Third factors of boy's clothing image were fashionable cute splendid and classic And factors for girl's clothing image were lively tidy fashionable and classic. These factors revealed the differences of preferences between boys and girls clothing image. Fourth the preferences of clothing color image for children changed across seasons. Bright and neat color images were preferred in spring and summer warm and deep color images were preferred in fall and winter. Fifty the preferences of clothing images classified into four groups and each group has the different preference in color tone. Finally Season and gender were revealed to be more important variables in the preferences of children's clothing image and color image.

• Journal of the Korean Society of Clothing and Textiles
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• v.35 no.1
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• pp.51-62
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• 2011

This study provides guidelines for the development of Korean fashion cultural products. This study identified adolescents' perception of Korean traditional culture and examined their attitudes towards the fashion cultural products of the Korean image with a focus on their image association of those products. For this study, questionnaire data from 447 adolescents was used for statistical analysis. Adolescents were classified into three groups (apathy group, modernization group, and balanced succession group) according to their perception of Korean traditional culture. There were notable differences among the three groups in the image association with the fashion cultural products of Korean image and their value seeking. A large number of adolescents showed positive attitudes towards products with splendid and decorative images as well as simple and refined images. It is important to maintain a balanced strategy in developing cultural products between modernization and the succession of traditional images in order to magnity the market opportunities for fashion cultural products of the Korean image that focus on adolescents.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.5
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• pp.413-422
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• 2018

Many applications using satellite data from high-resolution multispectral sensors require an image fusion step, known as pansharpening, before processing and analyzing the multispectral images when spatial fidelity is crucial. Image fusion methods are to improve images with higher spatial and spectral resolutions by reducing spectral distortion, which occurs on image fusion processing. The image fusion methods can be classified into MRA (Multi-Resolution Analysis) and CSA (Component Substitution Analysis) approaches. To suggest the efficient image fusion method for Pleiades and KOMPSAT (Korea Multi-Purpose Satellite) 3 satellites, this study will evaluate image fusion methods for multispectral and panchromatic images. HPF (High-Pass Filtering), SFIM (Smoothing Filter-based Intensity Modulation), GS (Gram Schmidt), and GSA (Adoptive GS) were selected for MRA and CSA based image fusion methods and applied on multispectral and panchromatic images. Their performances were evaluated using visual and quality index analysis. HPF and SFIM fusion results presented low performance of spatial details. GS and GSA fusion results had enhanced spatial information closer to panchromatic images, but GS produced more spectral distortions on urban structures. This study presented that GSA was effective to improve spatial resolution of multispectral images from Pleiades 1A and KOMPSAT 3.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.1
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• pp.395-413
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• 2016

Image authentication is a technique aiming at protecting the integrity of digital images. Reversible image authentication has attracted much attention of researcher because it allows to authenticate tampered regions in the image and to reconstruct the stego image to its original version losslessly. In this paper, we propose a new, reversible image authentication scheme based on adaptive prediction error expansion (PEE) technique. In the proposed scheme, each image block is classified into smooth or complex regions. Then, according to the characteristic of each block, the authentication code is embedded adaptively to achieve high performance of tamper detection. The experimental results demonstrated that the proposed scheme achieves good quality of stego images. In addition, the proposed scheme has ability to reconstruct the stego image to its original version, if no modification is performed on it. Also demonstrated in the experimental results, the proposed scheme provides higher accuracy of tamper detection than state-of-the-art schemes.

• Fashion & Textile Research Journal
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• v.9 no.2
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• pp.197-202
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• 2007

The femme fatale image presently observable in various fields is reproducing its image through repetitive imitation, change and application, in particular, through 'movies' which have a greater ripple effect on the public than any other mass media by incessantly producing a countless number of images. This study aims to figure out the intrinsic meaning and the characteristics of the image of femme fatale, understand the modern expression of it in movies and finally shed light on its image represented in Korean movies. For this study, the literature and internet materials related to the image of femme fatale in the movie "Sympathy for Lady Vengeance" and the general concept of femme fatale were comprehensively surveyed. The femme fatale image which is represented in this movie is classified into 4 images ; disguise & mystery, retribution & cruelty, enchantment & beauty, salvation & redemption. The findings of this study provide an insight into how the femme fatale image is expressed in movies, the mass media which has a gigantic ripple effect, and provide the momentum to recognize the need and significance of understanding the femme fatale image represented in Korean movies.