• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.31 no.6_2
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• pp.559-565
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• 2013

Spatial resolution of land covers from remotely sensed images can be increased using super-resolution mapping techniques for soft-classified land cover proportions. A further development of super-resolution mapping technique is downscaling the original remotely sensed image using super-resolution mapping techniques with a forward model. In this paper, the model for increasing spatial resolution of remote sensing multispectral image is tested with real SPOT 5 imagery at 10m spatial resolution for an area in Bac Giang Province, Vietnam in order to evaluate the feasibility of application of this model to the real imagery. The soft-classified land cover proportions obtained using a fuzzy c-means classification are then used as input data for a Hopfield neural network (HNN) to predict the multispectral images at sub-pixel spatial resolution. The 10m SPOT multispectral image was improved to 5m, 3,3m and 2.5m and compared with SPOT Panchromatic image at 2.5m resolution for assessment.Visually, the resulted image is compared with a SPOT 5 panchromatic image acquired at the same time with the multispectral data. The predicted image is apparently sharper than the original coarse spatial resolution image.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.2
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• pp.376-381
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• 2009

The image data compression, recognition, restoration, etc. are parts of the digital image processing technology. In the process by various devices, noises would be made. Because the noise could damage the image, we use the image filter to preserve the original image from the noise. The image filter used in digital image process basically has a two-dimensional structure. There an two methods of creating the filter - One is reiterating one dimension and the other is using an indivisible two-dimension image filter. The image filter is being widely used along with one-dimension filter according to each noise, and various median filters are being used to remove the impulse noise. In this paper, I suggested a powerful modified median filter, and compared with conventional filters for objective verification.

• Journal of Broadcast Engineering
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• v.16 no.2
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• pp.319-330
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• 2011

For objective assessment of stereoscopic 3D image quality, we measure quality of left and right image with 2D image quality measurement method. However, this method is inconvenient because that we have to measure quality of left and right image individually. Therefore we propose a method of stereoscopic 3D image quality assessment using one overlaid image with left and right image. Using this method, One can measure quality of stereoscopic 3D image more easily and quickly.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.6_2
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• pp.665-672
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• 2012

Amid rapidly increasing imagery inputs and their volume in a remote sensing imagery database, Content-Based Image Retrieval (CBIR) is an effective tool to search for an image feature or image content of interest a user wants to retrieve. It seeks to capture salient features from a 'query' image, and then to locate other instances of image region having similar features elsewhere in the image database. For a CBIR approach that uses texture as a primary feature primitive, designing a texture descriptor to better represent image contents is a key to improve CBIR results. For this purpose, an extended feature vector combining the Gabor filter and co-occurrence histogram method is suggested and evaluated for quantitywise and qualitywise retrieval performance criterion. For the better CBIR performance, assessing similarity between high dimensional feature vectors is also a challenging issue. Therefore a number of distance metrics (i.e. L1 and L2 norm) is tried to measure closeness between two feature vectors, and its impact on retrieval result is analyzed. In this paper, experimental results are presented with several CBIR samples. The current results show that 1) the overall retrieval quantity and quality is improved by combining two types of feature vectors, 2) some feature is better retrieved by a specific feature vector, and 3) retrieval result quality (i.e. ranking of retrieved image tiles) is sensitive to an adopted similarity metric when the extended feature vector is employed.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.376-381
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• 1992

This paper presents an expert system for the segmentation of a 2.5-D image. The results of two segmentation approaches, edge-based and region-based, are combined to produce a consistent and reliable segmentation. Rich information embedded in the 2.5-D image is utilized to obtain a view independent surface patch description of the image, which can facilitate object recognition considerably.

• Journal of Korean Academy of Nursing
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• v.32 no.6
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• pp.906-916
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• 2002

The purpose of this study was to identify the change and difference and relationship of postpartum depression and physical image. Method: The subjects consisted of 86 postpartum women at one general hospital in Seoul. The data was collected from September to November 2001. The instrument used for this study were SRD (Self-Rating Depression Scale) and Norris' Body Image Scale to evaluate depression and body image. The collected data was analyzed with frequency, mean, t-test, paired t-test, ANOVA and Pearson's correlation coefficient. Result: The result of this study were as follows: 1. The mean score of D2 was significantly higher than D1(p=.003). There was no difference significantly B1 and B2(p=310). 2. There was significant correlation between the two, D1-D2(r=.381, p<.01), B1-B2(r=.364, p<.01), D1-B1(r=.579, p<.01), D2-B2(r= .567, p<.01). (*D1: depression of postpartum 1-3days, D2: depression of postpartum 6-8weeks, B1: body image of postpartum 1-3days, B2: body image of postpartum 6-8weeks) Conclusion: There was very high postpartum depression in postpartum women, but body image was positive. Also, there was correlated to postpartum depression and body image. Thus it is necessary to implement nursing intervention focused on to decrease the postpartum depression and to enhance the body image of the postpartum women.

• Journal of information and communication convergence engineering
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• v.8 no.2
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• pp.185-190
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• 2010

In this paper we propose the CBIR algorithm which is based on a novel image block method that combined both color and edge feature. The main drawback of global histogram representation is dependent of the color without spatial or shape information, a new image block method that divided the image to 8 related blocks which contained more information of the image is utilized to extract image feature. Based on these 8 blocks, histogram equalization and edge detection techniques are also used for image retrieval. The experimental results show that the proposed image block method has better ability of characterizing the image contents than traditional block method and can perform the retrieval system efficiently.

• Journal of the Korean Home Economics Association
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• v.39 no.2
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• pp.73-84
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• 2001

The purposes of this study were 1) to identify the effect of clothing benefit sought on fashion image sought and 2) to determine the effects of fashion image and benefit sought on purchase intention of Gal-ot. The data were collected via a self-administered questionnaire from 172 female tourist(20 to 50 ages) in Cheju and analyzed by factor analysis, stepwise multiple regression analysis and logistic regression analysis. Four factors of benefit sought were identified : Practicality/economic-value, aesthetics, reputation, and souvenir-value. Six factors of fashion image were found and labeled as: Sexy/feminine, wild/mannish, easy/simple, Cheju image, ecology and natural image. The effects of benefits sought(Practicality/economic-value, aesthetics, reputation and souvenir-value) on fashion image(Sexy/feminine, easy/simple, Cheju and natural image) were found. There were also significant effects of benefit sought(souvenir-value) and fashion image(Cheju image) on purchase intention of Gal-ot.

• Journal of the Korea Fashion and Costume Design Association
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• v.19 no.2
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• pp.145-157
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• 2017

This study aimed to investigate the relationship between values orientation and fashion image orientation with a focus on the new senior generation. The study conducted data analysis by using the SPSS 17.0 program for the final 397 copies excluding incomplete questionnaires. The results of this study are as follows. First, values orientation was drawn as the four factors of social orientation, dependent orientation, family-like orientation, and individual orientation. The fashion image orientation was compartmentalized as three factors: urban image, individual image, and feminine image. Second, social orientation had a significant effect on feminine image as shown in Photo 1, while only individual orientation exerted a significant influence on individual image (Photo 2). Social orientation and family-like orientation respectively exercised a significant influence on individual image and feminine image, and feminine image (Photo 3). Third, the four groups did not show a significant difference in the relationship with the sub-elements of fashion image orientation. It appeared that all four groups were felt as a complex image in which modern, feminine, and individual images were mixed. Fourth, the four groups showed a significant difference in the unusual, elegant, refined, youthful, feminine, and modern images among the factors of fashion image orientation.

• Journal of the Korean Society of Clothing and Textiles
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• v.24 no.1
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• pp.24-33
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• 2000

The purpose of this study was to investigate the characteristic and image of oriental costume design on represented among three countries, Korea, China and Japan. The specific objectives were; 1) to identify the design characteristics of oriental costume. 2) to investigate the hierarchic structure of oriental costume image and the meaning structure of oriental costume image. The stimulus were 75 costume design of contemporary costume which represented the traditional image of orient. The main survey of questionary consisted of their evaluation of the oriental costume image by 26 semantic differential bi-polar scales and the subjects were 99 female students majoring in clothing and textiles. The data were analyze by Cluster analysis. Factor analysis, ANOVA, Scheffe test. The major findings were as follows; 1) As a result of design analysis, costume design of Korea, China, Japan had differences on form, color, texture, pattern, ornament, etc. 2) The hierarchic structure of oriental costume image consisted of elegance, sexy, feminine. Through factor analysis about oriental costume image 7 factors were identified; Attention, Attractiveness, Sexiness, Activeness, Weightness, Classics, Classics, Maturity. It was found out strongly that Korean costume image was simple and comfort image, Chinese costume image was sexy and feminine image, Japanese costume image was luxurious and mature image.