• Journal of the Korean Society of Fashion and Beauty
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• v.2 no.3 s.3
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• pp.44-59
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• 2004

The purpose of this study was to find out proper evaluative words according to fashion image and to identify the correlation between clothing style and hair style related to fashion image. The questionnaire was used to collect data. 326 female aged between 23 to 40 were selected for the subjects of this study. The data were analyzed by frequency, factor analysis, pearsons correlation. The results of this study were as follows. 1. Evaluative words for each fashion image were selected by factor analysis. modern image intellectual, cold, urbane, simple, straight. elegance image : graceful, dignified, refined, decorous, luxurious. romantic image : cute, lovely, girlish, feminine, romantic. natural image : natural, comfortable, gentle, intimate, soft. casual image : energetic, active, free, cheerful, vivid. avant-garde image : experimental, strange, creative, avant-garde, irregular. 2. Correlation between clothing style image and hair style image ; clothing style and hair style was positively correlated. with the same image in case of modern, romantic, casual, elegance and avantgarde but natural image of clothing style was correlated with the natural, elegance, romantic, modern image of hair style. 3. The most suitable hair style for the clothing style according to fashion image : The clothing style of a particular image was matched best with the hair style of the same image.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2007.04a
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• pp.187-190
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• 2007

This study is for analyzing best band in image matching using correlation coefficient of left and right images of stereo image pair, lot red, green, blue band images separated from color aerial photo and gray image converted from the same color aerial photo image. The image matching is applied to construct Digital Elevation Model(DEM) or terrain data. The correlation coefficients and variation by change of pixel patch size are computed from pixel patches of which sizes are $11{\times}11{\sim}101{\times}101$. Consequently, the correlation coefficient in red band image is highest. The lowest is in blue band. Therefore, to construct terrain data using image matching, the red band image is preferable. As the size of pixel patch is growing, the correlation coefficient is increasing. But increasing rate declines from $51{\times}51$ image patch size and above. It is proved that the smaller pixel patch size than $51{\times}51$ is applied to construct terrain data using image matching.

• Journal of information and communication convergence engineering
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• v.9 no.6
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• pp.747-752
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• 2011

The position detection of overlapping area in the interframe for image stitching using auto and cross correlation function (ACCF) and compounding one image with the stitching algorithm is presented in this paper. ACCF is used by autocorrelation to the featured area to extract the filter mask in the reference (previous) image and the comparing (current) image is used by crosscorrelation. The stitching is detected by the position of high correlation, and aligns and stitches the image in shifting the current image based on the moving vector. The ACCF technique results in a few computations and simplicity because the filter mask is given by the featuring block, and the position is enabled to detect a bit movement. Input image captured from CMOS is used to be compared with the performance between the ACCF and the window correlation. The results of ACCF show that there is no seam and distortion at the joint parts in the stitched image, and the detection performance of the moving vector is improved to 12% in comparison with the window correlation method.

• Journal of information and communication convergence engineering
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• v.8 no.4
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• pp.349-354
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• 2010

Moving pixel displacement detection algorithm using correlation functions for making panorama image on the continuous images is presented in this paper. The input images get from a CMOS image sensor (CIS). The camera is maintained by constant brightness and uniform sensing area in test input pattern. For simple navigation and capture image has to 70% overlapped region. A correlation rate in two image data is evaluated by using reference image with first captures, and compare image with next captures. The displacement of the two images are expressed to second order function of x, y and solved with finding the coefficient in second order function. That results in the change in the peak correlation displacement from the reference to the compare image, is moving to pixel length. The navigating error is reduced by varying the path because the error is shown in the difference of the positioning vector between the true pixel position and the navigated pixel position. The algorithm performance is evaluated to be different from the error vector to vary the navigating path grid.

• Journal of the Korean Society of Clothing and Textiles
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• v.24 no.7
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• pp.1088-1099
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• 2000

The purpose of this study was to investigate the effect on self-esteem and emotion of an improved self-appearance image among the female psychiatric patients, and the therapeutic effect of fashion therapy. The treatment intervention was provided for 37 psychiatric patients and the data of 17 participants was analyzed. The results were as follows: 1. The actual self-appearance image improved overall and all factors. Their expectation for the‘attractive’image was heightened. Their self-esteem was improved and negative emotions were reduced overall and depression. 2. The changes of the actual self-appearance had a positive correlation with self-esteem. and a negative correlation with negative emotion overall, especially anxiety, depression. Improvement of ‘attractive’image had the most correlation. 3. The changes of the ideal self-appearance image didn't have the correlation with self-esteem, but negative correlation with emotions overall and anxiety, depression and hostility. 4. The change in the incongruity of their ideal and actual self-appearance image overall had a negative correlation with the change of self-esteem and positive correlation with negative emotion, especially depression and hostility.

• Journal of the East Asian Society of Dietary Life
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• v.4 no.1
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• pp.37-47
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• 1994

A survey on images and consumption for Instant food for 450 homemakers in Ullungdo, Hansando and Daegu area were summarized as follows. 1) The tought of Homemakers food took 'easy to cook' and 'save time' as the best advantage in the image on instant food, while 'tasty' as the lowest one. It appeared that characteristic variables as household income, homemaker's education, homemaker's age, and area had influence on the image about instant food. 2) Processed food(ham, sausage)was purchased the most, while fermented food(kimchi, gochuchang) was purchased the least. It appeared that characteristics variables as household income, homemaker's education and homemaker's age had influence on the purchasing degree of instant food. 3) There were positive correlation coefficient between homemaker's image on instant food and household income(0.247) and area(0.211). There were negative correlation coefficient between homemaker's image on instant food and homemaker's age(-0.171). 4) Homemaker's purchasing degree about instant food had positive correlation coefficient with homemaker's image on instant food(0.389), household income(0.247) and area(0.211)and had negative correlation coefficient with homemaker's age(-0.190). 5) Fat intake had positive correlation coefficient with homemaker's purchasing degree(0.281) and homemaker's image(0.144) on instant food. Energy intake had positive correlation coefficient with homemaker's purchasing degree(0.206) and homemaker's image(0.138) on instant food.

• Journal of Environmental Science International
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• v.24 no.4
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• pp.403-414
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• 2015

This study is daytime and nighttime runoff image data caused by heavy rain on May 27, 2013 at Oedo Water Treatment Plant of Oedo-Stream, Jeju to compute runoff by applying Surface image velocimeter (SIV) and analyzing correlation according to current. At the same time, current was comparatively analyzed using ADCP observation data and fixed electromagnetic surface current meter (Kalesto) observed at the runoff site. As a result of comparison on resolutions of daytime and nighttime runoff images collected, correlation coefficient corresponding to the range of 0.6~0.7 was 6.8% higher for nighttime runoff image compared to daytime runoff image. On the contrary, correlation coefficient corresponding to the range of 0.9~1.0 was 17% lower. This result implies that nighttime runoff image has lower image quality than daytime runoff image. In the process of computing current using SIV, a rational filtering process for correlation coefficient is needed according to images obtained.

• The Korean Journal of Rehabilitation Nursing
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• v.9 no.1
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• pp.34-41
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• 2006

Purpose: This study was to analyze the relationship the physical disability, cognitive disorder and body image. Method: The research was a descriptive relationship study. A sample is composed of 101 hospitalized stroke patients. Data were collected from November, 2005 to December, 2005. The survey instruments used in the study Sharon and Glen's physical disability scale, Lim's cognitive disorder scale and Osgood's body image scale. The collected data were analyzed frequency, percentage, mean, standard deviation, ANOVA, Duncan test, Pearsons' correlation coefficients. Result: The level of physical disability the score was 2.26, cognitive disorder 1.84 and body image 3.54. and they were relation to significant correlation. The body image showed significant negative correlation with physical disability, cognitive disorder. Physical disability showed significant positive correlation with cognitive disorder(r=.639, p=.000), and significant negative correlation with body image(r=-.420, p=.000). Cognitive disorder showed significant negative correlation with body image(r=-.620, p=.000). There were significant differences of body image by general characteristics as follows: age(p=.000), occupation(p=.004), education(p=.008), disease(p=.007). monthly income(p=.006), burden of medical expenses(p=.001), duration of stroke(p=.008). Conclusion: There was a significant correlation between physical disability, cognitive disorder and body image. there will be considered useful nursing intervention effect to physical disability, cognitive disorder and body image of stroke patients.

• Journal of Animal Environmental Science
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• v.7 no.3
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• pp.177-182
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• 2001

This study was conducted to find out the coefficient relationships between intensity values image processing and pollution density of slurries. Slurry images were obtained from the image processing system using personnel computer and CCD-camera. Software, written in Visual $c^{++}$, combined the functions of the image capture, image processing and image analysis. The data of image processing for slurries were analyzed by the method of regression analysis. The results are as follows. 1. Red(R)-values among image processing data were obtained the highest correlation coefficient 0.9213 for detecting COD. Also, green(G)-value were obtained the highest correlation coefficient 0.9019 fur detecting BOD. Blue(B)-value could not find significant values to detect the pollution resources density. 2. Hue(H)-values among image processing data were obtained the highest correlation coefficient 0.9466 for detecting BOD. This fact could be used in detecting BOD 3. Green(G)-value, GRAY-value, Hue(H)-value, Saturation(5)-value and Intensity(I)-value were the correlation coefficient more than 0.8 for BOD. Hue(H)-value was higher correlation coefficient than any other value. It was possible to detect pollution density of slurries by using the image processing system. 4. Red(R)-value, GRAY-value and Saturation(5)-value were obtained the correlation coefficient more than 0.8 for detecting COD. a-value had the highest correlation coefficient Among these values. It was possible to detect density indirectly by using the image processing system. 5. SS-density were obtained the correlation coefficient less than 0.8 by using the image processing system. The density of $NH_4$-N and $NO_3$-N were obtained correlation coefficient less than 0.2.

• Journal of Biosystems Engineering
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• v.28 no.4
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• pp.343-350
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• 2003

This study was conducted to find out the coefficient relationships between intensity values of image processing and biological/physical parameters of soil in greenhouses. Soil images were obtained by an image processing system consisting of a personal computer and a CCD earners. A software written in Visual C$\^$++/ systematically integrated the functions of image capture, image processing, and image analysis. Image processing data of the soil samples were analyzed by the method of regression analysis. The results are as follows. For detecting soil density of unbroken soil samples, the highest correlation coefficients of 0.82 and 0.84, respectively were obtained fur R-value and S-value among image processing data while it was 0.97 for G-value. Considering the relationship between biological characteristics and image processing data of soil in greenhouse, the correlation was found generally low. For pH of unbroken soil sample, the correlation coefficients were found 0.87, 0.85, and 0.94, respectively with G, I, and H values of image processing data. In the case of bacteria, any correlation was not found with the image processing data For Actinomyctes, they were 0.86 and 0.85, respectively with G-value and B-value of image processing data showing high correlation coefficient compared to the other variables. The correlation coefficient between Fungi and H-value was shown 0.88, the highest among the variables higher than 0.8 while the other variables showed low correlation. For broken soil samples from greenhouse, the relation between biological parameter and image processing data were rarely shown in this study. The results of this study indicated that most of correlation coefficient between the variables were usually lower than 0.01. Accordingly, it was assumed that the soil should be used without broken to fairly estimate biological characteristics using CCD camera.