• Journal of IKEEE
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• v.27 no.3
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• pp.280-287
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• 2023

Deep learning advancements can solve computer vision problems, but large-scale datasets are necessary for high accuracy. In this paper, we propose an image generation technique using object bounding boxes and image edge components. The object bounding boxes are extracted from the images through object detection, and image edge components are used as input values for the image generation model to create new image data. As results of experiments, the images generated by the proposed method demonstrated similar image quality to the source images in the image quality assessment, and also exhibited good performance during the deep learning training process.

• The Journal of the Korea Contents Association
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• v.14 no.12
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• pp.785-795
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• 2014

The purpose of this study was to develop and validate of Smoker Image Scale and to evaluate the effect of the smoker image on adulthood smoking intention of youth. Data were collected from 610 high school students were analysed using SPSS 21.0 and AMOS 21.0 programs. Smoker Image Scale were developed and verified the reliability and validity. In addition, ordinal logistic regression analysis was implemented for impact of smoker image on adulthood smoking intention. As a results of analysis, first, the developed Smoker Image Scale confirmed with 10 items in 1 factor and Cronbach's ${\alpha}$ was .91. Second, men and smokers had significantly higher positive smoker image formed by cigarette advertising. Third, positive smoker image had a significant positive effect on adulthood smoking intention while controlling of gender and smoking status. Positive smoker image formed by cigarette advertising was associated with adulthood smoking intention of youth. Based on these findings, implications and suggestions for future research were discussed for the risk of adulthood smoking intention of youth.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.44 no.1
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• pp.125-132
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• 2024

Optical satellite images are being used for national security and collection of information, and their utilization is increasing. However, it acquires low-quality images that are not suitable for the user's requirement due to weather conditions and time constraints. In this paper, a deep learning-based conversion of image and colorization model referring to high-resolution SAR images was created to simulate the occluded area with clouds of optical satellite images. The model was experimented according to the type of algorithm applied and input data, and each simulated images was compared and analyzed. In particular, the amount of pixel value information between the input black-and-white image and the SAR image was similarly constructed to overcome the problem caused by the relatively lack of color information. As a result of the experiment, the histogram distribution of the simulated image learned with the Gray-scale image and the high-resolution SAR image was relatively similar to the original image. In addition, the RMSE value was about 6.9827 and the PSNR value was about 31.3960 calculated for quantitative analysis.

• Science of Emotion and Sensibility
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• v.12 no.1
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• pp.1-10
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• 2009

The purpose of this study is to find out the relationship between the design factor and the sensitivity in web site. The classification of sensitivity-types consists of the research of books and the survey, and the language specialist's review and the analysis of factor. The research of the Image Scale accomplished through the analysis of the result of sensitivity-types. The major findings of the analysis are summarized as follows. The webpage sensitivity-types are classified into the 7 types, namely 'refreshment', 'calm', 'refinement', 'strongness', 'youth', 'uniqueness', 'futurity'. As a result of analyzing of similarity between the adjectives by multiple standards, the web site Image Scale space consists of the axis between 'heavy-light' and 'soft-hard'. As a result of the research of relationship between the web site design factor and the emotion, the color and the layout influenced into 'soft-hard' much, and the light and the color influenced into 'heavy-light' much.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.9 no.2
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• pp.129-135
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• 2015

The objective grading system for the facial palsy is needed. In this study, the facial palsy grading system was developed with combination of three dimensional image processing and Nottingham scale. The developed system is composed of 4 parts; measurement part, image processing part, computational part, facial palsy evaluation & display part. Two web cam were used to get images. The 8 marker on face were recognized at image processing part. The absolute three dimensional positions of markers were calculated at computational part. Finally, Nottingham scale was calculated and displayed at facial palsy evaluation & display part. The effects of measurement method and position of subject on Nottingham scale were tested. The markers were measured with 2-dimension and 3-dimension. The subject was look at the camera with $0^{\circ}$ and $11^{\circ}$ rotation. The change of Scale was large in the case of $11^{\circ}$ rotation with 2-dimension measurement. So, the developed system with 3-dimension measurement is robust to the orientation change of subject. The developed system showed the robustness of grading error originated from subject posture.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.29 no.5
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• pp.449-457
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• 2011

As automated image processing techniques have been required in multi-temporal/multi-sensor geospatial image applications, use of automated but highly invariant image matching technique has been a critical ingredient. Note that there is high possibility of geometric and spectral differences between multi-temporal/multi-sensor geospatial images due to differences in sensor, acquisition geometry, season, and weather, etc. Among many image matching techniques, the SIFT (Scale Invariant Feature Transform) is a popular method since it has been recognized to be very robust to diverse imaging conditions. Therefore, the SIFT has high potential for the geospatial image processing. This paper presents a performance test results of the SIFT on geospatial imagery by simulating various image differences such as shear, scale, rotation, intensity, noise, and spectral differences. Since a geospatial image application often requires a number of good matching points over the images, the number of matching points was analyzed with its matching positional accuracy. The test results show that the SIFT is highly invariant but could not overcome significant image differences. In addition, it guarantees no outlier-free matching such that it is highly recommended to use outlier removal techniques such as RANSAC (RANdom SAmple Consensus).

• Asian Oncology Nursing
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• v.11 no.3
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• pp.221-228
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• 2011

Purpose: This study was aimed to identify the influencing factors on the quality of life among breast cancer survivors. Methods: The subjects were 159 female patients who visited out-patient department (OPD) after the mass removal surgery for breast cancer and had completed adjuvant treatments such as chemotherapy, radiation therapy at a university hospital and a general hospital. Data collection was conducted using the Ferrell QOL scale, the Mishel uncertainty scale, the Fitts & Osgoods body image scale revised by Jeon & Kim. the Rosenberg self-esteem scale, and the Kang family support scale. Results: The level of QOL in the participants was in the middle. There were a significant correlation between QOL, uncertainty, self-esteem, and family support. There were significant differences in QOL with the perceived health condition and the best support person. In a regression analysis, the most powerful predictor of QOL was body image (21.7%). Altogether uncertainty and perceived health condition explained 28.6% of the variance of QOL of the participants. Conclusion: Body image, uncertainty, and perceived health condition were important predictors of QOL. These results demonstrated the need for developing interventions to improve QOL of breast cancer survivors.

• Journal of the Korean Academy of Clinical Electrophysiology
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• v.8 no.2
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• pp.39-43
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• 2010

Purpose : The purpose of this study was to analyze skin reactions induced by ultraviolet irradiation using digital imagery. Methods : We recruited 15 women and ultraviolet irradiation was applied to their lumbar area. (The degree of inflammatory reaction was set on the basis of the third erythema dose. Image analysis was divided by Photoshop CS (8 bit RGB scale and gray scale). Then, images were processes using Image Pro Plus 4.5 program analyzing R, G, B, chromatic red value, luminance value and gray value. Results : As a result of analyzing changes in RGB scale, there were statistically significant differences in R, G, and chromatic red values. As a result of analyzing changes in gray scale, there were statistically significant differences in gray value. Analysis of changes in B and luminance values showed that there was no statistically significant difference. Conclusion : This study found that ultraviolet irradiation had influence on RGB and gray scale. These results suggest that changes to digital images on skin reaction by ultraviolet irradiation are related to erythema. In particular, these changes are related to R and gray values.

• Journal of the Institute of Convergence Signal Processing
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• v.2 no.1
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• pp.53-62
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• 2001

In this paper, the hybrid function by local scale control is proposed to detect the optimal edges from blurred images. In the case of image capturing, some blurring is occurred by the characteristics of the illumination and the reflected light. During processing the blurred image, it is difficult to detect perfect edges. This algorithm proposed a new hybrid function which is merged Gaussian function and the second derivative of Gaussian function. And it detects the optimal edges applying directional edge detection by Canny algorithm as the scale factor of $\sigma$ in the given local mask has been changed after convolving the hybrid function for input image. In the result, the performance is confirmed that this algorithm is better than Sobel, Robert and Canny edge detector by analyzing the some test images. And the results is obtained 0.2 ㏈ ~ 14 ㏈ of PSNR than those conventional method.

• Journal of the Institute of Convergence Signal Processing
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• v.12 no.3
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• pp.169-175
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• 2011

In this paper, an automatic scoring system of the OMR answer sheet is implemented using Gray Scale and image segmentation method. The proposed method was used to extract the OMR data on multiple-choice answer sheet from captured image. In addition, On-line scoring system is developed and implemented to mark the short-answer type on the reverse side. Therefore, teachers can mark the short-answer type for anytime and anywhere within the available time. There were many advantages to mark of the multiple-choice answer sheet without additional OMR reader. In the future, the grading of short-answer type will be more efficient if it were performed by using an automatic scoring system based on image processing.