• Journal of Physiology & Pathology in Korean Medicine
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• v.22 no.3
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• pp.528-534
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• 2008

It has been known that Tri-origin theory could describe pertinently the dynamic phenomena of life. From the viewpoint of the asian image-mathematics, the most representative Tri-origin could be Four Images, Five Phases, and Six Qi(six kinds of weather). In Korean traditional medicine, Tri-origin could be meridian system, Jangbu viscera system, and body essence vital energy mentality blood system. Here we reasoned whether asian image-mathematics could be applicable to Korean traditional medicine system, and as a conclusion ; Meridian system belongs to Six Qi, Jangbu viscera system belongs to Five Phases, and body essence vital energy mentality blood system belongs to Four Images.

• Journal of Families and Better Life
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• v.20 no.2
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• pp.185-191
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• 2002

The Purposes of this study were to improve the understanding of how the Korean traditional fairy tales were recognized, by examining the recognition of parent and teacher toward the traditional fairy tales, and to serve as the basis for teacher and parent to guide children appropriately, by developing a desirable teaching activity, using the Korean traditional fairy tales. The subject in this study were 238 parents, and 77 kindergarten teachers in Seoul, Sunchon, Chonan, Ichon and Ulsan city. And the questionnaire was used. The collected data were handled by frequency, percentage and t-test. The findings of this study were as below: These Parents and teachers thought the Korean traditional fairy tales are appropriate because of moral, ethical values, and knowledge. On the older hand, they thought these are inappropriate because of unrealistic things or image.

• Journal of Korean Society of Rural Planning
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• v.16 no.3
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• pp.1-10
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• 2010

The purpose of this study is to find out the color preference on rural rooftop color. Today, public profit value of a rural community has been heavily recognized in the areas of preservation of pro-environmental and traditional life styles and foundation of collective community. Comparatively with urban, rural town conserves the scenic of those days when the historic landscape existed. Therefore, elements of historic and tradition in rural town are interesting resources to people who want traditional experience. Color is one of the most influenced elements for the image of Landscape. On the other hand, radical modernization has brought conflicting color element that does not blend with existing environmental color. Among others, roof represents one of the important traits of rapidly developing rural community due to vast amount of space it covers. In order to come up with more appropriate coloring scheme, it is necessary determine color that forms a balance with present conditions of rural life and historic landscape. This study provides more objective rooftop coloring selection process by employing additional surveys regarding color image adjective. I justified necessity of the balance between environmental color and roof color through analyzing correlation between environmental color of the rural town and Color Image Scale of the preliminary selection of roofs.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.8
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• pp.1843-1859
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• 2013

The continuous increase of the spatial resolution of remote sensing images brings great challenge to image analysis and processing. Traditional prior knowledge-based region detection and target recognition algorithms for processing high resolution remote sensing images generally employ a global searching solution, which results in prohibitive computational complexity. In this paper, a more efficient region of interest (ROI) detection algorithm based on visual attention and threshold segmentation (VA-TS) is proposed, wherein a visual attention mechanism is used to eliminate image segmentation and feature detection to the entire image. The input image is subsampled to decrease the amount of data and the discrete moment transform (DMT) feature is extracted to provide a finer description of the edges. The feature maps are combined with weights according to the amount of the "strong points" and the "salient points". A threshold segmentation strategy is employed to obtain more accurate region of interest shape information with the very low computational complexity. Experimental statistics have shown that the proposed algorithm is computational efficient and provide more visually accurate detection results. The calculation time is only about 0.7% of the traditional Itti's model.

• KIEAE Journal
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• v.11 no.2
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• pp.9-15
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• 2011

Many Korean palaces such as Deoksu Palace and Kyungbok Palace are located in downtown Seoul. Modern high-rise buildings around the palace have been the background scenery of traditional architecture in it. In this case, such landscapes mixed with traditional images and contemporary images can give a negative impression to visitors watching from inside the palace. In this study, we analysed the correlation between landscape image of Deoksu Palace and trees' view blockage of buildings around it with three independent variables. The first variable is completely blocked view of buildings around the palace by the trees. The second variable is half-blocked view of buildings around the palace by the trees. The third variable is the view of buildings around the palace that is not blocked by the trees. The analysis showed that there were some significant correlations between landscape image of Deoksu Palace and trees' view blockage of buildings around it. It also showed that the view blockage ratio by the trees has positive correlation with improvement of landscape image of the palace.

• Journal of Electrical Engineering and Technology
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• v.13 no.5
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• pp.2099-2106
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• 2018

This study presents a novel approach of discriminative feature vectors based on manifold learning using nonlinear dimension reduction (DR) technique to improve loss function, and combine with the Adversarial examples to regularize the object function for image classification. The traditional convolutional neural networks (CNN) with many new regularization approach has been successfully used for image classification tasks, and it achieved good results, hence it costs a lot of Calculated spacing and timing. Significantly, distrinct from traditional CNN, we discriminate the feature vectors for objects without empirically-tuned parameter, these Discriminative features intend to remain the lower-dimensional relationship corresponding high-dimension manifold after projecting the image feature vectors from high-dimension to lower-dimension, and we optimize the constrains of the preserving local features based on manifold, which narrow the mapped feature information from the same class and push different class away. Using Adversarial examples, improved loss function with additional regularization term intends to boost the Robustness and generalization of neural network. experimental results indicate that the approach based on discriminative feature of manifold learning is not only valid, but also more efficient in image classification tasks. Furthermore, the proposed approach achieves competitive classification performances for three benchmark datasets : MNIST, CIFAR-10, SVHN.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.5
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• pp.1597-1610
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• 2022

At present, the main method of high-speed train chassis detection is using computer vision technology to extract keypoints from two related chassis images firstly, then matching these keypoints to find the pixel-level correspondence between these two images, finally, detection and other steps are performed. The quality and accuracy of image matching are very important for subsequent defect detection. Current traditional matching methods are difficult to meet the actual requirements for the generalization of complex scenes such as weather, illumination, and seasonal changes. Therefore, it is of great significance to study the high-speed train image matching method based on deep learning. This paper establishes a high-speed train chassis image matching dataset, including random perspective changes and optical distortion, to simulate the changes in the actual working environment of the high-speed rail system as much as possible. This work designs a convolutional neural network to intensively extract keypoints, so as to alleviate the problems of current methods. With multi-level features, on the one hand, the network restores low-level details, thereby improving the localization accuracy of keypoints, on the other hand, the network can generate robust keypoint descriptors. Detailed experiments show the huge improvement of the proposed network over traditional methods.

• The International Journal of Costume Culture
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• v.2 no.2
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• pp.60-70
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• 1999

The purposes of this study were to investigate preference and images of Korean traditional motifs, and to identify the relationship between them. The subjects consisted of 369 male and 356 female undergraduate students. The experimental materials used in this study were 48 stimuli and a questionnaire composed of 7-point semantic differential scales of 26 adjectives. Twelve motifs selected from 3 groups of Korean motifs were used as pattern design stimuli. Twelve repeated patterns were constructed from them to be applied on a CAD-simulated dress. The data were analyzed by ANOVA, Duncan's multiple range test, and regression. The major findings were as follows : 1. Category, composition type, and application object had a significant effect on the preference. Interpretation type has no significant effects on the preference independently, but it had interaction effects when combined with composition type, and category. Especially the composition type had a greater effect than the other variables on the preference. Cloud motif and its abstract and decorative type were found to be more related to the preference than the other category and interpretation type. On the basis of the analysis results, image charts and preference charts were developed. By combining information from the image chart and preference chart, motifs and images preferred by consumers may be selected and developed into new valuable designs. 2. The preference was affected mainly by 'quality'image followed by 'simplicity', 'interest', and 'modernity'image. The preference on pattern design was affected by 'quality', 'simplicity', 'interest', and 'interest', 'simplicity', and 'modernity'image in the order. The relationship between the preference and sensibility images has been represented by equations.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.10
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• pp.2448-2463
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• 2013

The traditional block-based motion compensation methods in frame rate up-conversion (FRUC) only use a single uniquely motion vector field. However, there will always be some mistakes in the motion vector field whether the advanced motion estimation (ME) and motion vector analysis (MA) algorithms are performed or not. Once the motion vector field has many mistakes, the quality of the interpolated frame is severely affected. In order to solve the problem, this paper proposes a novel joint overlapped block motion compensation method (8J-OBMC) which adopts motion vectors of the interpolated block and its 8-neighbor blocks to jointly interpolate the target block. Since the smoothness of motion filed makes the motion vectors of 8-neighbor blocks around the interpolated block quite close to the true motion vector of the interpolated block, the proposed compensation algorithm has the better fault-tolerant capability than traditional ones. Besides, the annoying blocking artifacts can also be effectively suppressed by using overlapped blocks. Experimental results show that the proposed method is not only robust to motion vectors estimated wrongly, but also can to reduce blocking artifacts in comparison with existing popular compensation methods.

• Journal of Digital Convergence
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• v.12 no.10
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• pp.353-361
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• 2014

This study was confirmed nurse's traditional, social, professional and personal image of the dimensional perception of the difference between the majors and non-majors students exist? and Reflected on the role of the media image of nurses are there differences in perception? and Nurses and nurse related information, and information on contacting the media and contacted the media image of the existing research results and is there a difference? For the purpose, we survey the nursing majors and non-majors students. The results follows. First, the traditional nurses, social, professional and personal image perception gap is high. Second, the media reflected the image of the nurse in charge of the secondary role of a doctor about the image is high. Third, the nurse contacted the media about the TV is very high. The results of this study have implications to enable communication between patients and nurses agree that will provide evidence. In particular, the nurses through the use of media(PPL and Publicity strategy) suggest ways to improve the image.