• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.12
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• pp.4292-4307
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• 2021

For the research field of night infrared surveillance video, the target imaging in the video is easily affected by the light due to the characteristics of the active infrared camera and the classical ViBe algorithm has some problems for moving target extraction because of background misjudgment, noise interference, ghost shadow and so on. Therefore, an improved ViBe algorithm (I-ViBe) for moving target extraction in night infrared surveillance video is proposed in this paper. Firstly, the video frames are sampled and judged by the degree of light influence, and the video frame is divided into three situations: no light change, small light change, and severe light change. Secondly, the ViBe algorithm is extracted the moving target when there is no light change. The segmentation factor of the ViBe algorithm is adaptively changed to reduce the impact of the light on the ViBe algorithm when the light change is small. The moving target is extracted using the region growing algorithm improved by the image entropy in the differential image of the current frame and the background model when the illumination changes drastically. Based on the results of the simulation, the I-ViBe algorithm proposed has better robustness to the influence of illumination. When extracting moving targets at night the I-ViBe algorithm can make target extraction more accurate and provide more effective data for further night behavior recognition and target tracking.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.111-115
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• 2009

This paper is related to a skinny smudge tool based on the image segmentation for a master shape. The smudge tool is the popular graphic tool embedded in Adobe Photoshop. The smudge tool is used to smear paint on your canvas. The effect is much like finger painting. You can use the smudge tool by clicking on the smudge icon and clicking on the canvas and while holding the mouse button down, dragging in the direction you want to smudge. A disadvantage of previous smudge tool is to also smear pixels in the undesired region according to generating the target image as blending all pixels in a diameter of the master. In this paper to reduce the disadvantage, the skinny smudge tool based on the image segmentation for a master shape is proposed. The proposed skinny smudge tool has the advantage of applying the smudge effect to the desired regions regardless of the background as the master shape adhered closely to the contour shape is extracted by color image segmentation.

• Culinary science and hospitality research
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• v.23 no.5
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• pp.109-120
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• 2017

This study aimed to develop Chinese restaurant set menu which was proper to tendency of market segmentation by using conjoint analysis. In order to examine tendency of market segmentation, this study investigated the important factors and effective values of whole market and segment market. First, the study found that whole market and segment market seemed to prefer seafood to meat except Cluster 3 (Gentle demand type). Second, regarding efficiency of attribute level, the study found that crap soup is favored over seafood in both whole market and segment market except Cluster 1 (strong demand type). Third, Cluster 1 (strong demand type) showed a high level of efficiency on menu which is mixed with meat and seafood. In Cluster 2 (middle demand type), there was a high level of efficiency in meat menu. In case of Cluster 3 (gentle demand type), seafood menu showed high level of efficiency. Forth, there was a high level of efficacy in rice and western dessert menu on the result of analysis on whole market and segment market. Therefore, this study suggests that the preference of seafood is more higher than the preference of meat. It means that current customers care their health more than they used to be. According to this study, people who want to develop Chinese restaurant menu should focus on seafood more than meat. What's more, marketers of chinese restaurants have to not only present new awareness and fresh atmosphere but also provide typical composition of set menu for target customers.

• Phonetics and Speech Sciences
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• v.5 no.2
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• pp.43-51
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• 2013

English native listeners have a tendency to treat strong syllables in a speech stream as the potential initial syllables of new words, since the majority of lexical words in English have a word-initial stress. The current study investigates whether Korean (L1) - English (L2) late bilinguals perceive strong syllables in English continuous speech as word onsets, as English native listeners do. In Experiment 1, word-spotting was slower when the word-initial syllable was strong, indicating that Korean listeners do not perceive strong syllables as word onsets. Experiment 2 was conducted in order to avoid any possibilities that the results of Experiment 1 may be due to the strong-initial targets themselves used in Experiment 1 being slower to recognize than the weak-initial targets. We employed the gating paradigm in Experiment 2, and measured the Isolation Point (IP, the point at which participants correctly identify a word without subsequently changing their minds) and the Recognition Point (RP, the point at which participants correctly identify the target with 85% or greater confidence) for the targets excised from the non-words in the two conditions of Experiment 1. Both the mean IPs and the mean RPs were significantly earlier for the strong-initial targets, which means that the results of Experiment 1 reflect the difficulty of segmentation when the initial syllable of words was strong. These results are consistent with Kim & Nam (2011), indicating that strong syllables are not perceived as word onsets for Korean listeners and interfere with lexical segmentation in English running speech.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.4
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• pp.617-623
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• 2018

In this paper, we propose a novel seamless video composition method based on shape matching and Poisson equation. Video composition method consists of video segmentation process and video blending process. In the video segmentation process, the user first sets a trimap for the first frame, and then performs a grab-cut algorithm. Next, considering that the performance of video segmentation may be reduced if the color, brightness and texture of the object and the background are similar, the object region segmented in the current frame is corrected through shape matching between the objects of the current frame and the previous frame. In the video blending process, the object of source video and the background of target video are blended seamlessly using Poisson equation, and the object is located according to the movement path set by the user. Simulation results show that the proposed method has better performance not only in the naturalness of the composite video but also in computational time.

• Journal of Industrial Convergence
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• v.2 no.2
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• pp.47-68
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• 2004

The term "social marketing" was first introduced in 1971 to describe the use of marketing principles and techniques to advance a social cause, idea, or behavior. Social Marketing is a strategy for changing behavior. It utilizes concepts of market segmentation, consumer research, product concept development and testing, directed communication, facilitation, incentives, and exchange theory to maximize the target adopters' response. Social marketing requires knowledge of each target-adopter group, including its 1. social demographic characteristics, 2. psychological profile and 3. behavioral characteristics. To know the target adopters in these three related ways enables social marketer to make more accurate predictions. In addition to differentiating among and selecting target adopter groups, the social marketer will identify influence-holding groups, or influentials, who can affect a program's success. Great changes and opportunities exist to produce changes in the ways that individuals and groups think and behave and in meeting human needs. The balance of the scales of social change, we hope, will shift away from the use of force and violence to the use of persuasion and voluntary action. I trust that this dissertation will be useful highlighting the strategies and means of peaceful, planned social change designed to elevate the quality of life.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.5
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• pp.363-371
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• 2015

Feature extraction is one of the main goals in many remote sensing analyses. After high-resolution imagery became more available, it became possible to extract more detailed and specific features. Thus, considerable image segmentation algorithms have been developed, because traditional pixel-based analysis proved insufficient for high-resolution imagery due to its inability to handle the internal variability of complex scenes. However, the individual segmentation method, which simply uses color layers, is limited in its ability to extract various target features with different spectral and shape characteristics. Spectral indices can be used to support effective feature extraction by helping to identify abundant surface materials. This study aims to evaluate a feature extraction method based on a segmentation technique with spectral indices. We tested the extraction of diverse target features-such as buildings, vegetation, water, and shadows from eight band WorldView-2 satellite image using decision tree classification and used the result to draw the appropriate spectral indices for each specific feature extraction. From the results, We identified that spectral band ratios can be applied to distinguish feature classes simply and effectively.

• Journal of Broadcast Engineering
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• v.27 no.1
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• pp.44-55
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• 2022

In order to automatically provide information on fruits in agricultural related broadcasting contents, instance image segmentation of target fruits is required. In addition, the information on the 3D pose of the corresponding fruit may be meaningfully used. This paper represents research that provides information about tomatoes in video content. A large amount of data is required to learn the instance segmentation, but it is difficult to obtain sufficient training data. Therefore, the training data is generated through a data augmentation technique based on a small amount of real images. Compared to the result using only the real images, it is shown that the detection performance is improved as a result of learning through the synthesized image created by separating the foreground and background. As a result of learning augmented images using images created using conventional image pre-processing techniques, it was shown that higher performance was obtained than synthetic images in which foreground and background were separated. To estimate the pose from the result of object detection, a point cloud was obtained using an RGB-D camera. Then, cylinder fitting based on least square minimization is performed, and the tomato pose is estimated through the axial direction of the cylinder. We show that the results of detection, instance image segmentation, and cylinder fitting of a target object effectively through various experiments.

• Culinary science and hospitality research
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• v.3
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• pp.57-81
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• 1997

Recently foodservice industry marketing environment changes rapidly and the qualitic change of demand is accelerated from high growth phase to low growth on industrial environment. To actively competely with the foreign brands that runs with the developed management skills and enough fund, the domestic should classify the customers first and develop the menu. To introduce the modern management technique to pursue the management utility by establishing the market segmentation forcusing the target market and discriminating strategy of menu and service. The method of this study is focused on the changes of foodservice industrial environment and alternatives.

• Proceedings of the Korea Society for Simulation Conference
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• 2001.10a
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• pp.95-98
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• 2001

Edge detection is an important problem in computer vision and image understanding. Because the threshold is difficult to properly determine, edge images gained by the usually gradient-based segmentation methods are often tend to have many disjoint or overlapping boundaries, which makes the edge images spinous. In this paper, a practical multilevel morphological filter is presented for smoothing spinous edge images. The experimental results show that the method is effective in dealing with the images of a target in the sky.