• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.4 s.310
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• pp.66-73
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• 2006

Safety is the most important for all traffic management and control technology. This paper focuses on developing a flexible, reliable and real-time processing algorithm which is able to generate signal for the entering vehicle at the joining road through a camera and image processing technique. The images obtained from the camera located beside and upon the road can be used for traffic surveillance, the vehicle's travel speed measurement, predicted arriving time in joining area between main road and joining road. And the proposed algorithm displays the confluence safety signal with red, blue and yellow color sign. The three methods are used to detect the vehicle which is driving in setted detecting area. The first method is the gray scale normalized correlation algorithm, and the second is the edge magnitude ratio changing algorithm, and the third is the average intensity changing algorithm The real-time prototype confluence safety signal generation algorithm is implemented on stored digital image sequences of real traffic state and a program with good experimental results.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.1
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• pp.153-158
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• 2016

A detection algorithm of fallen pear bags caused by natural disaster like heavy rain, typhoon, hurricane, etc. is presented in this paper. The algorithm is developed for the gray pear bags with printed characters which are widely used at pear farms at Sangju and Naju producing large quantity of pears for export. It sets a region of interest (ROI) at first and then eliminates the regions having chromatic color in ROI. Morphological operation and prior information are used to eliminate small noises and several unusual regions and finally the regions of fallen pear bags are remained. The remained regions are analyzed and counted to estimate the scale of damage. Test images are consisted of the images taken at pear farms of Sangju and Naju at 2014. Experimental result shows that the detection rate of pear bags is more than 90% and also the proposed system can be implemented in real-time using hand-held devices because of its simple and parallel architecture.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.1
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• pp.8-15
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• 2011

In this paper, we propose a new structure modeling algorithm from 3D cloud points of terrestrial LADAR data. Terrestrial LIDAR data have various obstacles which make it difficult to apply conventional algorithms designed for air-borne LIDAR data. In the proposed algorithm, the field data are separated into several clusters by adopting the structure extraction method which uses color information and Hough transform. And cluster based Delaunay triangulation technique is sequentially applied to model the artificial structure. Each cluster has its own priority and it makes possible to determine whether a cluster needs to be considered not. The proposed algorithm not only minimizes the effects of noise data but also interactively controls the level of modeling by using cluster-based approach.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.49 no.1
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• pp.41-48
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• 2012

Red tide is a natural phenomenon temporary blooming harmful algal with changing sea color from normal to red, which fish and shellfish die en masse. It also give a bad influence to coastal environment and sea ecosystem. The damage of sea farming by a red tide has been occurred each year which it cost much to prevent disasters of red tide blooms. Red tide damage and prevention cost of red tide disasters can be minimized by means of prediction of red tide blooms. In this paper, we proposed the red tide blooms prediction method using ensemble train. The proposed method use the bagging and boosting ensemble train methods for enhancing red tide prediction and forecast. The experimental results demonstrate that the proposed method achieves a better red tide prediction performance than other single classifiers.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.6
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• pp.16-25
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• 2009

In this paper we propose the block based image segmentation method using the cyclic properties of hue components in HSI color model. In proposed method we use center point instead of hue mean values as the hue representatives for regions in image segmentation considering hue cyclic properties and we also use directed distance for the hue difference among regions. Furthermore we devise the simple and effective method to get critical values through control parameter to reduce the complexity in the calculation of those in the conventional method. From the experimental results we found that the segmented regions in the proposed method is more natural than those in the conventional method especially in texture and red tone regions. In the simulation results the proposed method is better than the conventional methods in the in the evaluation of the human segmentation dataset presented Berkely Segmentation Database.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.11
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• pp.195-205
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• 2013

The analysis of electroencephalographic signal associated with the attention is essential for the understanding of human cognition. In this paper, the characteristic differences between the attention and inattention status in the brain were inspected by nonlinear analysis. The recurrence quantification analysis was applied to the relatively small number of samples of evoked potential having time varying characteristics, where the recurrence plot (RP), the color recurrence plot (CRP), and mean and time-sequential trend parameters were extracted. The dimension and the time delay in phase transformation can be determined by the paired set of extracted parameters. It is observed from RP, CRP, and parameters that the brain dynamics in attention is more complex than that in the inattention, as well as the synchronized brain response is stable in the mean sense but locally time varying. It is feasible that the non-linear analysis method can be useful for the analysis of complex brain dynamics associated during visual attentional task.

• Korean journal of food and cookery science
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• v.31 no.5
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• pp.581-587
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• 2015

This study was conducted to investigate the antioxidative and antimicrobial activities of Korean dandelion (Taraxacum coreanum). Water extracts, ethanol extracts and methanol extracts were used to examine the free radical scavenging activity, total flavonoid content, total polyphenol content and antimicrobial activity. The free radical scavenging activity, total flavonoid, total polyphenol and total antioxidant activity of the water extracts were higher than those of the other extraction solvents. The antimicrobial activties of Korean dandelion extracts were examined on several food borne illness microorganisms using the paper disc diffusion method. Inhibition zones were observed on Staphylococcus aureus subsp. aureus, Listeria monocytogenes, Bacillus subtilis, Bacillus cereus and Escherichia coli in ethanol extracts. Inhibition zones were also observed on Listeria monocytogenes in water extracts. The physico-chemical properties of Korean dandelion tea according to the roasting time and soaking amount of tea were studied. The pH of the dandelion tea significantly decreased while the soluble solid contents significantly increased with increased roasting time (p<0.01). The lightness of the dandelion tea decreased and the turbidity increased with increased roasting time. In sensory evaluation, the sensory scores for the color, flavor and total acceptability were highest in the 40 min roasted tea. These results suggest that the water extract of Korean dandelion could be used as an antioxidative and antimicrobial functional food source. The optimum roasting time for Korean dandelion tea was 40 min at $200^{\circ}C$.

• Journal of the Korea Computer Graphics Society
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• v.16 no.4
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• pp.35-40
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• 2010

Due to the distribution of digital camera, many work for photo management has been studied. However, most work use a sequential grid layout which arranges photos considering one criterion of digital photo. This interface makes users have lots of scrolling and concentrate ability when they manage their photos. In this paper, we propose a clustering method based on a temporal sequence considering their color similarity in detail. First we cluster photos using Cooper's event clustering method. Second, we makes more detailed clusters from each clustered photo set, which are clustered temporal clustering before, using maximal clique finding algorithm of interval graph. Finally, we arrange each detailed dusters on a user screen with their overlap keeping their temporal sequence. In order to evaluate our proposed system, we conducted on user studies based on a simple questionnaire.

• Journal of the Korea Convergence Society
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• v.8 no.7
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• pp.7-13
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• 2017

Robot performances in public places are conducted for the purpose of promoting robot technology and inducing interest in events, exhibitions, and streets instead of dedicated stages. This paper extracts robot images in real time from a robot operation in front of a green chroma key cloth, and synthesizes them on various stage images. A simple and robust method for extracting a foreground robot from a chroma key background without a user's preset is proposed. After increasing the color difference between the background and the foreground, this method automatically removes the background based on the histogram of the difference information, thereby eliminating the need for a user's preset. The simulation shows 98.8% of foreground extraction rate and experimental results demonstrate that the robots can effectively be extracted from the background.

• Journal of Korea Game Society
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• v.17 no.3
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• pp.45-52
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• 2017

This paper proposes a new strategy of emotion-based music visualization. Emotional LED lighting control system is suggested to help audiences enhance the musical experience. In the system, emotion in music is recognized by a proposed algorithm using a dimensional approach. The algorithm used a method of music emotion variation detection to overcome some weaknesses of Thayer's model in detecting emotion in a one-second music segment. In addition, IRI color model is combined with Thayer's model to determine LED light colors corresponding to 36 different music emotions. They are represented on LED lighting control system through colors and animations. The accuracy of music emotion visualization achieved to over 60%.