• Journal of the Korea Society of Computer and Information
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• v.14 no.9
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• pp.21-28
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• 2009

Color polarity classification is a process to determine whether the color of text is bright or dark and it is prerequisite task for text extraction. In this paper we propose a color polarity method to extract text region. Based on the observation for the text and background regions, the proposed method uses the ratios of sizes and standard deviations of bright and dark regions. At first, we employ Otsu's method for binarization for gray scale input region. The two largest segments among the bright and the dark regions are selected and the ratio of their sizes is defined as the first measure for color polarity classification. Again, we select the segments that have the smallest standard deviation of the distance from the center among two groups of regions and evaluate the ratio of their standard deviation as the second measure. We use these two ratio features to determine the text color polarity. The proposed method robustly classify color polarity of the text. which has shown by experimental result for the various font and size.

• Journal of Korea Multimedia Society
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• v.21 no.2
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• pp.147-157
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• 2018

Alzheimer's disease has the significant factors for the both specific and characteristic features according to the disease progressing that are the volumetry and surface area by the brain hippocampus shrinking and thinning. However, we have suggested a shape analysis to calculate the variance by the roughness, coarseness or uneven surface on 3D MR images. For the reasons we have presented two methods: the first method is the distance calculation from major axis to edge points and the second method is the distance calculation from centroidal point to edge points on a coronal plane. Then we selected the shortest distance and the longest distance in each slice and analyzed the ANOVA and average distances. Consequently we obtained the available and great results by the longest distance of the axial and centroidal point. The results of average distances were 44.85(AD), 45.04(MCI) and 49.31(NC) from the axial points and 39.30(AD), 39.58(MCI) and 44.78(NC) from centroidal points respectively. Finally the distance variations for the easily recognized visualization were shown by the color mapping. This research could be provided an indicator of biomarkers that make diagnosis and prognosis the Alzheimer's diseases in the future.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.2
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• pp.65-71
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• 2014

This paper present the multi-modal user distance estimation system using mono camera and mono microphone basically equipped with a mobile device. In case of a distance estimation method using an image, we is estimated a distance of the user through the skin color region extraction step, a noise removal step, the face and eyes region detection step. On the other hand, in case of a distance estimation method using speech, we calculates the absolute difference between the value of the sample of speech input. The largest peak value of the calculated difference value is selected and samples before and after the peak are specified as the ROI(Region of Interest). The samples specified perform FFT(Fast Fourier Transform) and calculate the magnitude of the frequency domain. Magnitude obtained is compared with the distance model to calculate the likelihood. We is estimated user distance by adding with weights in the sorted value. The result of an experiment using the multi-modal method shows more improved measurement value than that of single modality.

• Journal of The Korean Astronomical Society
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• v.28 no.2
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• pp.169-175
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• 1995

Deep V I CCD photometry of the Pegasus dwarf irregular galaxy shows that the tip of the red giant branch (RGB) is located at I = $21.15{\pm}0.10$ mag and (V - I) = $1.58{\pm}0.03$. Using the I magnitude of the tip of the RGB (TRGB), the distance modulus of the Pegasus galaxy is estimated to be $(m\;-\;M)_o\;=\;25.13{\pm}0.11$ mag (corresponding to a distance of d = $1060{\pm}50$ kpc). This result is in a good agreement with the recent distance estimate based on the TRGB method by Aparicio [1994, ApJ, 437, L27],$ (m\;-\;M)_o$ = 24.9 (d = 950 kpc). However, our distance estimate is much smaller than that based on the Cepheid variable candidates by Hoessel et al.[1990, AJ, 100, 1151], $(m\;-\;M)_o\;=\;26.22{\pm}0.20$ (d = $1750{\pm}160$ kpc) mag. The color-magnitude diagram illustrates that the Cepheid candidates used by Hoessel et al.are not located in the Cepheid instability strip, but in the upper part of the giant branch. This result shows that the Cepheid candidates studied by Hoessel et al.are probably not Cepheids, but other types of variable stars. Taking the average of our distance estimate and Aparicio's, the distance to the Pegasus galaxy is d= $1000{\pm}80$ kpc. Considering the distance and velocity of the Pegasus galaxy with respect to the center of the Local Group, we conclude that the Pegasus galaxy is probably a member of the Local Group.

• Journal of Digital Convergence
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• v.20 no.4
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• pp.513-518
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• 2022

In the past two years, all sectors of society have been underdeveloped and suffered a significant damage due to COVID-19. In particular, people who were working in many areas of research were unable to do anything due to restrictions on meetings with people and social distancing. The purpose of this study is to develop a social distancing device that allows users to maintain the distance in accordance with the government guidelines through an analysis of people's social distancing methods in the COVID-19 society through UX Design. In order to develop the social distancing device, the distance is expressed by changing the color of LED based on research related to UI design such as ultrasonic distance sensor, battery, charging method, distance display method, etc. The outer form of the social distancing device is designed using 3D, the device is developed by installing ultrasonic distance sensor, neo-pixel module and Arduino after printing a prototype using a 3D printer, and this device is tested to develop a final product that helps the social distancing practice amid COVID-19.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.49 no.4
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• pp.10-15
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• 2012

In a color image, people and especially facial patterns are important and interesting visual objects. Thus, effective skin color reproduction is essential, as skin color is a key memory color in color application systems. Previous studies suggested skin color reproduction by mapping only to the center value of preferred skin region. However, it is not suitable to determine one preference color because preference color from the observer's preference test is not dominant. In this paper, skin color reproduction using multiple preferred skin colors for each race is proposed. The proposed method first defines multiple preferred skin colors for each race according to their luminance level. After that, skin region is detected in an image. The race is then selected by calculating distance between average chromaticity of detected region and that of each racial skin from a database to assign preferred skin color for each race. Next, each corresponding preferred skin color is determined for each selected race. Finally, input skin color is proportionally mapped toward preferred skin color according to the difference between the input skin color and the preferred skin color for a smoothly reproduced skin color. In the experimental results, the proposed method gives better color correction on the objective and subjective evaluation than the previous methods.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.1
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• pp.177-186
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• 2020

This paper deals with the car paint sequencing problem (CPSP) that the entrance sequence is to same colored group with maximum sequenced cars for the buffer arriving cars from the body shop. This problem classified by NP-complete problem because of the exact solution has not obtained within polynomial time. CPSP is aim to minimum pugging number that each pugging must be performs at color changing time in order to entirely cleaning the remaining previous color. To be obtain the minimum number of moving distance with window concept and minimum number of pugging, this paper sorts same color and arriving sequence. Then we basically decide the maximum length section color time to winner team using stage race method. For the case of the loser team with no more racing or yield to loser team and more longer stage in upcoming racing, the winner team give way to loser team. As a result, all cars(runners) are winner in any stage without fail. For n cars, the proposed algorithm has a advantage of simple and fast with O(nlogn) polynomial time complexity, this algorithm can be get the minimum number of moving distance and purging for all of experimental data.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.41 no.6
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• pp.81-89
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• 2004

In this paper, we compare face recognition rate by PCA algorithm using distance change and embedded data being input left side and right side image in stereo images. The proposed method detects face region from RGB color space to YCbCr color space. Also, The extracted face image's scale up/down according to distance change and extracts more robust face region. The proposed method through an experiment could establish standard distance (100cm) in distance about 30∼200cm, and get 99.05% (100cm) as an average recognition result by scale change. The definition of super state is specification region in normalized size (92${\times}$112), and the embedded data extracts the inner factor of defined super state, achieved face recognition through PCA algorithm. The orignal images can receive specification data in limited image's size (92${\times}$112) because embedded data to do learning not that do all learning, in image of 92${\times}$112 size averagely 99.05%, shows face recognition rate of test 1 99.05%, test 2 98.93%, test 3 98.54%, test 4 97.85%. Therefore, the proposed method through an experiment showed that if apply distance change rate could get high recognition rate, and the processing speed improved as well as reduce face information.

• Journal of the Korea Computer Industry Society
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• v.7 no.5
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• pp.537-544
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• 2006

Image Search is one of the most exciting and fast growing research areas in the filed of multimedia technology. This paper conducts an empirical evaluation of color descriptor that uses the information of color distribution in color images, which is the most basic element for image search. With the experimental results, we observe that in the top 10% of precision, HSV, Daubechies 9/7 and 2 level decomposition have little better than others. Also histogram quadratic metrics outperform the Minkowski form distance metrics in similarity measurements, but spend more than 20 in computational times.

• The Transactions of the Korea Information Processing Society
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• v.7 no.9
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• pp.2994-3001
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• 2000

In this paper. a method for color image segmentation using region merging is proposed. A inhomogeneity which exists in image is reduced by smoothing with non-linear filtering. saturation enhancement and intensity averaging in previous step of image segmentation. and a similar regions are segmented by non-uniform quantization using zero-crossing information of color histogram. A edge strength of initial region is measured using high frequency energy of wavelet transform. A candidate region which is merged in next step is selected by doing this process. A similarity measure for region merging is processed using Euclidean distance of R. G. B color channels. A Proposed method can reduce an over-segmentation results by irregular light sources et. al, and we illustrated that the proposed method is reasonable by simulation.