• Journal of Information Technology Applications and Management
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• v.28 no.6
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• pp.69-85
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• 2021

In the era of the 4th Industrial Revolution, not only artificial intelligence, big data, robots, and biotechnology, but also cultural industries that require human creativity will lead. Among the cultural industries, the animation industry has high industrial utilization value due to its high connection with other industries. Among them, animation characters play the most important role as the subject leading the story of animation. In particular, the villain character not only serves as a medium for the main character to lead the story, but also captivates the audience with a different presence from the main character, adding to the fun and completeness of the animation. These characters consist of visual elements such as form and color, of which color is a tool that effectively conveys the character's personality and role to the audience, and is the first visual element to be considered in delicately describing the character's emotions and the relationship between characters. Therefore, this study attempts to analyze the color of the villain character. To this end, we will select eight Disney animations to derive the characteristics of the villain character's color by analyzing the color, value, chroma, and color association of the colors used in the Disney villain character. As a result of the analysis, the colors mainly used by Disney to convey the villain's image were red (R) and Orange (YR), and there was no difference depending on the times or animation production methods. Second, the brightness of Disney villain characters appeared to be the same medium/famous regardless of the times and production methods, and the frequency of use of high brightness was very low. In terms of saturation, the frequency of use of high and low saturation was high. Third, blackish (Bk), Strong (S), dull (Dl), and deep (Dp) tones were mainly used for tones. In particular, in recent 3D animations than previously produced 2D animations, the use of low chroma and the high black mixing rate increased. Fourth, it can be seen that Disney uses color as a visual method to more clearly express the psychology of the villain character using color association. In conclusion, the color selection of animation characters should be carefully considered as a tool to convey the character's personality, role, and emotion beyond simply using color, and the color selection of characters using color associations and symbols strengthens the narrative structure. It is hoped that this study will help analyze and select the character color of animation.

• Journal of the Korean earth science society
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• v.37 no.7
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• pp.420-433
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• 2016

The purpose of this study is to improve the calibration matrixes of 2-D and 3-D convective rainfall rates (CRR) using the brightness temperature of the infrared $10.8{\mu}m$ channel (IR), the difference of brightness temperatures between infrared $10.8{\mu}m$ and vapor $6.7{\mu}m$ channels (IR-WV), and the normalized reflectance of the visible channel (VIS) from the COMS satellite and rainfall rate from the weather radar for the period of 75 rainy days from April 22, 2011 to October 22, 2011 in Korea. Especially, the rainfall rate data of the weather radar are used to validate the new 2-D and 3-DCRR calibration matrixes suitable for the Korean peninsula for the period of 24 rainy days in 2011. The 2D and 3D calibration matrixes provide the basic and maximum CRR values ($mm\;h^{-1}$) by multiplying the rain probability matrix, which is calculated by using the number of rainy and no-rainy pixels with associated 2-D (IR, IR-WV) and 3-D (IR, IR-WV, VIS) matrixes, by the mean and maximum rainfall rate matrixes, respectively, which is calculated by dividing the accumulated rainfall rate by the number of rainy pixels and by the product of the maximum rain rate for the calibration period by the number of rain occurrences. Finally, new 2-D and 3-D CRR calibration matrixes are obtained experimentally from the regression analysis of both basic and maximum rainfall rate matrixes. As a result, an area of rainfall rate more than 10 mm/h is magnified in the new ones as well as CRR is shown in lower class ranges in matrixes between IR brightness temperature and IR-WV brightness temperature difference than the existing ones. Accuracy and categorical statistics are computed for the data of CRR events occurred during the given period. The mean error (ME), mean absolute error (MAE), and root mean squire error (RMSE) in new 2-D and 3-D CRR calibrations led to smaller than in the existing ones, where false alarm ratio had decreased, probability of detection had increased a bit, and critical success index scores had improved. To take into account the strong rainfall rate in the weather events such as thunderstorms and typhoon, a moisture correction factor is corrected. This factor is defined as the product of the total precipitable waterby the relative humidity (PW RH), a mean value between surface and 500 hPa level, obtained from a numerical model or the COMS retrieval data. In this study, when the IR cloud top brightness temperature is lower than 210 K and the relative humidity is greater than 40%, the moisture correction factor is empirically scaled from 1.0 to 2.0 basing on PW RH values. Consequently, in applying to this factor in new 2D and 2D CRR calibrations, the ME, MAE, and RMSE are smaller than the new ones.

• The KIPS Transactions:PartB
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• v.18B no.2
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• pp.51-56
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• 2011

Algorithms for intrinsic images reduce color differences in RGB images caused by the temperature of black-body radiators. Based on the reference light and detecting single invariant direction, these algorithms are weak in real images which can have multiple invariant directions when the scene illuminant is a colored illuminant. To solve these problems, this paper proposes a method of acquiring an intrinsic image by omnidirectional projection of an ROI and a translation of white patch in the ${\chi}$-chromaticity space. Because it is not easy to analyze an image in the three-dimensional RGB space, the ${\chi}$-chromaticity is also employed without the brightness factor in this paper. After the effect of the colored illuminant is decreased by a translation of white patch, an invariant direction is detected by omnidirectional projection of an ROI in this chromaticity space. In case the RGB image has multiple invariant directions, only one ROI is selected with the bin, which has the highest frequency in 3D histogram. And then the two operations, projection and inverse transformation, make intrinsic image acquired. In the experiments, test images were four datasets presented by Ebner and evaluation methods was the follows: standard deviation of the invariant direction, the constancy measure, the color space measure and the color constancy measure. The experimental results showed that the proposed method had lower standard deviation than the entropy, that its performance was two times higher than the compared algorithm.

• Journal of Korean Academy of Oral and Maxillofacial Radiology
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• v.28 no.2
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• pp.471-489
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• 1998

For the successful endodontic treatment, root canal should be cleaned thoroughly by accurate mechanical and chemical canal preparation and sealed completely with canal filling material without damaging the periapical tissues. The accuracy of the root canal length measurement is a prerequisite for the success of the endodontic treatment, and the root canal length is often determined by the standard periapical radiographs and digital tactile sense. In this study, the accuracy and the clinical usefulness of Digora/sup (R)/, an intraoral digital imaging processor and the conventional standard radiographs were compared by measuring the length from the top of the file to the root apex. 30 single rooted premolars were invested in a uniformly sized blocks and No.25 K-file was inserted into and fixed in each canal. Each block was placed in equal distance and position to satisfy the principle of the bisecting angle and paralleling techniques and Digora/sup (R)/ system's image and standard periapical radiographs were taken. Each radiograph was examined by 3 different observers by measuring the length from top of the file to the root apex and each data was compared and analyzed. The results were as follows; 1. In the bisecting angle technique, the average difference between the Digora/sup (R)/ system and standard periapical radiograph was 0.002 mm and the standard deviation was 0.341 mm which showed no statistically significant difference between the two systems(p>0.05). Also, in the paralleling technique, the average difference between these two system was 0.007 mm and the standard deviation was 0.323 mm which showed no statistically significant difference between the two systems(p>0.05). 2. In Digora/sup (R)/ system, the average difference between the bisecting angle and paralleling technique was -0.336 mm and the standard deviation was 0.472 mm which showed a statistically significant difference between the two techniques(p<0.05). Also, in the standard periapical radiographs, the average difference between the bisecting angle and paralleling technique was 0.328 mm and the standard deviation was 0.517 mm which showed a statistically significant difference between these two techniques(p<0.05). 3. In Digora/sup (R)/ system and the standard periapical radiographs. there was a statistically significant difference between the measurement using the bisecting angle technique and the actual length(p<0.05), But there was no statistically significant difference between the measurement using the paralleling technique and the actuallength(p>0.05). In conclusion. the determination of the root canal length by using the Digora/sup (R)/ system can give us as good an image as the standard periapical radiograph and using the paralleling technique instead of the bisecting angle technique can give a measurement closer to the actual canal length. thereby contributing to a successful result. Also. considering the advantages of the digital imaging processor such as decreasing the amount of exposure to the patient. immediate use of the image. magnification of image size. control of the contrast and brightness and the ability of storing the image can give us good reason to replace the standard periapical radiographs.

• 전자공학회논문지 IE
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• v.46 no.4
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• pp.57-65
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• 2009

This paper presents the image contrast enhancement technique suitable for local dimming backlight of small-sized mobile display while achieving the reduction of the power consumption. In addition to the large-sized TFT-LCD, small-sized one has adopted LED for backlight. Since, conventionally, LED was mounted on the side edge of a display panel, global dimming method has been widely used. However, recently, new advanced method of local dimming by placing the LED to the backside of the display panel and it raised the necessity of sub-blocked processing after partitioning the target image. When the sub-blocked image has low brightness, the supply current of a backlight LED is reduced, which gives both enhancement of contrast ratio and power consumption reduction. In this paper, we propose simple and improved image enhancement algorithm suitable for the small-sized mobile display. After partitioning the input image by equal sized blocks and analyzing the pixel information in each block, we realize the primary contrast enhancement by independently processing the sub-blocks using the information such as histogram, mean, and standard deviation values of luminance(Y) component. And then resulting information is transferred to each backlight control unit for local dimming to realize the secondary contrast enhancement as well as reduction of power consumption.

• Journal of Korea Multimedia Society
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• v.11 no.9
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• pp.1296-1301
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• 2008

Ultrasonography constructs pictures of areas inside the body needs in diagnosis by bouncing high-enorgy sound waves(ultrasound) off internal tissues or organs. In constructing an ultrasonographic image, the weakness of bounding signals induces noises and detailed differences of brightness, so that having a difficulty in detecting and diagnosing with the naked eyes in the analysis of ultrasonogram. Especially, the difficulty is extended when diagnosing muscle areas by using ultrasonographic images in the musculoskeletal test. In this paper, we propose a novel image processing method that computationally extracts a muscle area from an ultrasonographic image to assist in diagnosis. An ultrasonographic image consists of areas corresponding to various tissues and internal organs. The proposed method, based on features of intensity distribution, morphology and size of each area, extracts areas of the fascia, the subcutaneous fat and other internal organs, and then extracts a muscle area enclosed by areas of the fascia. In the extraction of areas of the fascia, a series of image processing methods such as histogram stretching, multiple operation, binarization and area connection by labeling is applied. A muscle area is extracted by using features on relative position and morphology of areas for the fascia and muscle areas. The performance evaluation using real ultrasonographic images and specialists' analysis show that the proposed method is able to extract target areas being approximate to real muscle areas.

• Journal of the Institute of Convergence Signal Processing
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• v.22 no.2
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• pp.71-78
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• 2021

In order to classify a target image in a cluster of images, the difference in brightness between the object and the background is mainly concerned, which is not easy to classify if the shape of the object is blurred and the sharpness is low. However, there are a few studies attempted to solve these problems, and there is still the problem of not properly distinguishing between wrong pattern and right pattern images when applied to actual data analysis. In this paper, we propose an algorithm that classifies 3D films into sharp and blurry using the width of the pixel values histogram. This algorithm determines the width of the right and wrong images based on the width of the pixel distributions. The larger the width histogram, the sharp the image, while the shorter the width histogram the blurry the image. Experiments show that the proposed algorithm reflects that the characteristics of these histograms allows classification of all wrong images and right images. To determine the reliability and validity of the proposed algorithm, we compare the results with the other obtained from preprocessed 3D films. We then trained the 3D films using few-shot learning algorithm for accurate classification. The experiments verify that the proposed algorithm can perform higher without complicated computations.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.3
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• pp.82-98
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• 2019

The importance of spatial information is rapidly rising. In particular, 3D spatial information construction and modeling for Real World Objects, such as smart cities and digital twins, has become an important core technology. The constructed 3D spatial information is used in various fields such as land management, landscape analysis, environment and welfare service. Three-dimensional modeling with image has the hig visibility and reality of objects by generating texturing. However, some texturing might have occlusion area inevitably generated due to physical deposits such as roadside trees, adjacent objects, vehicles, banners, etc. at the time of acquiring image Such occlusion area is a major cause of the deterioration of reality and accuracy of the constructed 3D modeling. Various studies have been conducted to solve the occlusion area. Recently the researches of deep learning algorithm have been conducted for detecting and resolving the occlusion area. For deep learning algorithm, sufficient training data is required, and the collected training data quality directly affects the performance and the result of the deep learning. Therefore, this study analyzed the ability of detecting the occlusion area of the image using various image quality to verify the performance and the result of deep learning according to the quality of the learning data. An image containing an object that causes occlusion is generated for each artificial and quantified image quality and applied to the implemented deep learning algorithm. The study found that the image quality for adjusting brightness was lower at 0.56 detection ratio for brighter images and that the image quality for pixel size and artificial noise control decreased rapidly from images adjusted from the main image to the middle level. In the F-measure performance evaluation method, the change in noise-controlled image resolution was the highest at 0.53 points. The ability to detect occlusion zones by image quality will be used as a valuable criterion for actual application of deep learning in the future. In the acquiring image, it is expected to contribute a lot to the practical application of deep learning by providing a certain level of image acquisition.

• Journal of Physiology & Pathology in Korean Medicine
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• v.23 no.1
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• pp.97-103
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• 2009

The status and the property of a tongue are the important indicators to diagnose one's health like physiological and clinicopathological changes of inner organs. However, the tongue diagnosis is affected by examination circumstances like a light source, patient's posture, and doctor's condition. To develop an automatic tongue diagnosis system for an objective and standardized diagnosis, classifying tongue coating is inevitable but difficult since the features like color and texture of the tongue coatings and substance have little difference, especially in the neighborhood on the tongue surface. The proposed method has two procedures; the first is to acquire the color table to classify tongue coatings and substance by automatically separating coating regions marked by oriental medical doctors, decomposing the color components of the region into hue, saturation and brightness and obtaining the 2nd order discriminant with statistical data of hue and saturation corresponding to each kind of tongue coatings, and the other is to apply the tongue region in an input image to the color table, resulting in separating the regions of tongue coatings and classifying them automatically. As a result, kinds of tongue coatings and substance were segmented from a face image corresponding to regions marked by oriental medical doctors and the color table for classification took hue and saturation values as inputs and produced the classification of the values into white coating, yellow coating and substance in a digital tongue diagnosis system. The coating regions classified by the proposed method were almost the same to the marked regions. The exactness of classification was 83%, which is the degree of correspondence between what Oriental medical doctors diagnosed and what the proposed method classified. Since the classified regions provide effective information, the proposed method can be used to make an objective and standardized diagnosis and applied to an ubiquitous healthcare system. Therefore, the method will be able to be widely used in Oriental medicine.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2007.04a
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• pp.201-205
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• 2007

In the post-Cold War era, acquisition technique of high-resolution satellite imagery (HRSI) has begun to commercialize. IKONOS-2 satellite imaging data is supplied for the first time in the 21st century. Many researchers testified mapping possibility of the HRSI data instead of aerial photography. It is easy to renew and automate a topographical map because HRSI not only can be more taken widely and periodically than aerial photography, but also can be directly supplied as digital image. In this study matching size of IKONOS Geo-level stereo image is presented lot production of digital elevation model (DEM). We applied area based matching method using correlation coefficient of pixel brightness value between the two images. After matching line (where "matching line" implies straight line that is approximated to complex non-linear epipolar geometry) is established by exterior orientation parameters (EOPs) to minimize search area, the matching is tarried out based on this line. The experiment on matching size is performed according to land cover property, which is divided off into four areas (water, urban land, forest land and agricultural land). In each of the test areas, window size for the highest correlation coefficient is selected as propel size for matching. As the results of experiment, the proper size was selected as $123{\times}123$ pixels window, $13{\times}13$ pixels window, $129{\times}129$ pixels window and $81{\times}81$ pixels window in the water area, urban land, forest land and agricultural land, respectively. Of course, determination of the matching size by the correlation coefficient may be not absolute appraisal method. Optimum matching size using the geometric accuracy therefore, will be presented by the further work.