• Korean Journal of Remote Sensing
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• v.38 no.5_1
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• pp.535-543
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• 2022

A drone is used to diagnose crop growth and to provide information through images in the agriculture field. In the case of using high spatial resolution drone images, growth information for each object can be produced. However, accurate object detection is required and adjacent objects should be efficiently classified. The purpose of this study is to develop a Chinese cabbage object detection algorithm using multispectral reflectance images observed from drone and computer vision techniques. Drone images were captured between 7 and 15 days after planting a Chinese cabbage from 2018 to 2020 years. The thresholds of object detection algorithm were set based on 2019 year, and the algorithm was evaluated based on images in 2018 and 2019 years. The vegetation area was classified using the characteristics of spectral reflectance. Then, morphology techniques such as dilatation, erosion, and image segmentation by considering the size of the object were applied to improve the object detection accuracy in the vegetation area. The precision of the developed object detection algorithm was over 95.19%, and the recall and accuracy were over 95.4% and 93.68%, respectively. The F1-Score of the algorithm was over 0.967 for 2 years. The location information about the center of the Chinese cabbage object extracted using the developed algorithm will be used as data to provide decision-making information during the growing season of crops.

• Journal of the Korea Society of Computer and Information
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• v.27 no.10
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• pp.11-17
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• 2022

In this paper, a model that can increase the efficiency of work in arranging interior furniture by applying augmented reality technology was studied. In the existing system to which augmented reality is currently applied, there is a problem in that information is limitedly provided depending on the size and nature of the company's product when outputting the image of furniture. To solve this problem, this paper presents an AR labeling algorithm. The AR labeling algorithm extracts feature points from the captured images and builds a database including indoor location information. A method of detecting and learning the location data of furniture in an indoor space was adopted using the CNN technique. Through the learned result, it is confirmed that the error between the indoor location and the location shown by learning can be significantly reduced. In addition, a study was conducted to allow users to easily place desired furniture through augmented reality by receiving detailed information about furniture along with accurate image extraction of furniture. As a result of the study, the accuracy and loss rate of the model were found to be 99% and 0.026, indicating the significance of this study by securing reliability. The results of this study are expected to satisfy consumers' satisfaction and purchase desires by accurately arranging desired furniture indoors through the design and implementation of AR labels.

• Journal of the Korean Geotechnical Society
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• v.39 no.2
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• pp.31-42
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• 2023

A study was conducted to use soil color obtained from digital im ages as an indicator of soil water content. Digital images of Jumoonjin standard sand with five different water contents were captured under nine different lighting conditions. Through digital image processing, the soil color of the sample was obtained based on the CIELAB color system, and the effect of lighting conditions and water content on the soil color was analyzed. The results indicated that L^* showed a high correlation with illuminance, whereas a^* and b^* showed a high correlation with color temperature. As the water content increased, L^*, which represents the brightness of the soil color, decreased, and a^* and b^* increased. Therefore, the soil color changed from green and blue to red and yellow. Based on the regression analysis results of lighting conditions, water content, and soil color, a water content predicting method based on the soil color of silica-based sand photographed under irregular light conditions was proposed. The proposed method can predict the water content with a m axim um error of 0.29%.

• Journal of the Korea Society for Simulation
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• v.18 no.4
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• pp.9-20
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• 2009

Navigation system providing route-guidance and traffic information is one of the most widely used driver-support system these days. Most of the navigation system is based on the 2D map paradigm so the information is ed and encoded from the real world. As a result it imposes a cognitive burden to the driver to interpret and translate the ed information to real world information. As a new concept of navigation system, augmented-reality navigation system (AR navigation) is suggested recently. It provides navigational guidance by imposing graphical information on real image captured by camera mounted on a vehicle in real-time. The ultimate goal of navigation system is to assist the driving task with least driving workload whether it is based on the abstracted graphic paradigm or realistic image paradigm. In this paper, we describe the comparative studies on how map navigation and AR navigation affect for driving tasks by experimental research. From the result of this research we obtained a basic knowledge about the two paradigms of navigation systems. On the basis of this knowledge, we are going to find the optimal design of navigation system supporting driving task most effectively, by analyzing characteristics of driving tasks and navigational information from the human-vehicle interface point of view.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.1
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• pp.15-22
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• 2022

In order to improve the accuracy of the deep learning object detection technique, the effect of magnification rate conditions and seasonal factors on detection accuracy in aerial photographs and drone images was analyzed through experiments. Among the deep learning object detection techniques, Mask R-CNN, which shows fast learning speed and high accuracy, was used to detect the vehicle to be detected in pixel units. Through Seoul's aerial photo service, learning images were captured at different screen magnifications, and the accuracy was analyzed by learning each. According to the experimental results, the higher the magnification level, the higher the mAP average to 60%, 67%, and 75%. When the magnification rates of train and test data of the data set were alternately arranged, low magnification data was arranged as train data, and high magnification data was arranged as test data, showing a difference of more than 20% compared to the opposite case. And in the case of drone images with a seasonal difference with a time difference of 4 months, the results of learning the image data at the same period showed high accuracy with an average of 93%, confirming that seasonal differences also affect learning.

• Proceedings of the Korea Contents Association Conference
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• 2006.11a
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• pp.322-326
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• 2006

Though human being has ability to percept a full colored vision, the technology of early photography only can produce black and white images. For cinema filming imagery also captured mono tone with black and white, until developed a color film technology. The desire for presenting color imagery and the technique for producing film and color ink, photography and print utilize color on it with noticeable color impact to viewers. It, however, abusing fun colors image each and every printed and filmed imagery, the freshness of eye catching power diminished now. On contrast, color becomes black and white or partially used for making discrepancy among full colored images. This image detected commercial and music video, and it spread to film. To use those bleached color images is for evoking a nostalgia and a visual differentiation. Especially, it can be provocative images brought to audience with that. such as "Anycall", "Dimchae" for CF, and "Schindler's list," and "Sin city" for movie. It is hard to investigate on the color studies for partially used images. Therefore, this study is to research that through CF and film, base on it, to investigate the application for this image. To collect data from survey, it will be established a basic concept for understanding the partial color applying.

• Journal of Naturopathy
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• v.9 no.1
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• pp.22-26
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• 2020

Purposes: The purposes of this study were to investigate the relationship between the standing position of the subject and the normal standing position(NSP) and the straight standing position(SSP) and to investigate the possibility of different body shape test results depending on the status of the image inspection apparatus. Methods: The images of the NSP and SSP were compared with each other by body line BLS system. Results: At the time of examination, the position of the camera was captured at a position 2.3 m vertically from the posterior position 45 cm behind the subject. This is a privacy protection method for covering the breast of the subject. Results: The physiological characteristics of the anatomical position of the body align image test are the living body. NSP and SSP tests showed different shapes of the pelvis AS(antero-supero) and pelvis rotation in the transverse plane. Shoulder and arm displacement was observed in the trunk extension image capture. Conclusions: In the body alignment test, the pelvis position test images of NSP and SSP are evaluated differently for pelvis rotation, AS, and PS. At the extension position of the trunk, a test of the maximal extension range showed that the left and right shortening of the shoulder anterior muscles could be observed. Inducing and testing the trunk extension is also useful.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.4
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• pp.337-345
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• 2023

Estimating the rice heading date is one of the most crucial agricultural tasks related to productivity. However, due to abnormal climates around the world, it is becoming increasingly challenging to estimate the rice heading date. Therefore, a more objective classification method for estimating the rice heading date is needed than the existing methods. This study, we aimed to classify the rice heading stage from various images using a CNN classification model. We collected top-view images taken from a drone and a phenotyping tower, as well as slanted-view images captured with a RGB camera. The collected images underwent preprocessing to prepare them as input data for the CNN model. The CNN architectures employed were ResNet50, InceptionV3, and VGG19, which are commonly used in image classification models. The accuracy of the models all showed an accuracy of 0.98 or higher regardless of each architecture and type of image. We also used Grad-CAM to visually check which features of the image the model looked at and classified. Then verified our model accurately measure the rice heading date in paddy fields. The rice heading date was estimated to be approximately one day apart on average in the four paddy fields. This method suggests that the water head can be estimated automatically and quantitatively when estimating the rice heading date from various paddy field monitoring images.

• Cartoon and Animation Studies
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• s.38
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• pp.53-70
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• 2015

In industrialized societies throughout the 19th and 20th centuries, Over Produced and Mass consumption images were constantly shown to people via Mass-Media as means to provoke one's desire. Frank Mouris, the American independent animator, captured and showed the infinite nesting of industrialized image with his autobiographical story through his work (1973) and made it as an intense visual flow. This innovative art animation has broke the traditional form of narrative animation and won the Annecy Animation Festival Grand Prix and the Academy Awards in 1974. This was also selected for preservation in the United States National Film Registry by the Library of Congress as being culturally, historically, or aesthetically significant in 1996. This study explores and shows that how these a-half million images to express Franks Mouris's autobiographical story in could be analyzed by the concept of Walter Benjamin's 'dialectical images'. Typically, the term 'dialectic' need to be formed by contradiction or opposite concept in the basic principles, but a dialectical image of Benjamin could be formed without any opposite concept while maintaining the uniqueness of each new relationship of the past. Benjamin's dialectical images are no longer stay in the historical past, It always meets with the present when someone realizes the past in the present moment. I suggest three different aspect according to Benjamin's point of view to analyse this animated film such as 'Historical-dialectical imaging of private/collective memory', 'Reconfiguring of present through analysing the relationship between the image flows and its own time/space', and 'Old future over the existing fragment and the presence of fragment. has the great value not only to present the experimental and innovative aesthetics of animated film, but also to show an analysis of contemporary culture and social aspect in mid-20th century. This study is to explore the diversity of animation representation, aesthetics, and also to suggest a new aspect of animation studies.

• Applied Chemistry for Engineering
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• v.31 no.1
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• pp.84-89
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• 2020

Particulate matters of PM_2.5, particularly focusing on 0.1~1 ㎛ decrease the efficiency of dust-collector due to the brownian-motion. This study is to verify the effect of coagulant on the particle size distributions of potassium and PM_2.5. The activated coagulant was spayed to the coal fired fluidized bed combustion boiler by the weight ratio of 1,200 : 1 = coal : coagulant, and the size distributions of captured particles at both the cyclone (FP) and electrostatic precipitator (EP) were measured. As the result of XRP analysis, the potassium content of FP increased to 13.33% (averagely from 1.65% to 1.87%) and, in EP at 17.68% (averagely from 1.65% to 2.03%). And it was confirmed by the particle size distribution analyzer and SEM image analysis that the distribution rates of PM_2.5 decreased at 89.53% on average in FP, and at 88.57% in EP. The total dust concentration (mg/㎥) confirmed by tele-monitering system (TMS) decreased during the primary test from 2.6 to 1.7~1.9 and also the secondary test from 2.9 to 1.7~1.9.