• 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.

• Journal of Cadastre & Land InformatiX
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• v.47 no.1
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• pp.15-26
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• 2017

The decrease of green space according to the urbanization has caused many environmental problems as the destruction of habitat, air pollution, heat island effect. With interest growing in natural view recently, proper management of evergreen tree which is lived even the winter season has been on the rise importantly. This study analyzed the distribution area of evergreen tree using vegetation index based on unmanned aerial vehicle (UAV). Firstly, RGB and NIR+RG camera were loaded in fixed-wing UAV and image mosaic was achieved using GCPs based on Pix4d SW. And normalized differences vegetation index (NDVI) and soil adjusted vegetation index (SAVI) was calculated by band math function from acquired ortho mosaic image. validation points were applied to evaluate accuracy of the distribution of evergreen tree for each range value and analysis showed that kappa coefficient marked the highest as 0.822 and 0.816 respectively in "NDVI > 0.5" and "SAVI > 0.7". The area of evergreen tree in "NDVI > 0.5" and "SAVI > 0.7" was $11,824m^2$ and $15,648m^2$ respectively, that was ratio of 4.8% and 6.3% compared to total area. It was judged that UAV could supply the latest and high resolution information to vegetation works as urban environment, air pollution, climate change, and heat island effect.

• Journal of Fashion Business
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• v.14 no.6
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• pp.53-69
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• 2010

This study compared the work environment colors and the colors of working clothes by conducting a field survey of domestic machinery manufacturers who are playing a central role in Korean industries so as to develop and evaluate working clothes based on the safety of workers and environmental harmony. For the study method, after the color-related requirements were collected through interviews and field surveys, the fabrics for working clothes were woven and the colors were selected using the requirements. The designs of working clothes were developed with an emphasis on color design. The colors of the working clothes were also analyzed in their relationship to the working environment. The evaluations were separately performed for the appearance and the colors with workers of D machinery manufacturing company. The appearance and color satisfaction, safety, psychology, and harmony with environment were evaluated on a 5-point scale by workers and their safety managers. Furthermore, pictures of the workers in their existing working clothes and the newly developed working clothes were taken with a digital camera while they were working in the field. The RGB values of the pictures were extracted using Photoshop ver. 7.01, which were converted to HVC values using Munsell Conversion ver. 4.0.1. This study found that higher satisfaction levels were shown for the newly developed working clothes compared to the existing ones. The actual measurements also showed that the newly developed had higher brightness and clearer chromatic contrast than the existing ones, indicating higher explicitness and attention for safety of workers. These types of studies can contribute to the integrated working environment plan of machinery manufacturers.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.32 no.3
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• pp.191-197
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• 2019

As the shipbuilding and offshore plant industries grow larger and more complex, their maintenance and inspection systems become more important. Recently, maintenance and inspection systems based on augmented reality have been attracting much attention for improving worker's understanding of work and efficiency, but it is often difficult to work with because accurate matching between the augmented model and reality information is not. To solve this problem, marker based AR technology is used to attach a specific image to the model. However, the markers get damaged due to the characteristic of the shipbuilding and offshore plant industry, and the camera needs to be able to detect the entire marker clearly, and thus requires sufficient space to exist between the operator. In order to overcome the limitations of the existing AR system, in this study, a markerless AR was adopted to accurately recognize the actual model of the pipe system that occupies the most processes in the shipbuilding and offshore plant industries. The matching methodology. Through this system, it is expected that the twist phenomenon of the augmented model according to the attitude of the real worker and the limited environment can be improved.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.10C
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• pp.933-941
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• 2006

In this paper, we proposed an efficient coding method for digital hologram (fringe pattern) acquired by a CCD camera or by computer generation using multi-view prediction technique and MPEG video compression standard technique. It proceeds each R, G, or B color component separately. The basic processing unit is a partial image segmented into the size of $N{\times}N$. Each partial image retains the information of the whole object. This method generates an assembled image for a row of the segmented and frequency-transformed partial images, which is the basis of the coding process. That is, a motion estimation and compensation technique of MPEG is applif:d to the reconstructed images from the assembled images with the disparities found during generation of assembled image and the original partial images. Therefore the compressed results are the disparity of eachpartial image to form the assembled image for the corresponding row, assembled image, and the motion vectors and the compensated image for each partial image. The experimental results with the implemented algorithm showed that the proposed method has NC (Normal Correlation) values about 4% higher than the previous method, by which ours has better compression efficiency. Consequently, the Proposed method is expected to be used effectively in the application areas to transmit the digital hologram data. can be identified in comparison with the previous researches and commercial IPs.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1353-1369
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• 2023

In the event of a disaster accident at sea, the scale of damage will vary due to weather effects such as wind, currents, and tidal waves, and it is obligatory to minimize the scale of damage by establishing appropriate control plans through quick on-site identification. In particular, it is difficult to identify pollutants that exist in a thin film at sea surface due to their relatively low viscosity and surface tension among pollutants discharged into the sea. Therefore, this study aims to develop an algorithm to detect suspended pollutants on the sea surface in RGB images using imaging equipment that can be easily used in the field, and to evaluate the performance of the algorithm using input data obtained from actual waters. The developed algorithm uses image enhancement techniques to improve the contrast between the intensity values of pollutants and general sea surfaces, and through histogram analysis, the background threshold is found,suspended solids other than pollutants are removed, and finally pollutants are classified. In this study, a real sea test using substitute materials was performed to evaluate the performance of the developed algorithm, and most of the suspended marine pollutants were detected, but the false detection area occurred in places with strong waves. However, the detection results are about three times better than the detection method using a single threshold in the existing algorithm. Through the results of this R&D, it is expected to be useful for on-site control response activities by detecting suspended marine pollutants that were difficult to identify with the naked eye at existing sites.