• The Journal of the Korea Contents Association
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• v.8 no.11
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• pp.182-188
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• 2008

The MLC(multi leaf collimator) in charge of important role in radiation therapy field recently have been exchanging from shielding block into it rapidly, owing to being convenient. However, MLC can be occurred the leakage dose of inter_leaves and the error of algorithm in imput and output from digital signal. We compared the difference of imput method to MLC made by Varian Cop. with the error and effective field induced by MLC shaper and film scanner based on XimaVision value as using MLC layer of various shapes. According to comparing standard value with them to basic MLC layer (test1-5), MLC shaper was $0{\sim}0.29cm$, $0.23{\sim}3.59cm^2$ and film scanner was $0{\sim}0.78cm$, $0.24{\sim}3.89cm^2$. At the MLC layer to be applied in clinic, MLC shaper was $0{\sim}0.54cm$, $0.04{\sim}1.68cm^2$ and film scanner was $0{\sim}0.78cm$, $0.24{\sim}3.89cm^2$. The more distance and field from axis of central line increase, the more bigger the error value increases. There is a few mm error from standard point at the process which imput various information to apply MLC in clinic. and effective field did not have variation of monitor unit and dose owing to being a few cm2 error against real field. But there are some problem to shield critical organs because some part of target volume induced by the movement of organs can be not included, therefore we have to pay attention on the process to imput MLC layer

• Korean Journal of Agricultural and Forest Meteorology
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• v.18 no.4
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• pp.378-388
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• 2016

International societies are currently working together to achieve the Climate-Smart Agriculture (CSA) initiative which aims the triple wins: (1) sustainably increasing agricultural productivity and incomes; (2) adapting and building resilience to climate change; and (3) mitigating greenhouse gases emissions. In terms of its scope and context, CSA follows the '3Nong (三農)' vision cast about 200 years ago by Dasan Jeong Yak-Yong who emphasized the triad of governance, management and monitoring towards comfortable, profitable and noble agriculture. Yet, the CSA provides the practical aims that facilitate the development of holistic indicators for quantitative evaluation and monitoring, on which decision-making support system is based. In this study, we introduce an agent-based model, i.e. Mathematical Programming Multi-Agent Systems (MP-MAS), as a tool for supporting the decision-making toward CSA. We have established the initial version of MP-MAS adapted for domestic use and present the preliminary results from an application to the rice farming case in Haenam, Korea. MP-MAS can support both farmers and policy-makers to consider diverse management options from multiple perspectives. When the modules for system resilience and carbon footprint are added, MP-MAS will serve as a robust tool that fulfills not only CSA but also Dasan's '3Nong' vision of sustainable agricultural-societal systems.

• 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 Institute of Control, Robotics and Systems
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• v.21 no.12
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• pp.1130-1135
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• 2015

The bond pull test is the most widely used technique for the evaluation and control of wire bond quality. The wire being tested is pulled upward until the wire or bond to the die or substrate breaks. The inspector test strength of wire by manually and it takes around 3 minutes to perform the test. In this paper, we develop a 3D vision system to measure 3D position of wire. It gives 3D position data of wire to move a hook into wires. The 3D measurement method to use here is a confocal imaging system. The conventional confocal imaging system is a spot scanning method which has a high resolution and good illumination efficiency. However, a conventional confocal systems has a disadvantage to perform XY axis scanning in order to achieve 3D data in given FOV (Field of View) through spot scanning. We propose a method to improve a parallel mode confocal system using a micro-lens and pin-hole array to remove XY scan. 2D imaging system can detect 2D location of wire and it can reduce time to measure 3D position of wire. In the experimental results, the proposed system can measure 3D position of wire with reasonable accuracy.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.6
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• pp.3188-3207
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• 2017

In this paper, we propose an image enhancement algorithm to improve license plate extraction rate in various environments (Day Street, Night Street, Underground parking lot, etc.). The proposed algorithm is composed of image enhancement algorithm and license plate extraction algorithm. The image enhancement method can improve an image quality of the degraded image, which utilizes a histogram information and overall gray level distribution of an image. The proposed algorithm employs an interpolated probability distribution value (PDV) in order to control a sudden change in image brightness. Probability distribution value can be calculated using cumulative distribution function (CDF) and probability density function (PDF) of the captured image, whose values are achieved by brightness distribution of the captured image. Also, by adjusting the image enhancement factor of each part region based on image pixel information, it provides a function that can adjust the gradation of the image in more details. This processed gray image is converted into a binary image, which fuses narrow breaks and long thin gulfs, eliminates small holes, and fills gaps in the contour by using morphology operations. Then license plate region is detected based on aspect ratio and license plate size of the bound box drawn on connected license plate areas. The images have been captured by using a video camera or a personal image recorder installed in front of the cars. The captured images have included several license plates on multilane roads. Simulation has been executed using OpenCV and MATLAB. The results show that the extraction success rate is more improved than the conventional algorithms.

• Journal of Digital Convergence
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• v.13 no.12
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• pp.203-208
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• 2015

Image degradation will occur depending on hardware characteristics according to the lapse of time between beam projectors when multivision system is installed in the Theme park/Exhibition/Science Museum. In this paper, we have researched the 10-bit High-depth and high-resolution $360^{\circ}$ projection image analysis technique to solve the problems of quality and the maintenance of the theater. The goal is to minimize the economic losses and the development of special theater calibration system that can efficiently support a quality of an image. We proposed the method of image analysis technology, and explained the detailed functions and evaluation methods for image analysis technique. Evaluation method included the performance items, and proposed reasonable value to the experimental method and the goal value.

• Journal of Multimedia Information System
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• v.4 no.4
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• pp.195-204
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• 2017

Mobile robots are used for years as a valuable research and educational tool in form of available open-platform designs and Do-It-Yourself kits. Rapid development and costs reduction of Unmanned Air Vehicles (UAV) and ground based mobile robots in recent years allowed researchers to utilize them as an affordable research platform. Despite of recent developments in the area of ground and airborne robotics, only few examples of Unmanned Surface Vehicle (USV) platforms targeted for research purposes can be found. Aim of this paper is to present the development of open-design USV drone with integrated multi-level control hardware architecture. Proposed catamaran - type water surface drone enables direct control over wireless radio link, separate development of algorithms for optimal propulsion control, navigation and communication with the ground-based control station. Whole design is highly modular, where each component can be replaced or modified according to desired task, payload or environmental conditions. Developed USV is planned to be utilized as a part of the system for detection and identification of marine and lake waste. Cameras mounted to the USV would record sea or lake surfaces, and recorded video sequences and images would be processed by state-of-the-art computer vision and machine learning algorithms in order to identify and classify marine and lake waste.

• Journal of Technology Innovation
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• v.22 no.4
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• pp.89-116
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• 2014

Socially-oriented R&D programs aimed at solving societal problem rather than scientific and industrial fruits have started recently. Societal problem is recognized as dilemma since this problem related to various stakeholders. And this is not solved with single program and needed long-term process. So the perspective of socio-technical system transition including technological and institutional change is needed. This paper suggests policy implication of Socially-oriented R&D programs from socio-technical system transition perspective. 'Transitioning of Socially-oriented R&D program' is the key concept of restructuring the program for the system transition. The establishment of multi-layer transition governance and the transition vision-making and transition experiment planning are the key process of transitioning the R&D program. This paper suggests the ways and issues of implementing this process in Socially-oriented R&D program.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.4
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• pp.86-101
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• 2019

Remote sensing technology has been continuously developed both quantitatively and qualitatively, including platform development, exploration area, and exploration functions. Recently, the use cases and related researches in the agricultural field are increasing. Also, since it is possible to detect and quantify the condition of cropland and establish management plans and policy support for cropland and agricultural environment, it is being studied in various fields such as crop growth abnormality determination and crop estimation based on time series information. The purpose of this study was to analyze the vegetation index for agricultural land reclamation area using a UAV equipped with a multi-spectral sensor. In addition, field surveys were conducted to evaluate the accuracy of vegetation indices calculated from multispectral image data obtained using UAV. The most appropriate vegetation index was derived by evaluating the correlation between vegetation index calculated by field survey and vegetation index calculated from UAV multispectral image, and was used to analyze vegetation index of the entire area.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.3
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• pp.513-520
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• 2020

Recently, the development of a vision inspection system using machine learning has become more active. This study seeks to develop a defect inspection model using machine learning. Defect detection problems for images correspond to classification problems, which are the method of supervised learning in machine learning. In this study, defect detection models are developed based on algorithms that automatically extract features and algorithms that do not extract features. One-dimensional CNN and two-dimensional CNN are used as algorithms for automatic extraction of features, and MLP and SVM are used as algorithms for non-extracting features. A defect detection model is developed based on four models and their accuracy and AUC compare based on AUC. Although image classification is common in the development of models using CNN, high accuracy and AUC is achieved when developing SVM models by converting pixels from images into RGB values in this study.