• Journal of Drive and Control
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• v.21 no.2
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• pp.53-64
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• 2024

Global population growth has resulted in an increased demand for food production. Simultaneously, aging rural communities have led to a decrease in the workforce, thereby increasing the demand for automation in agriculture. Drones are particularly useful for unmanned pest control fields. However, the current method of uniform spraying leads to environmental damage due to overuse of pesticides and drift by wind. To address this issue, it is necessary to enhance spraying performance through precise performance evaluation. Therefore, as a foundational study aimed at optimizing drone-based pest control technologies, this research evaluated water-sensitive paper (WSP) via density map estimation using convolutional neural networks (CNN) with a encoder-decoder structure. To achieve more accurate estimation, this study implemented multi-task learning, incorporating an additional classifier for image segmentation alongside the density map estimation classifier. The proposed model in this study resulted in a R-squared (R²) of 0.976 for coverage area in the evaluation data set, demonstrating satisfactory performance in evaluating WSP at various density levels. Further research is needed to improve the accuracy of spray result estimations and develop a real-time assessment technology in the field.

• The Journal of the Korea Contents Association
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• v.14 no.11
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• pp.558-574
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• 2014

The number of fatty liver patients is sharply growing due to the rapid increase in the incidence of metabolic syndrome, which can lead to diseases such as abdominal obesity, hypertension, diabetes, and hyperlipidemia. Early diagnosis requires examinations using magnetic resonance imaging (MRI), wherein quantitative analyses are implemented through a professional water-fat separation method in many cases, as the intensity values of the areas of interest and non-interest are considerably similar or the same. However, such separation method generates inaccurate results in high magnetic fields, where the inhomogeneity of the fields increases. To overcome the limits of such conventional fat quantification methods, this paper proposes a field map estimation method that is effective in high magnetic fields. This method generates field maps through echo images that are obtained using the existing IDEAL sequences, and considers the wrapping degree of the field maps. Then clustering is performed to separate calibration areas, the least square fits based on the region growing method schema of the separated calibration areas, and the histograms are adjusted to separate the water from the fats. In experiment results, our proposed method had a superior fat detection rate of an average of 86.4%, compared to the ideal method with an average of 61.5% and Yu's method with an average of 62.6%. In addition, it was confirmed that the proposed method had a more accurate water detection rate of 98.4% on the average than the 88.6% average of the fat saturation method.

• Journal of the Korea Institute of Military Science and Technology
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• v.15 no.2
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• pp.169-176
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• 2012

GPS(Global Positioning System) is widely used for the position estimation of an aerial vehicle. However, GPS may not be available due to hostile jamming or strategic reasons. A vision-based position estimation method can be effective if GPS does not work properly. In mountainous areas without any man-made landmark, a horizon is a good feature for estimating the position of an aerial vehicle. In this paper, we present a new method to estimate the position of the aerial vehicle equipped with a forward-looking infrared camera. It is assumed that INS(Inertial Navigation System) provides the attitudes of an aerial vehicle and a camera. The horizon extracted from an infrared image is compared with horizon models generated from DEM(Digital Elevation Map). Because of a narrow field of view of the camera, two images with a different camera view are utilized to estimate a position. The algorithm is tested using real infrared images acquired on the ground. The experimental results show that the method can be used for estimating the position of an aerial vehicle.

• Spatial Information Research
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• v.15 no.1
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• pp.81-94
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• 2007

Even though the data of digital cadastral map, stored in the Korea Land Information System(hereinafter referred to as "KLIS") has a wide variety of errors, it has been used in a cadastral surveying field without any compensating work. As a result, it has given rise to a lot of problems when we use this digital cadastral map in the cadastral surveying field. That is why we should analyse the accuracy of digital cadastral map which has been stored in the KLIS. In this context, this paper has been intended to provide acceptable proposals with regards to present operation of KLIS or the cadastral re-survey project in the future by analysing the data of digital cadastral map which is one of the layers of the KLIS. Our study results showed that the accuracy of both the location and area in the present KLIS datum was not satisfactory Therefore, in our own judgment, it is necessary to revise cadastral maps more accurately in order to use in the field of cadastral surveying or in carrying out the cadastral re-survey project.

• IEIE Transactions on Smart Processing and Computing
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• v.2 no.5
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• pp.317-321
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• 2013

This paper proposes a detection algorithm for view reversal in a stereoscopic video using a disparity map and motion vector field. We obtain the disparity map of a stereo image was obtained using a specific stereo matching algorithm and classify the image into the foreground and background. Next, the motion vector field of the image on a block basis was produced using a full search algorithm. Finally, the stereo image was considered to be reversed when the foreground moved toward the background and the covered region was in the foreground. The proposed algorithm achieved a good detection rate when the background was covered sufficiently by its moving foreground.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.49 no.2
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• pp.69-75
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• 2012

This paper presents a novel de-interlacing algorithm that can make up motion compensation errors by using maximum a posteriori (MAP) estimator. First, a proper registration is performed between a current field and its adjacent fields, and the progressive frame corresponding to the current field is found via MAP estimator based on the computed registration information. Here, in order to obtain a stable solution, well-known bilateral total variation (BTV)-based regularization is employed. Next, so-called feathering artifacts are detected on a block basis effectively. So, edge-directional interpolation is applied to the pixels where feathering artifact may happen, instead of the above-mentioned temporal de-interlacing. Experimental results show that the PSNR of the proposed algorithm is on average 4dB higher than that of previous studies and provides the better subjective quality than the previous works.

• Korean Journal of Remote Sensing
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• v.25 no.3
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• pp.295-309
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• 2009

In this study, an iterative maximum a posteriori (MAP) approach using a Bayesian model of Markovrandom field (MRF) was proposed for despeckling images that contains speckle. Image process is assumed to combine the random fields associated with the observed intensity process and the image texture process respectively. The objective measure for determining the optimal restoration of this "double compound stochastic" image process is based on Bayes' theorem, and the MAP estimation employs the Point-Jacobian iteration to obtain the optimal solution. In the proposed algorithm, MRF is used to quantify the spatial interaction probabilistically, that is, to provide a type of prior information on the image texture and the neighbor window of any size is defined for contextual information on a local region. However, the window of a certain size would result in using wrong information for the estimation from adjacent regions with different characteristics at the pixels close to or on boundary. To overcome this problem, the new method is designed to use less information from more distant neighbors as the pixel is closer to boundary. It can reduce the possibility to involve the pixel values of adjacent region with different characteristics. The proximity to boundary is estimated using a non-uniformity measurement based on standard deviation of local region. The new scheme has been extensively evaluated using simulation data, and the experimental results show a considerable improvement in despeckling the images that contain speckle.

• Journal of Biosystems Engineering
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• v.34 no.4
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• pp.278-285
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• 2009

Navigation system is applied in variety of fields including the simple location positioning, autopilot navigation of unmanned robot tractor, autonomous guidance systems for agricultural vehicles, construction of large field works that require high precision and map making process. Particularly utilization of GPS (Global Positioning System) is very common in the present navigation system. This study introduces a navigation system for autonomous field robot that travels to the pre-input path using GPS information. Performance of the GPS- based navigation is highly depended on its receiving rate because GPS receivers do not acquire any navigation information in the period between the refresh intervals. So this study presents an algorithm that improves an accuracy of the navigation by estimation the positional information during the blind period of a low rate GPS receiver. In fact the algorithm calculated the robot's heading in a 50 Hz rate, so the blind period of an 1 Hz GPS receiver is extensively covered. Consequently implementation of the algorithm to the GPS based navigation showed an improvement in guidance accuracy. The conventional field robot directly carried an expensive control computer and sensors onboard, therefore the miniaturization and weight reduction of the robot was limited. In this paper, the field robot carried only communication equipments such as GPS module, normal RC receiver, and bluetooth modem. This enabled the field robot to be built in an economic cost and miniature size.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.31 no.1
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• pp.79-87
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• 2013

This study proposed a method to analyze the economic benefit of the national map revision program using the replacement cost method. The replacement cost method measures the benefit of a project as the minimum cost to replace functions of the project with those of alternative goods or services in an existing market. Thus, the demands on 1/5,000 topographic map revision in 18 administrative tasks such as city and district management planning were surveyed in three local autonomous entities. Then the cost to alternatively fulfill the demands was estimated with the standard construction estimating system for the field surveying and surveying results in commercial GIS companies for the site investigation. With this cost estimation model, the benefit of the current national map revision program to the local autonomous entities was estimated as 265,960,999 won. And cost benefit ratios according to several revision frequencies from 0.5 to 4 year were also compared to find the optimal frequency.

• Journal of Forest and Environmental Science
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• v.33 no.3
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• pp.187-196
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• 2017

The use of unmanned aerial vehicles (UAV) for the estimation of tree height is gaining recognition. This study aims to assess the effectiveness of tree height estimation of Pinus densiflora Sieb. et Zucc. and Pinus koraiensis Sieb. et Zucc. using digital surface model (DSM) generated from UAV-acquired imageries. Images were taken with the $Trimble^{(R)}$ UX5 equipped with Sony ${\alpha}5100$. The generated DSM, together with the digital elevation model (DEM) generated from a digital map of the study areas, were used in the estimation of tree height. Field measurements were conducted in order to generate a regression model and carry out accuracy assessment. The obtained coefficients of determination (R2) and root mean square error (RMSE) for P. densiflora (R2=0.71; RMSE=1.00 m) and P. koraiensis (R2=0.64; RMSE=0.85 m) are comparable to the results of similar studies. The results of the paired two-tailed t-test show that the two tree height estimation methods are not significantly different (p-value=0.04 and 0.10, alpha level=0.01), which means that tree height estimation using UAV imagery could be used as an alternative to field measurement.