• Journal of the Korea Computer Graphics Society
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• v.21 no.1
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• pp.1-11
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• 2015

Researchers have developed virtual reality environments to provide audience with more visually immersive experiences than previously possible. One of the most popular solutions to build the immersive VR space is a multi-projection technique. However, utilization of multiple projectors requires large spaces, expensive cost, and accurate geometry calibration among projectors. This paper presents a novel omnidirectional projection system with a single projector and a single spherical mirror.We newly designed the simple and intuitive calibration system to define the shape of environment and the relative position of mirror/projector. For successful image projection, our optimized omnidirectional image generation step solves image distortion produced by the spherical mirror and a calibration problem produced by unknown parameters such as the shape of environment and the relative position between the mirror and the projector. Additionally, the focus correction is performed to improve the quality of the projection. The experiment results show that our method can generate the optimized image given a normal panoramic image for omnidirectional projection in a rectangular space.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.6
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• pp.749-754
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• 2011

In this study, we propose the design of optimized pRBFNNs-based face recognition system using two-dimensional Image and ASM algorithm. usually the existing 2 dimensional face recognition methods have the effects of the scale change of the image, position variation or the backgrounds of an image. In this paper, the face region information obtained from the detected face region is used for the compensation of these defects. In this paper, we use a CCD camera to obtain a picture frame directly. By using histogram equalization method, we can partially enhance the distorted image influenced by natural as well as artificial illumination. AdaBoost algorithm is used for the detection of face image between face and non-face image area. We can butt up personal profile by extracting the both face contour and shape using ASM(Active Shape Model) and then reduce dimension of image data using PCA. The proposed pRBFNNs consists of three functional modules such as the condition part, the conclusion part, and the inference part. In the condition part of fuzzy rules, input space is partitioned with Fuzzy C-Means clustering. In the conclusion part of rules, the connection weight of RBFNNs is represented as three kinds of polynomials such as constant, linear, and quadratic. The essential design parameters (including learning rate, momentum coefficient and fuzzification coefficient) of the networks are optimized by means of Differential Evolution. The proposed pRBFNNs are applied to real-time face image database and then demonstrated from viewpoint of the output performance and recognition rate.

• The KIPS Transactions:PartD
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• v.17D no.1
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• pp.1-8
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• 2010

Association rule mining techniques enable us to acquire knowledge concerning sales patterns among individual items from voluminous transactional data. Certainly, one of the major purposes of association rule mining is utilizing the acquired knowledge to provide marketing strategies such as catalogue design, cross-selling and shop allocation. However, this requires too much time and high cost to only extract the actionable and profitable knowledge from tremendous numbers of discovered patterns. In currently available literature, a number of interest measures have been devised to accelerate and systematize the process of pattern evaluation. Unfortunately, most of such measures, including support and confidence, are prone to yielding impractical results because they are calculated only from the sales frequencies of items. For instance, traditional measures cannot differentiate between the purchases in a small basket and those in a large shopping cart. Therefore, some adjustment should be made to the size of market baskets because there is a strong possibility that mutually irrelevant items could appear together in a large shopping cart. Contrary to the previous approaches, we attempted to consider market basket's size in calculating interest measures. Because the devised measure assigns different weights to individual purchases according to their basket sizes, we expect that the measure can minimize distortion of results caused by accidental patterns. Additionally, we performed intensive computer simulations under various environments, and we performed real case analyses to analyze the correctness and consistency of the devised measure.

• The Journal of Engineering Geology
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• v.16 no.4 s.50
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• pp.337-349
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• 2006

Seven hundred and fifty one fractures of the rhyolitic tuffaceous rock masses were mapped using 6 scanlines placed on rock slope exposures that were within 8.02 km of Busan-Ulsan highway. These data were analyzed to find the number of fracture sets that exist in the rock slopes and the probability distributions of orientation, spacing, trace length and fracture size in 3-D for each of the fracture sets. All the fracture set orientation distributions exhibit high variability. The Fisher distributions were found to be unsuitable to represent the statistical distribution of orientation for most of the fracture sets. The probability distributions, gamma, exponential and lognormal were found to be highly suitable to represent the distribution of spacing and semi-trace length of fracture sets. In obtain-ing these distributions, corrections were applied for sampling biases associated with spacing and trace length. The generated fracture system in 3-D was used to make predictions of fracture traces for each fracture set on 2-D win-dows. Developed stochastic 3-D fracture network for the rock mass was validated by comparing statistical proper-ties of the observed fracture traces on scanlines with the predicted fracture traces on the scanlines. This exercise fumed out to be successful.

• KIPS Transactions on Software and Data Engineering
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• v.1 no.2
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• pp.103-108
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• 2012

Recently, as the prevalence of high-performance mobile devices and the application of the multimedia content are expanded, Super Resolution (SR) technique which reconstructs low resolution images to high resolution images is becoming important. And in the mobile devices, the development of the SR algorithm considering the operation quantity or memory is required because of using the restricted resources. In this paper, we propose a new single frame fast SR technique suitable for mobile devices. In order to prevent color distortion, we change RGB color domain to HSV color domain and process the brightness information V (Value) considering the characteristics of human visual perception. First, the low resolution image is enlarged by the improved fast back projection considering the noise elimination. And at the same time, the reliable edge map is extracted by using the LoG (Laplacian of Gaussian) filtering. Finally, the high definition picture is reconstructed by using the edge information and the improved back projection result. The proposed technique removes effectually the unnatural artefact which is generated during the super resolution restoration, and the edge information which can be lost is amended and emphasized. The experimental results indicate that the proposed algorithm provides better performance than conventional back projection and interpolation methods.

• Korean Journal of Remote Sensing
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• v.37 no.5_1
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• pp.1207-1214
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• 2021

In thisletter, we developed technology which can exclude effect of cloudsto perform remote waterbody detection based on Sentinel-2 optical satellite imagery to calculate the area of ungauged reservoirs and applied to the Hwanggang dam reservoir, a representative ungauged reservoir, to verify usability. The remote waterbody detection technology calculates the cloud blocking ratio by comparing the cloud boundary in the Sentinel-2 imagery and the reservoir boundary first. Next, itselects data whose cloud blocking ratio does not exceed a specific value and calculates NDWI (Normalized Difference Water Index) with selected imagery. In last, it calculatesthe area of the reservoir by counting the number of grids which have NDWI value considered as waterbody within the boundary of the target reservoir and correcting with cloud blocking ratio. To determine cloud blocking ratio threshold forselecting image, we performed the area calculation of Hwanggang dam reservoir from July 2018 to October 2021. As a result, when the cloud blocking ratio threshold wasset 10%, we confirmed that the result with large error due to clouds were filtered well and obtained 114 results that can show changes in Hwanggang dam reservoir area among 220 images.

• The Journal of Engineering Geology
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• v.28 no.4
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• pp.701-714
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• 2018

The purpose of this study is to show the possibility of 3-dimensional modeling of open-pit limestone mine by using a rotary-wing unmanned aerial vehicle, a drone, and to estimate the amount of mining before and after mining of limestone by explosive blasting. Analysis of the image duplication of the mine has shown that it is possible to achieve high image quality. Analysis of each axis error at the shooting position after analyzing the distortions through camera calibration was shown the allowable range. As a result of estimating the amount of mining before and after explosive blasting, it was possible to estimate the amount of mining of a wide range quickly and accurately in a relatively short time. In conclusion, it is considered that the drone of a rotary-wing unmanned aerial vehicle can be usefully used for the monitoring of open-pit limestone mines and the estimation of the amount of mining. Furthermore, it is expected that this method will be utilized for periodic monitoring of construction sites and road slopes as well as open-pit mines in the future.

• Journal of the Korean Society of Radiology
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• v.15 no.4
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• pp.409-414
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• 2021

In order to acquire an image from a gamma camera, linearity correction must be performed. To this end, digital coordinates are acquired by using a linearity map to accurately specify the location where the scintillator and gamma rays interact. In this study, a method for acquiring undistorted images and digital coordinates was developed using a lookup table and maximum likelihood position estimation without using a linearity map. The proposed method was verified by configuring a small gamma camera through DETECT2000 simulation. A gamma camera was constructed using a GAGG scintillator and a SiPM optical sensor, and a gamma-ray interaction was generated at the center of the scintillator, and a lookup table was prepared using the ratio of the signals obtained from the SiPM. Through the prepared lookup table and the maximum likelihood position estimation, the position of the signal obtained by the gamma-ray interaction was acquired as digital coordinates to compose an image. As a result, the linearity was maintained compared to the generally acquired image, the accuracy of the location where the gamma-ray interaction was generated was excellent, and the distance between the locations was uniform. Since the lookup table obtained through simulation is created using the ratio of the signal, it can be directly used in the experiment, and the position of the signal can be conveniently obtained with digital coordinates with corrected linearity without creating a linearity map.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1219-1230
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• 2022

Multi-spectral drones in agricultural observation require quantitative and reliable data based on physical quantities such as radiance or reflectance in crop yield analysis. In the case of remote sensing data for crop monitoring, images taken in the same area over time-series are required. In particular, biophysical data such as leaf area index or chlorophyll are analyzed through time-series data under the same reference, it can be directly analyzed. So, comparable reflectance data are required. Orthoimagery using drone images, the entire image pixel values are distorted or there is a difference in pixel values at the junction boundary, which limits accurate physical quantity estimation. In this study, reflectance and vegetation index based on drone images were calculated according to the correction method of drone images for time-series crop monitoring. comparing the drone reflectance and ground measured data for spectral characteristics analysis.

• Journal of Korea Water Resources Association
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• v.55 no.12
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• pp.1077-1089
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• 2022

With the construction of Seoul National University (SNU), the Mt. Gwanak watershed has undergone some urbanization. As with other campus catchments, data related to the water cycle is extremely limited. Therefore, this study began by collecting hydrological and meteorological data using Atmos-41, a complex meteorological observation instrument. The observation results of Atmos-41 were validated by analyzing the statistical characteristics and confidence intervals based on the monthly variability of data from the Korea Meteorological Administration. Results of the previous research were used to validate the simulated surface runoff and infiltration using the Storm Water Management Model (SWMM). The potential evapotranspiration (PET) simulated by the SWMM was rectified by comparing it to the Atmos-41 observation data. Multiple regression analysis was employed to adjust for the fluctuations in precipitation, relative humidity, and wind speed because the calculated SWMM PET tends to be underestimated during periods of low temperatures. R² increased from 0.54 to 0.80 when compared to the Atmos-41 PET. The rate of change in the water cycle as a consequence of the SNU's construction resulted in a 15.7% increase in surface runoff, a 14.2% decrease in infiltration rate, and a 1.6% decrease in evaporation.