• Annual Conference of KIPS
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• 2006.05a
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• pp.415-418
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• 2006

다양한 데이터에 대해 정확한 분석이 요구되는 분야가 증가하면서, 데이터를 효율적으로 가시화하는 방법에 대한 요구도 증가하고 있다. 분석에 효율적인 가시화란 데이터의 특성을 잘 표현함으로써 분석가가 데이터를 직관적으로 이해할 수 있도록 도와주는 것을 말한다. 이를 통해 데이터를 분석하는 시간을 줄이고 정확한 결과를 얻는데 도움을 준다. 본 논문에서는 가스 배관을 검사하기 위한 Geometry 피그（PIG:Pipeline Inspection Gauge)와 MFL 피그로부터 얻어지는 데이터를 다양한 방법으로 가시화하고 분석에 효과적인 가시화와 시스템의 구현에 대해 다룬다. 각 피그의 다중 센서를 통해 얻어온 데이터를 Line graph, Pseudo Color Image, 3D Surface, Polar View, 3D Pipeline View와 같은 다양한 방법으로 가시화하고 view들 간의 동기화 및 사용자 지정 view 배치를 통해 빠르고 정확한 분석을 가능하게 하는 여러 가지 방법에 대해 설명한다.

• Transactions on Electrical and Electronic Materials
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• v.5 no.4
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• pp.133-137
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• 2004

The development of digital x-ray detector has been extensively progressed for the application of various medical modalities. In this study, we introduce a new hybrid-type x-ray detector to improve problems of a conventional direct or indirect digital x-ray image technology, which composed of multi-layer structure using a CaWO$_4$ phosphor and amorphous selenium (a-Se) photoconductor. The leakage current of our detector was found to be ∼180 pA/cm$^2$ at 10 V/m, which was significantly reduced than that of a single a-Se detector. The x-ray sensitivity was measured as the value of 4230 pC/cm$^2$/mR at 10 V/m. We found that the parylene thin film between a CaWO$_4$ phosphor and an a-Se layer acts as an insulator to prevent charge injection from indium thin oxide (ITO) electrode into an a-Se layer under applied bias.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.3
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• pp.287-292
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• 2003

The ability of robot is being various and complex. The robot is utilizing distance, image data and voice data for sensing its circumstance. This paper suggests the 2-layer fuzzy control as the algorithm that control robot with various sensor information. In a obstacle avoidance, it utilizes many range finders and classifies them into 3parts(front, left, right). In 3 sub-controllers, the controller executes fuzzy conference. And then it executes combined control with a combination of outputs of 3 sub-controllers in the second step. The text compares the 2-layer fuzzy controller with the hierarchical fuzzy controller that has analogous structure. And the performance of the 2-layer fuzzy controller is confirmed by application this controller to robot following, simulation to each other and real experiment.

• Journal of Satellite, Information and Communications
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• v.9 no.4
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• pp.26-31
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• 2014

In this paper, we present performance analysis of video smoke detection based on BPN-Network that is using multi-smoke feature, and Neural Network. Conventional smoke detection method consist of simple or mixed functions using color, temporal, spatial characteristics. However, most of all, they don't consider the early fire conditions. In this paper, we analysis the smoke color and motion characteristics, and revised distinguish the candidate smoke region. Smoke diffusion, transparency and shape features are used for detection stage. Then it apply the BPN-Network (Back-Propagation Neural Network). The simulation results showed 91.31% accuracy and 2.62% of false detection rate.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.5
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• pp.397-402
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• 2019

Recently, with the emergence of autonomous vehicles and the increasing interest in safety, a variety of research has been being actively conducted to precisely estimate the position of a vehicle by fusing sensors. Previously, researches were conducted to determine the location of moving objects using GNSS (Global Navigation Satellite Systems) and/or IMU (Inertial Measurement Unit). However, precise positioning of a moving vehicle has lately been performed by fusing data obtained from various sensors, such as LiDAR (Light Detection and Ranging), on-board vehicle sensors, and cameras. This study is designed to enhance kinematic vehicle positioning performance by using feature-based recognition. Therefore, an analysis of the required precision of the observations obtained from the images has carried out in this study. Velocity and attitude observations, which are assumed to be obtained from images, were generated by simulation. Various magnitudes of errors were added to the generated velocities and attitudes. By applying these observations to the positioning algorithm, the effects of the additional velocity and attitude information on positioning accuracy in GNSS signal blockages were analyzed based on Kalman filter. The results have shown that yaw information with a precision smaller than 0.5 degrees should be used to improve existing positioning algorithms by more than 10%.

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.262-266
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• 1999

Several commercial companies that plan to provide improved panchromatic and/or multi-spectral remote sensor data in the near future are suggesting that merge datasets will be of significant value. This study evaluated the utility of one major merging process-process components analysis and its inverse. The 6 bands of 30$\times$30m Landsat TM data and the 10$\times$l0m SPOT panchromatic data were used to create a new 10$\times$10m merged data file. For the image classification, 6 bands that is 1st, 2nd, 3rd, 4th, 5th and 7th band may be used in conjunction with supervised classification algorithms except band 6. One of the 7 bands is Band 6 that records thermal IR energy and is rarely used because of its coarse spatial resolution (120m) except being employed in thermal mapping. Because SPOT panchromatic has high resolution it makes 10$\times$10m SPOT panchromatic data be used to classify for the detailed classification. SPOT as the Landsat has acquired hundreds of thousands of images in digital format that are commercially available and are used by scientists in different fields. After the merged, the classifications used supervised classification and neural network. The method of the supervised classification is what used parallelepiped and/or minimum distance and MLC(Maximum Likelihood Classification) The back-propagation in the multi-layer perception is one of the neural network. The used method in this paper is MLC(Maximum Likelihood Classification) of the supervised classification and the back-propagation of the neural network. Later in this research SPOT systems and images are compared with these classification. A comparative analysis of the classifications from the TM and merged SPOT/TM datasets will be resulted in some conclusions.

• Journal of Broadcast Engineering
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• v.23 no.5
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• pp.598-605
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• 2018

Behavior awareness is a technology that recognizes human behavior through data and can be used in applications such as risk behavior through video surveillance systems. Conventional behavior recognition algorithms have been performed using the 2D camera image device or multi-mode sensor or multi-view or 3D equipment. When two-dimensional data was used, the recognition rate was low in the behavior recognition of the three-dimensional space, and other methods were difficult due to the complicated equipment configuration and the expensive additional equipment. In this paper, we propose a method of recognizing human behavior using only CCTV images without additional equipment using only RGB and depth information. First, the skeleton extraction algorithm is applied to extract points of joints and body parts. We apply the equations to transform the vector including the displacement vector and the relational vector, and study the continuous vector data through the RNN model. As a result of applying the learned model to various data sets and confirming the accuracy of the behavior recognition, the performance similar to that of the existing algorithm using the 3D information can be verified only by the 2D information.

• Proceedings of the KSRS Conference
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• v.2
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• pp.590-593
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• 2006

Timber inventory management includes to measure and update forest attributes, which is crucial information for private companies and public organizations in property assessment and environment monitoring. Field measurement would be accurate, but time-consuming and inefficient. For the reason, remote sensing technology has been an alternative to field measurement from an economic perspective. Among several sensors, LiDAR and Radar interferometry are known for their efficiency for forest monitoring because they are less influenced by weather and light conditions, and provide reasonably accurate vertical/horizontal measurement for a large area in a short period. For example, Shuttle Radar Topography Mission (SRTM) and National Elevation Dataset (NED) in the U.S. can provide tree height information and DSM. On the other hand, LiDAR DSM (the first return) and DEM (the last return) can also present tree height estimation. With respect to project site of loblolly pine plantation in Louisiana in the U.S., the accuracy of SRTM C-Band approach estimating tree height was assessed by the LiDAR approaches. In addition, SRTM X-Band and NED were also compared with the results. Plantation year in inventory GIS, which is directly related to forest age, is high correlated with the difference between SRTM C-Band and NED. As a byproduct, several stands of age mismatch could be recognized using an outlier detection algorithm, and optical satellite image (ETM+) were used to verify the mismatch. The findings of this study were (1) the confirmation of usefulness of the SRTM DSM for forest monitoring and (2) Multi-sensors- Radar, LiDAR, ETM+, MODIS can be used for accuracy improvement of forest inventory GIS altogether.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2002.11a
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• pp.416-419
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• 2002

There are being two prominent studying for Digital Radiography. Direct and Indirect method of Digital Radiography are announced for producing high quality digital image. The one is using amorphous selenium as photoconductor and the other is using phosphor layer as a light conversion. But each two systems have strength and weakness such as high voltage and blurring effect. In this study, we investigated the electrical characteristic of $multi-layer\left(CaWO_{4}+a-Se \right)$ as a photoconductor according to the changing arsenic composition ratio. This is a basic research for developing of Hybrid digital radiography which is a new type X-ray detector. The arsenic composition ratio of a-Se compound is classified into 7 different kinds which have 0.1%, 0.3%, 0.5%, 1%, 1.5%, 5%, 10% and were made test sample throught thermo-evaporation. The phosphor layer of $CaWO_4$ was overlapped on a-Se using EFIRON optical adhesives. We measured the dark and photo current about the test sample and compared the electrical characteristic of the net charge and signal-to-noise ratio. Among other things, test sample of compound material of 0.3% arsenic showed good characteristic of $2.45nA/cm^2$ dark current and $357.19pC/cm^2/mR$ net charge at $3V/{\mu}m$.

• 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.