• 한국통신학회논문지
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• 제24권8B호
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• pp.1490-1499
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• 1999

본 논문에서는 필기숫자의 형태와 FSOM을 이용한 새로운 필기숫자 인식 알고리즘을 제안한다. 제안한 알고리즘은 비슷한 형태를 가지는 숫자는 같은 그룹으로 분류된다는 사실에 기초한 알고리즘으로, 필기숫자의 외접선에 의한 형태결정과 템플레이트 매칭을 이용하여 필기숫자 데이터를 여러 개의 그룹으로 분할하고 분할된 각 그룹별로 인식 알고리즘을 적용한다. 본 실험에서는 필기숫자의 데이터를 16개의 그룹으로 분류하였으며, 분류된 그룹별로 각각의 특징추출과 SOM의 단점을 보완한 FSOM을 적용하였다. 분할된 16개의 FSOM은 각 그룹별로 독립적인 학습이 가능한 특징뿐만 아니라 한 그룹씩 단계적으로 학습을 할 수 있는 장점이 있다. 제안한 알고리즘의 성능을 입증하기 위해서 Concordia 대학의 필기 숫자 데이터를 사용하여 실험하였다.

• 센서학회지
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• 제14권2호
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• pp.116-124
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• 2005

In this paper range measurement systems are designed using an ultrasonic sensor and a camera. An ultrasonic sensor provides the range measurement to a target quickly and simply but its low resolution is a disadvantage. We tackle this problem by employing a camera. Instead using a stereoscopic sensor, which is widely used for 3D sensing but requires a computationally intensive stereo matching, the range is measured by focusing and structured lighting. In focusing a straightforward focusing measure named as MMDH(min-max difference in histogram) is proposed and compared with existing techniques. In the method of structure lighting, light stripes projected by a beam projector are used. Compared to those using a laser beam projector, the designed system can be constructed easily in a low-budget. The system equation is derived by analysing the sensor geometry. A sensing scenario using the systems designed is in two steps. First, when better accuracy is required, measurements by ultrasonic sensing and focusing of a camera are fused by MLE(maximum likelihood estimation). Second, when the target is in a range of particular interest, a range map of the target scene is obtained by using structured lighting technique. The systems designed showed measurement accuracy up to 0.3[mm] approximately in experiments.

• 한국자동차공학회논문집
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• 제22권7호
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• pp.107-116
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• 2014

This paper presents camera-based road surface marking detection methods suited to sensor fusion-based positioning system that consists of low-cost GPS (Global Positioning System), INS (Inertial Navigation System), EDM (Extended Digital Map), and vision system. The proposed vision system consists of two parts: lane marking detection and RSM (Road Surface Marking) detection. The lane marking detection provides ROIs (Region of Interest) that are highly likely to contain RSM. The RSM detection generates candidates in the regions and classifies their types. The proposed system focuses on detecting RSM without false detections and performing real time operation. In order to ensure real time operation, the gating varies for lane marking detection and changes detection methods according to the FSM (Finite State Machine) about the driving situation. Also, a single template matching is used to extract features for both lane marking detection and RSM detection, and it is efficiently implemented by horizontal integral image. Further, multiple step verification is performed to minimize false detections.

• 로봇학회논문지
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• 제13권4호
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• pp.230-236
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• 2018

3D depth perception has played an important role in robotics, and many sensory methods have also proposed for it. As a photodetector for 3D sensing, single photon avalanche diode (SPAD) is suggested due to sensitivity and accuracy. We have researched for applying a SPAD chip in our fusion system of time-of-fight (ToF) sensor and stereo camera. Our goal is to upsample of SPAD resolution using RGB stereo camera. Currently, we have 64 x 32 resolution SPAD ToF Sensor, even though there are higher resolution depth sensors such as Kinect V2 and Cube-Eye. This may be a weak point of our system, however we exploit this gap using a transition of idea. A convolution neural network (CNN) is designed to upsample our low resolution depth map using the data of the higher resolution depth as label data. Then, the upsampled depth data using CNN and stereo camera depth data are fused using semi-global matching (SGM) algorithm. We proposed simplified fusion method created for the embedded system.

• 천문학회보
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• 제44권1호
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• pp.69.3-69.3
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• 2019

The CHIMPS2 survey is to extend the JCMT HARP $^{13}CO/C^{18}O$ J=3-2 Inner Milky-Way Plane Survey (CHIMPS) and the ${12}^CO$ J=3-2 survey (COHRS) into the inner Galactic Plane, the Central Molecular Zone (CMZ), and a section of the Outer Plane. When combined with the complementary $^{12}CO/^{13}CO/C^{18}O$ J=1-0 survey at the Nobeyama 45m (FUGIN) at matching 15" resolution and sensitivity, and other current CO surveys, the results will provide a complete set of transition data with which to calculate accurate column densities, gas temperatures and turbulent Mach numbers. These will be used to: analyze molecular cloud properties across a range of Galactic environments; map the star-formation efficiency (SFE) and dense-gas mass fraction (DGMF) in molecular gas as a function of position in the Galaxy and its relation to the nature of the turbulence within molecular clouds; determine Galactic structure as traced by molecular gas and star formation; constrain cloud-formation models; study the relationship of filaments to star formation; test current models of the gas kinematics and stability in the Galactic center region and the flow of gas from the disc. It will also provide an invaluable legacy data set for JCMT that will not be superseded for several decades. In this poster, we will present the current status of the CHIMPS2.

• 한국BIM학회 논문집
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• 제10권1호
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• pp.1-8
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• 2020

In managing building facilities, spatial information is the basic data for decision making. However, the method of acquiring spatial information is not easy. In many cases, the site and drawings are often different due to changes in facilities and time after construction. In this case, the site data should be scanned to obtain spatial information. The scan data actually contains spatial information, which is a great help in making space related decisions. However, to obtain scan data, an expensive LiDAR (Light Detection and Ranging) device must be purchased, and special software for processing data obtained from the device must be available.Recently, SLAM (Simultaneous localization and mapping), an advanced map generation technology, has been spreading in the field of robotics. Using SLAM, 3D spatial information can be obtained quickly in real time without a separate matching process. This study develops and tests whether SLAM technology can be used to obtain spatial information for facility management. This draws considerations for developing a SLAM device for real-time remote scanning for facility management. However, this study focuses on the system development method that acquires spatial information necessary for facility management through SLAM technology. To this end, we develop a prototype, analyze the pros and cons, and then suggest considerations for developing a SLAM system.

• 로봇학회논문지
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• 제16권3호
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• pp.179-188
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• 2021

Construction monitoring is one of the key modules in smart construction. Unlike structured urban environment, construction site mapping is challenging due to the characteristics of an unstructured environment. For example, irregular feature points and matching prohibit creating a map for management. To tackle this issue, we propose a system for data acquisition in unstructured environment and a framework for Intensity and Ambient Enhanced Lidar Inertial Odometry via Smoothing and Mapping, IA-LIO-SAM, that achieves highly accurate robot trajectories and mapping. IA-LIO-SAM utilizes a factor graph same as Tightly-coupled Lidar Inertial Odometry via Smoothing and Mapping (LIO-SAM). Enhancing the existing LIO-SAM, IA-LIO-SAM leverages point's intensity and ambient value to remove unnecessary feature points. These additional values also perform as a new factor of the K-Nearest Neighbor algorithm (KNN), allowing accurate comparisons between stored points and scanned points. The performance was verified in three different environments and compared with LIO-SAM.

• 로봇학회논문지
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• 제19권2호
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• pp.149-158
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• 2024

This paper presents a robust autonomous navigation and reconnaissance system for tracked robots, designed to handle complex multi-floor indoor environments with stairs. We introduce a localization algorithm that adjusts scan matching parameters to robustly estimate positions and create maps in environments with scarce features, such as narrow rooms and staircases. Our system also features a path planning algorithm that calculates distance costs from surrounding obstacles, integrated with a specialized PID controller tuned to the robot's differential kinematics for collision-free navigation in confined spaces. The perception module leverages multi-image fusion and camera-LiDAR fusion to accurately detect and map the 3D positions of objects around the robot in real time. Through practical tests in real settings, we have verified that our system performs reliably. Based on this reliability, we expect that our research team's autonomous reconnaissance system will be practically utilized in actual disaster situations and environments that are difficult for humans to access, thereby making a significant contribution.

• 도시과학
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• 제12권2호
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• pp.43-52
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• 2023

UAV have the disadvantage that are weak from rainfall or winds due to the light platform, so use Scale-Invariant Feature Transform (SIFT) method which extrude keypoints in image matching process. To find the efficient filtering method for the construction of precise Digital Terrain Model (DTM) using UAV images, comparatively analyzed sobel and Differential of Gaussian (DoG) and found sobel is more efficient way to extrude buildings, trees, and so on. And edges are extruded more clearly when applying median additionally which have the merit of preserving edge and eliminating noise. In this study, applied sobel-median filtering which plus median to sobel and constructed the 1st filtered DTM that extrude building and trees and 2nd filtered DTM that extrude cars by threshold of gradient, Analysis of the degree of accuracy improvement showed that standard deviations of 1st filtered DTM and 2nd filtered DTM are 0.32m, 0.287m respectively, and both are acceptable for the tolerance of 0.33m for elevation points of 1/1,000 digital map, and the accuracy was increased about 10% by filtering automobiles. Plus, moving things are changed those position and direction in every image, and these are not target to filter because of the characteristic that is excluded from SIFT method.

• 한국지역지리학회지
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• 제3권2호
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• pp.19-35
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• 1997

본 연구는 최근 지리학에서 많이 이용되고 있는 GIS를 지형분석에 적응하기 위하여 한반도의 남해안에 위치하는 거제도를 해상으로 지형 및 하계망의 특성 및 지질과 지형, 지질과 하계망, 지형과 하계망과의 관련성을 GIS를 이용하여 분석한 것으로 상용 Data인 DTED와 지형도상의 Data를 같이 사용하고 이를 비교하여 봄으로써 장차 지형분석에 GIS의 이용 가능성과 DTED를 이용한 지형 및 하계분석의 가능성을 평가하고자 한다. 거제도의 자연 환경을 지형도 Data와 DTED를 이용 GIS Tool로 분석하여 그 결과를 비교한 결과 GIS Tool로 지형분석에는 문제가 없었으나 GIS자체가 지형분석을 위해 만들어진 Tool이 아니기 때문에 방법상의 문제가 제기되었다. 또한 지형도상의 Data와 DTED의 분석결과를 비교한 결과 DTED가 지형도 Data에 비해 정밀도가 떨어지고 좌표상의 오차가 발생하였다. 이러한 문제가 있기는 하나 접근이 불가능한 지역이나 넓은 지역을 대상으로 한 분석에서는 DTED가 유용한 자료로 사용될 수 있다.