• Proceedings of the KIEE Conference
• /
• 2011.07a
• /
• pp.1930-1931
• /
• 2011

세계적으로 많은 연구원들이 3차원 모델링에 대하여 연구하고 있다. 특히 무인자동차의 주행을 위한 센서시스템, 경로생성, 3차원 월드모델링 방법 등에 대한 연구가 많이 진행되고 있다. 이 논문은 스테레오 카메라를 이용한 3차원 도시환경복원을 위한 방법을 제안한다. 전체적인 시스템은 다중센서(스테레오 카메라, DGPS, IMU), PC, 이동로봇(전기차)으로 구성하였다. 스테레오 카메라를 통해 들어오는 이미지는 스테레오 정합기법을 이용하여 지역좌표계의 3차원 점군을 획득하는데 이용되며, DGPS와 IMU를 통해 얻은 정보는 이동로봇의 위치를 추정하는데 이용된다. 지역좌표계의 3차원 점군과 이동로봇의 위치를 융합하면 세계좌표계의 3차원 점군을 얻을 수 있으며, 이를 이용하여 도시환경을 복원을 시행하였다. 또한 스테레오 정합기법을 통해 얻어지는 점군의 중복복원을 회피하기 위하여 임시추적을 이용한다. 임시추적을 통해 동일한 점으로 판단되는 경우 중복복원을 방지하는 알고리즘을 제안한다. 실험결과는 3차원 도시환경 복원을 수행하여 점군으로 표현하였다.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.20 no.9
• /
• pp.474-480
• /
• 2019

We propose a method to evaluate a Modulation Transfer Function (MTF) using a circular target. In addition, a MATLAB GUI-based resolution analysis tool was developed to enhance the reliability of UAV image quality and the efficiency of the work. For this purpose, images were taken with an FC-6310 during flights at altitudes of 80 m, 120 m, and 150 m and by an iXM-100 at altitudes of 150 m, 200 m, and 400 m. The MTFs of UAV images were compared with traditional photogrammetry by measuring and analyzing MTFs on images taken by the UltraCAM Eagle Mark-2 sensor at a flight altitude of 1000 m. The results show that ${\sigma}MTF$ of the FC-6310 were 0.431(80 m), 0.524(120 m), and 0.699(150 m), and those of the iXM-100 were 0.332(150 m), 0.393(200 m), and 0.631(400 m), respectively. At the altitude of 150 m, the image quality of the iXM-100, which has a high-performance camera, was very high, and the effect of the camera performance on the image quality was confirmed. In addition, the ${\sigma}MTF$ of the UltraCAM Eagle Mark-2 was 0.711 due to the high flight altitude. This was the worst value among all UAV images. However, the ${\sigma}MTF$ of the FC-6310 at 150-m altitude was 0.699, which is almost the same as that of a manned aerial image.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.23 no.3
• /
• pp.202-207
• /
• 2013

In the paper, we design a autonomous mobile robot for freight transportation and propose an operation method of the robot in the warehouse. In order to implement autonomous navigation, it is needed to recognize the position of the robot and track the path to the target. Previous methods are hard to change the workspace environment and need high cost to install and keep a maintenance of the system. The lifter of freight transportation robot is designed to load and unload a baggage through up and down motion. Also, ultrasonic sensor, RFID, QR-code and camera sensor is used to carry out various functions while the robot navigates in the various environment. We design an operation method of the mobile robot in order to effectively arrive a goal position and transport a freight. The proposed methods are verified through various experiments.

• Spatial Information Research
• /
• v.23 no.3
• /
• pp.91-100
• /
• 2015

We developed a micro UAV based rapid mapping system that provides geospatial information of target areas in a rapid and automatic way. Users can operate the system easily although they are inexperienced in UAV operation and photogrammetric processes. For the aerial data acquisition, we constructed a micro UAV system mounted with a digital camera, a GPS/IMU, and a control board for the sensor integration and synchronization. We also developed a flight planning software and data processing software for the generation of geo-spatial information. The processing software operates automatically with a high speed to perform data quality control, image matching, georeferencing, and orthoimage generation. With the system, we have generated individual ortho-images within 30 minutes from 57 images of 3cm resolution acquired from a target area of $400m{\times}300m$.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.34 no.1
• /
• pp.53-62
• /
• 2016

In recent years, UAV Photogrammetry based on an ultra-light UAS(Unmanned Aerial System) installed with a low-cost compact navigation device and a camera has attracted great attention through fast and accurate acquirement of geo-spatial data. In particular, UAV Photogrammetry do gradually replace the traditional aerial photogrammetry because it is able to produce DEMs(Digital Elevation Models) and Orthophotos rapidly owing to large amounts of high resolution image collection by a low-cost camera and image processing software combined with computer vision technique. With these advantages, UAV-Photogrammetry has therefore been applying to a large scale mapping and cadastral surveying that require accurate position information. This paper presents experimental results of an accuracy performance test with images of 4cm GSD from a fixed wing UAS to demarcate parcel boundaries in agricultural area. Consequently, the accuracy of boundary point extracted from UAS orthoimage has shown less than 8cm compared with that of terrestrial cadastral surveying. This means that UAV images satisfy the tolerance limit of distance error in cadastral surveying for the scale of 1: 500. And also, the area deviation is negligible small, about 0.2%(3.3m²), against true area of 1,969m² by cadastral surveying. UAV-Photogrammetry is therefore as a promising technology to demarcate parcel boundaries.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.21 no.6
• /
• pp.1237-1242
• /
• 2017

Computer vision is coming more interesting with new imaging sensors' new capabilities which enable it to understand more its surrounding environment by imitating human vision system with artificial intelligence techniques. In this paper, we made experiments with Kinect camera, a new depth sensor for object detection and distance measurement functions, most essential functions in computer vision such as for unmanned or manned vehicles, robots, drones, etc. Therefore, Kinect camera is used here to estimate the position or the location of objects in its field of view and measure the distance from them to its depth sensor in an accuracy way by checking whether that the detected object is real object or not to reduce processing time ignoring pixels which are not part of real object. Tests showed promising results with such low-cost range sensor, Kinect camera which can be used for object detection and distance measurement which are fundamental functions in computer vision applications for further processing.

• Journal of the Institute of Electronics Engineers of Korea SC
• /
• v.45 no.6
• /
• pp.149-156
• /
• 2008

SLAM(Simultaneous Localization and Mapping) system is to find a global position and build a map with sensing data when an unmanned-robot navigates an unknown environment. Two kinds of system were developed. One is used distance measurement sensors such as an ultra sonic and a laser sensor. The other is used stereo vision system. The distance measurement SLAM with sensors has low computing time and low cost, but precision of system can be somewhat worse by measurement error or non-linearity of the sensor In contrast, stereo vision system can accurately measure the 3D space area, but it needs high-end system for complex calculation and it is an expensive tool. In this paper, we implement the SLAM system using a single camera image and a PSD sensors. It detects obstacles from the front PSD sensor and then perceive size and feature of the obstacles by image processing. The probability SLAM was implemented using the data of sensor and image and we verify the performance of the system by real experiment.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2016.10a
• /
• pp.224-226
• /
• 2016

With the technical development and rapid increase of private demand, the new market for unmanned vehicle combined with the characteristics of 'unmanned automation' and 'vehicle' is rapidly growing. Even though the pilot driving is currently allowed in some countries, there is no country that has institutionalized the formal driving of self-driving cars. In case of the existing vehicles, safety incidents are frequently happening due to the frequent malfunction of the rear sensor, blind spot of the rear camera, or drivers' carelessness. Once such minor flaws are complemented, the relevant regulations for the commercialization of self-driving car and small drone could be relieved. Contrary to the ultrasonic and laser sensors used for the existing vehicles, this paper aims to attempt the distance measurement by using the depth sensor. A depth camera calculates the distance data based on the TOF method calculating the time difference by lighting laser or infrared light onto an object or area and then receiving the beam coming back. As this camera can obtain the depth data in the pixel unit of CCD camera, it can be used for collecting depth data in real-time. This paper suggests to solve problems mentioned above by using depth data in real-time and also to design the obstacle avoidance system through distance measurement.

• Proceedings of the Korean Information Science Society Conference
• /
• 2012.06d
• /
• pp.143-145
• /
• 2012

끊이지 않는 원룸 침입 범죄 발생으로 인해 대부분의 원룸 거주자들은 긴장과 불안감을 느끼면서 생활하고 있다. 본 논문에서는 조도센서와 마이크 그리고 카메라 디바이스를 이용한 저전력 침입감지 기능과 침입자 감지시 알람과 자동 녹화 기능, 그리고 자동신고와 주변지인에게 도움요청SMS 전송 기능을 탑재한 스마트폰 기반 저전력 올인원 무인 경비 시스템 을 개발하였다 본 연구에서 개발한 시스템을 대학가 원룸에 실제 설치 후 실험을 통하여 정확성과 실용성, 그리고 에너지효율성을 확인하였다.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2019.05a
• /
• pp.711-713
• /
• 2019

본 논문은 기존의 단순 감지 센서형 양식장 관리 시스템을 벗어나기 위해 IoT와 AI기술을 이용한 무인 양식장 관리 시스템 개발에 관한 것이다. 국내 양식장 상황에 맞는 유해 조류와 한국형 어선 이미지를 학습시켜 실시간 카메라 영상을 통해 유해 및 무해 물체를 판단하도록 하였으며 이에 따라 적절한 퇴치 기능을 수행하도록 하였다. 또한 현존하는 양식장 관리 시스템이 환경 관리 시스템과 감시 및 퇴치 시스템으로 이분화 된 경향을 보여 하나로 통합하는 과정의 필요성이 대두되었다. 따라서 감시 및 퇴치 기능 수행뿐만 아니라 양식장 내 환경 데이터를 실시간으로 받아오고 사용자가 단말기를 통해 양식장 상황을 확인 및 관리가 가능하도록 구현하고자 하였다.