• Title/Summary/Keyword: 영상정보시스템

Search Result 6,156, Processing Time 0.037 seconds

Accuracy Analysis of Medium Format CCD Camera RCD105 (중형카메라 RCD105 정확도 분석)

  • Kim, Tae-Hoon;Won, Jae-Ho;Kim, Chung-Pyeong;So, Jae-Kyeong;Yun, Hee-Cheon
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
    • /
    • v.28 no.4
    • /
    • pp.449-454
    • /
    • 2010
  • Lately, airborne digital camera and airborne laser scanner in field of airborne surveying are used to build geography information such as digital ortho photo map and DEM(Digital Elevation Model). In this study, 3D position accuracy is compared medium format CCD camera RCD105 with airborne digital camera DMC. For this, test area was decided for aerial photograph. And using 1/1,000 scale digital map, ground control points were selected for aerial triangulation and check points were selected for horizontal/vertical accuracy analysis using softcopy stereoplotter. Accuracy of RCD105 and DMC was estimated by result of aerial triangulation and result of check points measurement of using softcopy stereoplotter. In result of aerial triangulation, RMSE(Root Mean Square Error) X, Y, Z of RCD105 is 2.1, 2.2, 1.3 times larger than DMC. In result of check point measurement using softcopy stereoplotter, horizontal/ vertical RMSE of RCD105 is 2.5, 4.3 times larger than DMC. Even though accuracy of RCD105 is lower than DMC, it is maybe possible to make digital map and ortho photo using RCD105.

Deep Learning-based Forest Fire Classification Evaluation for Application of CAS500-4 (농림위성 활용을 위한 산불 피해지 분류 딥러닝 알고리즘 평가)

  • Cha, Sungeun;Won, Myoungsoo;Jang, Keunchang;Kim, Kyoungmin;Kim, Wonkook;Baek, Seungil;Lim, Joongbin
    • Korean Journal of Remote Sensing
    • /
    • v.38 no.6_1
    • /
    • pp.1273-1283
    • /
    • 2022
  • Recently, forest fires have frequently occurred due to climate change, leading to human and property damage every year. The forest fire monitoring technique using remote sensing can obtain quick and large-scale information of fire-damaged areas. In this study, the Gangneung and Donghae forest fires that occurred in March 2022 were analyzed using the spectral band of Sentinel-2, the normalized difference vegetation index (NDVI), and the normalized difference water index (NDWI) to classify the affected areas of forest fires. The U-net based convolutional neural networks (CNNs) model was simulated for the fire-damaged areas. The accuracy of forest fire classification in Donghae and Gangneung classification was high at 97.3% (f1=0.486, IoU=0.946). The same model used in Donghae and Gangneung was applied to Uljin and Samcheok areas to get rid of the possibility of overfitting often happen in machine learning. As a result, the portion of overlap with the forest fire damage area reported by the National Institute of Forest Science (NIFoS) was 74.4%, confirming a high level of accuracy even considering the uncertainty of the model. This study suggests that it is possible to quantitatively evaluate the classification of forest fire-damaged area using a spectral band and indices similar to that of the Compact Advanced Satellite 500 (CAS500-4) in the Sentinel-2.

Development of Deep Learning Model for Detecting Road Cracks Based on Drone Image Data (드론 촬영 이미지 데이터를 기반으로 한 도로 균열 탐지 딥러닝 모델 개발)

  • Young-Ju Kwon;Sung-ho Mun
    • Land and Housing Review
    • /
    • v.14 no.2
    • /
    • pp.125-135
    • /
    • 2023
  • Drones are used in various fields, including land survey, transportation, forestry/agriculture, marine, environment, disaster prevention, water resources, cultural assets, and construction, as their industrial importance and market size have increased. In this study, image data for deep learning was collected using a mavic3 drone capturing images at a shooting altitude was 20 m with ×7 magnification. Swin Transformer and UperNet were employed as the backbone and architecture of the deep learning model. About 800 sheets of labeled data were augmented to increase the amount of data. The learning process encompassed three rounds. The Cross-Entropy loss function was used in the first and second learning; the Tversky loss function was used in the third learning. In the future, when the crack detection model is advanced through convergence with the Internet of Things (IoT) through additional research, it will be possible to detect patching or potholes. In addition, it is expected that real-time detection tasks of drones can quickly secure the detection of pavement maintenance sections.

A Case Study of Successful Strategy for Self-Directed Learning Center of Educational Service Franchise - Focusing on the Case of Learning Center of Daekyo Noonnoppi - (교육 서비스 프랜차이즈의 자기주도 학습관 사업화 사례연구 - 대교 눈높이 러닝센터 사례를 중심으로 -)

  • Yoo, Dong-Keun;Hong, Jong-Pil;Hwang, Jae-Kwang
    • The Korean Journal of Franchise Management
    • /
    • v.5 no.1
    • /
    • pp.49-64
    • /
    • 2014
  • The purpose of this work is to analyze successful business strategy of Daekyo Noonnoppi. Daekyo Noonnoppi, a franchise company of educational service, activated education business by establishing new way of providing education opportunity: self-directed learning center. They introduced not only the concept of learning center but also sustainable business strategies, which leads to remarkable success in the education business field. Daekyo Noonnoppi deployed three managerial concepts for study achievement: goal management, study management, and environment management. This Franchise company has three advantages of its success: Goal, Study and environment management: First, the goal management helps students to develop self-directed attitudes by making(appropriate) atmosphere which is able to build study goal and plan. In addition, this company provides information to their students to searches ways of study through the test reflecting their tendency. Furthermore, this company offers a variety of events for motivating study. Second, study management is helpful for students to develop holistic fundamental knowledge through its textbooks of this company and provides solutions and time management for study through 1 on 1 study advice. Third, environment management is used to making atmosphere to develop self-directed learning way for its students and provides spaces for students equipped with multimedia systems and cyber learning infrastructures.

Automatic 3D data extraction method of fashion image with mannequin using watershed and U-net (워터쉐드와 U-net을 이용한 마네킹 패션 이미지의 자동 3D 데이터 추출 방법)

  • Youngmin Park
    • The Journal of the Convergence on Culture Technology
    • /
    • v.9 no.3
    • /
    • pp.825-834
    • /
    • 2023
  • The demands of people who purchase fashion products on Internet shopping are gradually increasing, and attempts are being made to provide user-friendly images with 3D contents and web 3D software instead of pictures and videos of products provided. As a reason for this issue, which has emerged as the most important aspect in the fashion web shopping industry, complaints that the product is different when the product is received and the image at the time of purchase has been heightened. As a way to solve this problem, various image processing technologies have been introduced, but there is a limit to the quality of 2D images. In this study, we proposed an automatic conversion technology that converts 2D images into 3D and grafts them to web 3D technology that allows customers to identify products in various locations and reduces the cost and calculation time required for conversion. We developed a system that shoots a mannequin by placing it on a rotating turntable using only 8 cameras. In order to extract only the clothing part from the image taken by this system, markers are removed using U-net, and an algorithm that extracts only the clothing area by identifying the color feature information of the background area and mannequin area is proposed. Using this algorithm, the time taken to extract only the clothes area after taking an image is 2.25 seconds per image, and it takes a total of 144 seconds (2 minutes and 4 seconds) when taking 64 images of one piece of clothing. It can extract 3D objects with very good performance compared to the system.

Dynamic Traffic Assignment Using Genetic Algorithm (유전자 알고리즘을 이용한 동적통행배정에 관한 연구)

  • Park, Kyung-Chul;Park, Chang-Ho;Chon, Kyung-Soo;Rhee, Sung-Mo
    • Journal of Korean Society for Geospatial Information Science
    • /
    • v.8 no.1 s.15
    • /
    • pp.51-63
    • /
    • 2000
  • Dynamic traffic assignment(DTA) has been a topic of substantial research during the past decade. While DTA is gradually maturing, many aspects of DTA still need improvement, especially regarding its formulation and solution algerian Recently, with its promise for In(Intelligent Transportation System) and GIS(Geographic Information System) applications, DTA have received increasing attention. This potential also implies higher requirement for DTA modeling, especially regarding its solution efficiency for real-time implementation. But DTA have many mathematical difficulties in searching process due to the complexity of spatial and temporal variables. Although many solution algorithms have been studied, conventional methods cannot iud the solution in case that objective function or constraints is not convex. In this paper, the genetic algorithm to find the solution of DTA is applied and the Merchant-Nemhauser model is used as DTA model because it has a nonconvex constraint set. To handle the nonconvex constraint set the GENOCOP III system which is a kind of the genetic algorithm is used in this study. Results for the sample network have been compared with the results of conventional method.

  • PDF

Clinical Application of in Vivo Dosimetry System in Radiotherapy of Pelvis (골반부 방사선 치료 환자에서 in vivo 선량측정시스템의 임상적용)

  • Kim, Bo-Kyung;Chie, Eui-Kyu;Huh, Soon-Nyung;Lee, Hyoung-Koo;Ha, Sung-Whan
    • Journal of Radiation Protection and Research
    • /
    • v.27 no.1
    • /
    • pp.37-49
    • /
    • 2002
  • The accuracy of radiation dose delivery to target volume is one of the most important factors for good local control and less treatment complication. In vivo dosimetry is an essential QA procedure to confirm the radiation dose delivered to the patients. Transmission dose measurement is a useful method of in vivo dosimetry and it's advantages are non-invasiveness, simplicity and no additional efforts needed for dosimetry. In our department, in vivo dosimetry system using measurement of transmission dose was manufactured and algorithms for estimation of transmission dose were developed and tested with phantom in various conditions successfully. This system was applied in clinic to test stability, reproducibility and applicability to daily treatment and the accuracy of the algorithm. Transmission dose measurement was performed over three weeks. To test the reproducibility of this system, X-tay output was measured before daily treatment and then every hour during treatment time in reference condition(field size; $10 cm{\times} 10 cm$, 100 MU). Data of 11 patients whose pelvis were treated more than three times were analyzed. The reproducibility of the dosimetry system was acceptable with variations of measurement during each day and over 3 week period within ${\pm}2.0%$. On anterior- posterior and posterior fields, mean errors were between -5.20% and +2.20% without bone correction and between -0.62% and +3.32% with bone correction. On right and left lateral fields, mean errors were between -10.80% and +3.46% without bone correction and between -0.55% and +3.50% with bone correction. As the results, we could confirm the reproducibility and stability of our dosimetry system and its applicability in daily radiation treatment. We could also find that inhomogeneity correction for bone is essential and the estimated transmission doses are relatively accurate.

Design of Video Encoder activating with variable clocks of CCDs for CCTV applications (CCTV용 CCD를 위한 가변 clock으로 동작되는 비디오 인코더의 설계)

  • Kim, Joo-Hyun;Ha, Joo-Young;Kang, Bong-Soon
    • Journal of the Korea Institute of Information and Communication Engineering
    • /
    • v.10 no.1
    • /
    • pp.80-87
    • /
    • 2006
  • SONY corporation preoccupies $80\%$ of a market of the CCD used in a CCTV system. The CCD of SONY have high duality which can not follow the progress of capability. But there are some problems which differ the clock frequency used in CCD from the frequency used in common video encoder. To get the result by using common video encoder, the system needs a scaler that could adjust image size and PLL that synchronizes CCD's with encoder's clock So, this paper proposes the video encoder that is activated at equal clock used in CCD without scaler and PLL. The encoder converts ITU-R BT.601 4:2:2 or ITU-R BT.656 inputs from various video sources into NTSC or PAL signals in CVBS. Due to variable clock, property of filters used in the encoder is automatically changed by clock and filters adopt multiplier-free structures to reduce hardware complexity. The hardware bit width of programmable digital filters for luminance and chrominance signals, along with other operating blocks, are carefully determined to produce hish-quality digital video signals of ${\pm}1$ LSB error or less. The proposed encoder is experimentally demonstrated by using the Altera Stratix EP1S80B953C6ES device.

Comparison of Methodology and Accuracy of Digital Mapping of Forest Roads (수치임도망도 제작방법 및 정확도 비교)

  • Kim Tae-Geun;Yoon Jong-Suk;Woo Choong-Shik;Lee Kyu-Sung;Hong Chang-Hee
    • Spatial Information Research
    • /
    • v.13 no.3 s.34
    • /
    • pp.195-209
    • /
    • 2005
  • Forest road has been an essential infrastructure for various forestry practices as well as for recreational use, disaster management, and local economics promotion. Since 1980s, extensive network of forest roads has been constructed as an national project in Korea. However, due to the minimal-budget of the project, accurate maps of forest road are not usually available. Although forest road map is a main thematic layer for the forest Geographic Information System (FGIS), its locational accuracy has not been sufficient for the practical applications and, therefore, the update of digital forest road maps is urgent. The objectives of this study is to compare ae methodology of generating and updating digital forest road maps from the aspects of the map accuracy and the efficiency of methods. Four mapping methods (GPS surveying, satellite imagery, ortho aerial photograph, and digital photogrammetry) were applied to generate the forest road maps over the study area of Mt. Oseo in Chungchungnam-do, which has a 35km forest roads distributed in national, public and private forests. The forest road Imp produced by digital photogrammetric method is the most accurate and comparable to GPS surveying although it required the greatest amount of labor time.

  • PDF

Research Trends on Estimation of Soil Moisture and Hydrological Components Using Synthetic Aperture Radar (SAR를 이용한 토양수분 및 수문인자 산출 연구동향)

  • CHUNG, Jee-Hun;LEE, Yong-Gwan;KIM, Seong-Joon
    • Journal of the Korean Association of Geographic Information Studies
    • /
    • v.23 no.3
    • /
    • pp.26-67
    • /
    • 2020
  • Synthetic Aperture Radar(SAR) is able to photograph the earth's surface regardless of weather conditions, day and night. Because of its possibility to search for hydrological factors such as soil moisture and groundwater, and its importance is gradually increasing in the field of water resources. SAR began to be mounted on satellites in the 1970s, and about 15 or more satellites were launched as of 2020, which around 10 satellites will be launched within the next 5 years. Recently, various types of SAR technologies such as enhancement of observation width and resolution, multiple polarization and multiple frequencies, and diversification of observation angles were being developed and utilized. In this paper, a brief history of the SAR system, as well as studies for estimating soil moisture and hydrological components were investigated. Up to now hydrological components that can be estimated using SAR satellites include soil moisture, subsurface groundwater discharge, precipitation, snow cover area, leaf area index(LAI), and normalized difference vegetation index(NDVI) and among them, soil moisture is being studied in 17 countries in South Korea, North America, Europe, and India by using the physical model, the IEM(Integral Equation Model) and the artificial intelligence-based ANN(Artificial Neural Network). RADARSAT-1, ENVISAT, ASAR, and ERS-1/2 were the most widely used satellite, but the operation has ended, and utilization of RADARSAT-2, Sentinel-1, and SMAP, which are currently in operation, is gradually increasing. Since Korea is developing a medium-sized satellite for water resources and water disasters equipped with C-band SAR with the goal of launching in 2025, various hydrological components estimation researches using SAR are expected to be active.