• Title/Summary/Keyword: 영상취득시스템

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A Study on Change object Using Aerial photos (항공사진 입체시를 활용한 변화객체 탐색에 대한 연구)

  • Kim, Kam-Rae;Kim, Hak-Jun;HwangBo, Sang-Won;Jo, Won-U
    • Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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    • 2007.04a
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    • pp.197-200
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    • 2007
  • 항공사진 원데이터의 변형을 방지하고 효율적인 관리를 위해서는 자동독취를 통한 수치화 방안이 마련되어야 한다. 항공사진 판독업무에 있어서 기존 판독자만 밀착항공사진과 입체경을 통하여 건축물의 형태와 변화 여부를 판단하던 것을 모니터 상에서 누구나 건물의 변동사항을 볼 수 있도록 효율적인 판독시스템을 구축하여 판독의 신뢰도를 높여야 한다. 판독시스템 구축은 디지털 영상의 다양한 활용과 업무의 효율성 확보 및 대민서비스 향상 차원에서 이루어져야 할 것이다. 또한 현재 외국의 항측사들이 실제로 활용하고 있으며 조만간 국내에서도 도입 예정인 디지털항공카메라는 항공사진의 수치화 단계를 거치치 않고 직접 수치항공영상을 취득 할 수 있으므로 수치화 과정에서 발생하는 많은 오류들을 제거할 수 있음은 물론 판독시스템을 활용한 데이터의 직접처리가 가능해 시간적, 경제적으로 많은 장점들을 가지고 있다. 그러므로 디지털항공카메라의 도입에 대비한 개발현황과 활용도 등에 관한 사전 연구가 수행되어야 한다. 본 연구에서는 사용자가 직접 입체 판독 및 분석을 수행할 수 있는 플랫폼을 구비함으로서 오류를 최소화 할 수 있도록 편광 모니터(Z-Screen)를 사용하여 수행하였다. 또한 환경은 Microsoft Window OS 환경 상에서 구동될 수 있도록 개발함으로서 시스템의 범용적 사용을 위한 기초 환경을 제공하도록 제안하였다.

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A Real-time Pigsty Monitoring System Based on Audio/Visual Sensors (A/V 센서 기반의 실시간 돈사 모니터링 시스템)

  • Oh, Seunggeun;In, Kyeongjun;Chung, Yongwha;Chang, Hong-Hee;Park, Daihee
    • Proceedings of the Korea Information Processing Society Conference
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    • 2012.11a
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    • pp.1162-1165
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    • 2012
  • 어미로부터 생후 21일령(또는 28일령)에 젖을 때는 어린 자돈들은 면역력이 약하여 통상 폐사율이 30~40%까지 치솟는 등 자돈 관리가 국내 양돈 농가의 가장 큰 문제 중 하나로 인식되고 있다. 본 논문에서는 이러한 양돈 농가의 문제를 해결하기 위하여 자돈사(새끼돼지 축사)에 카메라와 마이크를 설치하고 획득된 영상과 소리 정보를 이용하여 자돈들을 모니터링하는 시스템을 제안한다. 제안된 시스템은 실시간으로 유입되는 영상과 소리 스트림 데이터로부터 각각 움직임 벡터와 평균 피치 값을 추출하여 이미 설정된 정상 상황의 임계치 값을 넘는 순간부터를 불특정 이상 상황이라 판단한다. 실제, 경상남도 함양군의 한 돼지 농장에 A/V 센서 기반의 실험 환경을 구축하고 2012년 6월 한 달간의 이유자돈 돈사의 모니터링 데이터 셋을 취득하였고 전반기 15일간의 데이터 셋을 이용하여 자돈사 모니터링 시스템의 프로토타입을 설계 구현하였으며 후반기 15일간의 A/V 스트림 데이터로는 검증 실험을 수행하였다.

Moving Objects Tracking Method using Spatial Projection in Intelligent Video Traffic Surveillance System (지능형 영상 교통 감시 시스템에서 공간 투영기법을 이용한 이동물체 추적 방법)

  • Hong, Kyung Taek;Shim, Jae Homg;Cho, Young Im
    • Journal of the Korean Institute of Intelligent Systems
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    • v.25 no.1
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    • pp.35-41
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    • 2015
  • When a video surveillance system tracks a specific object, it is very important to get quickly the information of the object through fast image processing. Usually one camera surveillance system for tracking the object made results in various problems such like occlusion, image noise during the tracking process. It makes difficulties on image based moving object tracking. Therefore, to overcome the difficulties the multi video surveillance system which installed several camera within interested area and looking the same object from multi angles of view could be considered as a solution. If multi cameras are used for tracking object, it is capable of making a decision having high accuracy in more wide space. This paper proposes a method of recognizing and tracking a specific object like a car using the homography in which multi cameras are installed at the crossroad.

Gait-based Human Identification System using Eigenfeature Regularization and Extraction (고유특징 정규화 및 추출 기법을 이용한 걸음걸이 바이오 정보 기반 사용자 인식 시스템)

  • Lee, Byung-Yun;Hong, Sung-Jun;Lee, Hee-Sung;Kim, Eun-Tai
    • Journal of the Korean Institute of Intelligent Systems
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    • v.21 no.1
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    • pp.6-11
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    • 2011
  • In this paper, we propose a gait-based human identification system using eigenfeature regularization and extraction (ERE). First, a gait feature for human identification which is called gait energy image (GEI) is generated from walking sequences acquired from a camera sensor. In training phase, regularized transformation matrix is obtained by applying ERE to the gallery GEI dataset, and the gallery GEI dataset is projected onto the eigenspace to obtain galley features. In testing phase, the probe GEI dataset is projected onto the eigenspace created in training phase and determine the identity by using a nearest neighbor classifier. Experiments are carried out on the CASIA gait dataset A to evaluate the performance of the proposed system. Experimental results show that the proposed system is better than previous works in terms of correct classification rate.

Development of an intelligent edge computing device equipped with on-device AI vision model (온디바이스 AI 비전 모델이 탑재된 지능형 엣지 컴퓨팅 기기 개발)

  • Kang, Namhi
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.22 no.5
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    • pp.17-22
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    • 2022
  • In this paper, we design a lightweight embedded device that can support intelligent edge computing, and show that the device quickly detects an object in an image input from a camera device in real time. The proposed system can be applied to environments without pre-installed infrastructure, such as an intelligent video control system for industrial sites or military areas, or video security systems mounted on autonomous vehicles such as drones. The On-Device AI(Artificial intelligence) technology is increasingly required for the widespread application of intelligent vision recognition systems. Computing offloading from an image data acquisition device to a nearby edge device enables fast service with less network and system resources than AI services performed in the cloud. In addition, it is expected to be safely applied to various industries as it can reduce the attack surface vulnerable to various hacking attacks and minimize the disclosure of sensitive data.

DEM Extraction from LiDAR DSM of Urban Area (도시지역 LiDAR DSM으로부터 DEM추출기법 연구)

  • Choi, Yun-Woong;Cho, Gi-Sung
    • Journal of Korean Society for Geospatial Information Science
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    • v.13 no.1 s.31
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    • pp.19-25
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    • 2005
  • Nowadays, it is possible to construct the DEMs of urban area effectively and economically by LiDAR system. But the data from LiDAR system has form of DSM which is included various objects as trees and buildings. So the preprocess is necessary to extract the DEMs from LiDAR DSMs for particular purpose as effects analysis of man-made objects for flood prediction. As this study is for extracting DEM from LiDAR DSM of urban area, we detected the edges of various objects using edge detecting algorithm of image process. And, we tried mean value filtering, median value filtering and minimum value filtering or detected edges instead of interpolation method which is used in the previous study and could be modified the source data. it could minimize the modification of source data, and the extracting process of DEMs from DSMs could be simplified and automated.

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Accuracy Analysis of Coastal Area Modeling through UAV Photogrammetry (무인항공측량을 통한 해안 지형 모델링의 정확도 분석)

  • Choi, Kyoungah;Lee, Impyeong
    • Korean Journal of Remote Sensing
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    • v.32 no.6
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    • pp.657-672
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    • 2016
  • Coastal erosion happens frequently in many different types. To control coastal erosion zone effectively and establish response plans, we need to accumulate data indicating topography changes through monitoring the erosion situation continuously. UAV photogrammetric systems, which can fly autonomously at a low altitude, are recommended as an economical and precision means to monitor the coastal zones. In this study, we aim to verify the accuracy of the generated orthoimages and DEM as a result of processing the UAV data of a coastal zone by comparing them with various reference data. We established a verification routine and examined the possibilities of applying the UAV photogrammetric systems to monitoring coastal erosion by checking the analyzed accuracy by the routine. As a result of verifying the generated the geospatial information from acquired data under various configurations, the horizontal and vertical accuracy (RMSE) were about 2.7 cm and 4.8 cm respectively, which satisfied 5 cm, the accuracy required for coastal erosion monitoring.

Iris Recognition Using the 2-D Gabor Filter (2-D Gabor 필터를 이용한 홍채인식)

  • Go, Hyoun-Joo;Lee, Dae-Jong;Chun, Myung-Geun
    • Journal of the Korean Institute of Intelligent Systems
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    • v.13 no.6
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    • pp.716-721
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    • 2003
  • This paper deals with the iris recognition as one of biometric techniques which are applied to identify a person using his/her behavior or congenital characteristics. The iris of a human eye has a texture that is unique and time invariant for each individual. First, we obtain the feature vector from the 2D iris pattern having a property of size invariant and divide it into 24 sectors which are further through three types of 2D Gabor filters. At the recognition process, we compute the similarity measure based on the correlation values. Here, since we use three different matching values obtained from three different directional Gabor filters and select the maximum value among them, it is possible to minimize the recognition error rate. To show the usefulness of the proposed algorithm, we applied it to a biometric database consisting of 50 iris patterns extracted from 10 subjects and finally get more higher than 90% recognition rate.

Study on Enhancements to Ultrasonic Data Imaging Using Full Matrix Capture Technique (Full Matrix Capture 기법을 통한 초음파신호 영상화 향상 연구)

  • Lee, Tae-Hun;Yoon, Byung-Sik;Lee, Jeong-Seok
    • Journal of the Korean Society for Nondestructive Testing
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    • v.35 no.5
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    • pp.299-306
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    • 2015
  • A conventional phased array system can control an ultrasonic beam electronically by adjusting the excitation time delay of individual elements in a multi-element probe and produce an ultrasonic image. In Contrast, full matrix capture (FMC) is a data acquisition process that allows receiving ultrasonic signals from one single shot of the phased array transducer element through all the other elements and captures the complete dataset from every possible transmit-receive combination. This FMC data can be used to create the ultrasonic image in post processing. It is possible to produce not only images equivalent to conventional phased array image but also total focusing method (TFM) images with improved resolution and sharpness, which is virtually focused at any point in a region of interest. In this paper, the system that can perform FMC by using a conventional phased array instrument is developed, and a study was conducted on the imaging algorithms to reconstruct sector B-scan and TFM images from FMC dataset.

Updating of Digital Map using Digital Image and LIDAR (디지털 영상과 LIDAR 자료를 이용한 수치지도 갱신)

  • Yun, Bu-Yeol;Hong, Jung-Soo
    • Journal of the Korean Geophysical Society
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    • v.9 no.2
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    • pp.87-97
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    • 2006
  • LIDAR(Light Detection and Ranging) is a new technology for obtaining DEM(Digital Elevation Model)ewith high density and high point acuracy. As LIDAR emerged, DEM could be developed in the earthsurface more efficiently and more economically, compared to the conventional aerial photogrametry.In this study, a digital camera is simultaneously used in combined LIDAR surveying, and acquired digitial image and DEM produce digital orthoimage. In this process, methods of combining sensor andorthoimage, GCPs determined by GPS surveying are used. Two digital orthoimage are produced; onewith a few GCP and the other without them. The produced maps can be used to corect or revised1:1,000 or 1:5,000 scale maps acordingly.

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