• Title/Summary/Keyword: Object-detection

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Measurement of Aerodynamic Heating over a Protuberance in Hypersonic Flow of Mach 7 (Mach 7 극초음속 유동 내의 돌출물 공력가열 계측)

  • Lee, Hyoung-Jin;Lee, Bok-Jik;Jeung, In-Seuck;Kim, Seong-Lyong;Kim, In-Sun
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.37 no.6
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    • pp.562-570
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    • 2009
  • An Experimental study was conducted on the flow characteristics and interference heating caused by a two-dimensional object protruding from a flat plate using a blow-down type of hypersonic wind tunnel. Inflow condition was a free-stream Mach number of 7.0 and a unit Reynolds number of $2.0{\times}10^6/m$. Experimental conditions were varied with three heights of protuberance for two flat plate models which have different lengths. Experimental data were obtained from Schlieren visualization images and heat flux measurements. Also, this paper suggests hypersonic experimental techniques such as boundary-layer detection method in detail. A Large separation region was observed in front of the protuberance and that region was very sensitive to the height of protuberance and the length of the flat plate. For only the highest protuberance, a severe jump of heat flux was observed at the top station among the measuring points. Measured heat flux is large when the height of protuberance is large and the length of flat plate is long.

Information Fusion of Photogrammetric Imagery and Lidar for Reliable Building Extraction (광학 영상과 Lidar의 정보 융합에 의한 신뢰성 있는 구조물 검출)

  • Lee, Dong-Hyuk;Lee, Kyoung-Mu;Lee, Sang-Uk
    • Journal of Broadcast Engineering
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    • v.13 no.2
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    • pp.236-244
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    • 2008
  • We propose a new building detection and description algorithm for Lidar data and photogrammetric imagery using color segmentation, line segments matching, perceptual grouping. Our algorithm consists of two steps. In the first step, from the initial building regions extracted from Lidar data and the color segmentation results from the photogrammetric imagery, we extract coarse building boundaries based on the Lidar results with split and merge technique from aerial imagery. In the secondstep, we extract precise building boundaries based on coarse building boundaries and edges from aerial imagery using line segments matching and perceptual grouping. The contribution of this algorithm is that color information in photogrammetric imagery is used to complement collapsed building boundaries obtained by Lidar. Moreover, linearity of the edges and construction of closed roof form are used to reflect the characteristic of man-made object. Experimental results on multisensor data demonstrate that the proposed algorithm produces more accurate and reliable results than Lidar sensor.

Computer Vision-based Method of detecting a Approaching Vehicle or the Safety of a Bus Passenger Getting off (버스 승객의 안전한 하차를 위한 컴퓨터비전 기반의 차량 탐지 시스템 개발)

  • Lee Kwang-Soon;Lee Kyung-Bok;Rho Kwang-Hyun;Han Min-Hong
    • Journal of the Institute of Convergence Signal Processing
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    • v.6 no.1
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    • pp.1-7
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    • 2005
  • This paper describes the system for detecting vehicles in the rear and rear-side that access between sidewalk and bus stopped to city road at day by computer vision-based method. This system informs appearance of vehicles to bus driver and passenger for the safety of a bus passenger getting off. The camera mounted on the top portion of the bus exit door gets the rear and rear-side image of the bus whenever a bus stops at the stop. The system sets search area between bus and sidewalk from this image and detects a vehicle by using change of image and sobel filtering in this area. From a central point of the vehicle detected, we can find out the distance, speed and direction by its location, width and length. It alarms the driver and passengers when it's judged that dangerous situation for the passenger getting off happens. This experiment results in a detection rate more than 87% in driving by bus on the road.

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Facial Expression Recognition Using SIFT Descriptor (SIFT 기술자를 이용한 얼굴 표정인식)

  • Kim, Dong-Ju;Lee, Sang-Heon;Sohn, Myoung-Kyu
    • KIPS Transactions on Software and Data Engineering
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    • v.5 no.2
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    • pp.89-94
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    • 2016
  • This paper proposed a facial expression recognition approach using SIFT feature and SVM classifier. The SIFT was generally employed as feature descriptor at key-points in object recognition fields. However, this paper applied the SIFT descriptor as feature vector for facial expression recognition. In this paper, the facial feature was extracted by applying SIFT descriptor at each sub-block image without key-point detection procedure, and the facial expression recognition was performed using SVM classifier. The performance evaluation was carried out through comparison with binary pattern feature-based approaches such as LBP and LDP, and the CK facial expression database and the JAFFE facial expression database were used in the experiments. From the experimental results, the proposed method using SIFT descriptor showed performance improvements of 6.06% and 3.87% compared to previous approaches for CK database and JAFFE database, respectively.

A Self-optimizing Mechanism of Location Aware Systems for Ubiquitous Computing (유비쿼터스 컴퓨팅을 위한 위치 감지 시스템의 자가 치적화 기법)

  • Choi, Ho-Young;Choi, Chang-Yeol;Kim, Sung-Soo
    • The KIPS Transactions:PartA
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    • v.12A no.4 s.94
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    • pp.273-280
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    • 2005
  • The mobility or highly interconnected and communicating devices and users has implications for the QoS in a ubiquitous computing environment. Therefore, it is important for location aware systems to detect location of mobile object correctly and Provide high quality services in ubiquitous environment. However, it is not easy that location aware systems offer highly reliable QoS to users because process strategies of location aware systems are limited by the capability according to the applied detection target objects. In this paper, we design an autonomic architecture which analyzes the location aware system condition and autonomously chooses the best appropriate process strategy. We also have simulated the Proposed architecture in order to verify its performance. The test results show us that the architecture using self-optimizing mechanism provides higher QoS to users in variable bandwidth.

3D Reconstruction of Tissue from a few of MRI Images using Radial Basis Function (BBF를 이용한 적은 수의 MRI 이미지로부터 3차원 조직 재구성)

  • Shin, Young-Seok;Kim, Hyoung-Seok B.
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.12 no.11
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    • pp.2077-2082
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    • 2008
  • Recent the advanced technologies in medical imaging such as magnetic resonance imaging (MRI) and computed tomography (CT) make doctors improve the diagnostic skill with detailed anatomical information. In general, it is necessary to get a number of MRI images in order to obtain more detail information. However, the performance of MRI machines of privately run hospitals is not good and thus we may obtain only a few of MRI images. If 3D surface reconstruction is accomplished with a few slices, then it generates 3D surface of poor qualify. This paper propose a way to Set a 3D surface of high quality from a few of number of slices. First of all, our algorithm detects the boundary of tissues which we want to reconstruct as a 3D object and find out the set of vortices on the boundary. And then we generate a 3D implicit surface to interpolate the boundary points by using radial basis function. Lastly, we render the 3D implicit surface by using Marching cube algorithms.

A Method of DTM Generation from KOMPSAT-3A Stereo Images using Low-resolution Terrain Data (저해상도 지형 자료를 활용한 KOMPSAT-3A 스테레오 영상 기반의 DTM 생성 방법)

  • Ahn, Heeran;Kim, Taejung
    • Korean Journal of Remote Sensing
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    • v.35 no.5_1
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    • pp.715-726
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    • 2019
  • With the increasing prevalence of high-resolution satellite images, the need for technology to generate accurate 3D information from the satellite images is emphasized. In order to create a digital terrain model (DTM) that is widely used in applications such as change detection and object extraction, it is necessary to extract trees, buildings, etc. that exist in the digital surface model (DSM) and estimate the height of the ground. This paper presents a method for automatically generating DTM from DSM extracted from KOMPSAT-3A stereo images. The technique was developed to detect the non-ground area and estimate the height value of the ground by using the previously constructed low-resolution topographic data. The average vertical accuracy of DTMs generated in the four experimental sites with various topographical characteristics, such as mountainous terrain, densely built area, flat topography, and complex terrain was about 5.8 meters. The proposed technique would be useful to produce high-quality DTMs that represent precise features of the bare-earth's surface.

Deep Learning for Herbal Medicine Image Recognition: Case Study on Four-herb Product

  • Shin, Kyungseop;Lee, Taegyeom;Kim, Jinseong;Jun, Jaesung;Kim, Kyeong-Geun;Kim, Dongyeon;Kim, Dongwoo;Kim, Se Hee;Lee, Eun Jun;Hyun, Okpyung;Leem, Kang-Hyun;Kim, Wonnam
    • Proceedings of the Plant Resources Society of Korea Conference
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    • 2019.10a
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    • pp.87-87
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    • 2019
  • The consumption of herbal medicine and related products (herbal products) have increased in South Korea. At the same time the quality, safety, and efficacy of herbal products is being raised. Currently, the herbal products are standardized and controlled according to the requirements of the Korean Pharmacopoeia, the National Institute of Health and the Ministry of Public Health and Social Affairs. The validation of herbal products and their medicinal component is important, since many of these herbal products are composed of two or more medicinal plants. However, there are no tools to support the validation process. Interest in deep learning has exploded over the past decade, for herbal medicine using algorithms to achieve herb recognition, symptom related target prediction, and drug repositioning have been reported. In this study, individual images of four herbs (Panax ginseng C.A. Meyer, Atractylodes macrocephala Koidz, Poria cocos Wolf, Glycyrrhiza uralensis Fischer), actually sold in the market, were achieved. Certain image preprocessing steps such as noise reduction and resize were formatted. After the features are optimized, we applied GoogLeNet_Inception v4 model for herb image recognition. Experimental results show that our method achieved test accuracy of 95%. However, there are two limitations in the current study. Firstly, due to the relatively small data collection (100 images), the training loss is much lower than validation loss which possess overfitting problem. Secondly, herbal products are mostly in a mixture, the applied method cannot be reliable to detect a single herb from a mixture. Thus, further large data collection and improved object detection is needed for better classification.

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Development of Unmanned Video Recording System using Mobile (모바일을 이용한 무인 영상 녹화 시스템 개발)

  • Ahn, Byeongtae
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.20 no.6
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    • pp.254-260
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    • 2019
  • Recently, a self-camera that generates and distributes a large amount of moving images has been rapidly increasing due to the appearance of SNS such as Facebook, Instagram, and Tweet using mobile. In particular, the amount of SNS connections using mobile phones is significantly increasing in terms of usage, number of connections, and usage time. However, the use of a self-recording system using a smartphone by itself is extremely limited not only in terms of usage but also in frequency of use. In addition, the conventional unattended recording system is a very expensive system that automatically records and tracks an object to be photographed using an infrared signal. Therefore, this paper developed a low cost unmanned recording system using mobile phone. The system consists of a commercial mobile camera, a servomotor for moving the camera from side to side, a microcontroller for controlling the motor, and a commercial wireless Bluetooth earset for video audio input. And it is an unmanned automation system using mobile, and anyone can record image by self image tracking.

Distributed Control Framework based on Mobile Agent Middleware

  • Lee, Yon-Sik
    • Journal of the Korea Society of Computer and Information
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    • v.25 no.12
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    • pp.195-202
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    • 2020
  • The control system for the efficiency of resource utilization in sensor network environment based on object detection and environmental sensor requires active control function which based on sensor data acquisition and transmission functions and server's data analysis. Using active rule-based mobile agent middleware, this paper proposes a new distributed control framework that reduces the load of central sensor data server in sensor network environment by implementing remote data sensing and Zigbee-based communication with server and data analysis method of server. In addition, we implemented a power-saving system prototype using active rule-based distributed control methods that applied consumer's demand and environmental variables, and verified the validity of the proposed system through experiments and evaluations in the mobile agent middleware environment. The proposed system is a system framework that can efficiently autonomously control distributed objects in the sensor network environment, and it can be applied effectively to the development of demand response service based on optimal power control for the smart power system in the future.