• Title/Summary/Keyword: Captured Image

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Indoor Location and Pose Estimation Algorithm using Artificial Attached Marker (인공 부착 마커를 활용한 실내 위치 및 자세 추정 알고리즘)

  • Ahn, Byeoung Min;Ko, Yun-Ho;Lee, Ji Hong
    • Journal of Korea Multimedia Society
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    • v.19 no.2
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    • pp.240-251
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    • 2016
  • This paper presents a real-time indoor location and pose estimation method that utilizes simple artificial markers and image analysis techniques for the purpose of warehouse automation. The conventional indoor localization methods cannot work robustly in warehouses where severe environmental changes usually occur due to the movement of stocked goods. To overcome this problem, the proposed framework places artificial markers having different interior pattern on the predefined position of the warehouse floor. The proposed algorithm obtains marker candidate regions from a captured image by a simple binarization and labeling procedure. Then it extracts maker interior pattern information from each candidate region in order to decide whether the candidate region is a true marker or not. The extracted interior pattern information and the outer boundary of the marker are used to estimate location and heading angle of the localization system. Experimental results show that the proposed localization method can provide high performance which is almost equivalent to that of the conventional method using an expensive LIDAR sensor and AMCL algorithm.

A Study on Monitoring System for an Abnormal Behaviors by Object's Tracking (객체 추적을 통한 이상 행동 감시 시스템 연구)

  • Park, Hwa-Jin
    • Journal of Digital Contents Society
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    • v.14 no.4
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    • pp.589-596
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    • 2013
  • With the increase of social crime rate, the interest on the intelligent security system is also growing. This paper proposes a detection system of monitoring whether abnormal behavior is being carried in the images captured using CCTV. After detection of an object via subtraction from background image and morpholgy, this system extracts an abnormal behavior by each object's feature information and its trajectory. When an object is loitering for a while in CCTV images, this system considers the loitering as an abnormal behavior and sends the alarm signal to the control center to facilitate prevention in advance. Especially, this research aims at detecting a loitoring act among various abnormal behaviors and also extends to the detection whether an incoming object is identical to one of inactive objects out of image.

A Study on Optical Condition and preprocessing for Input Image Improvement of Dented and Raised Characters of Tires (타이어 음,양각 문자의 입력영상 개선을 위한 전처리와 광학조건에 관한 연구)

  • 류한성;최중경;구본민;박무열;윤경섭
    • Proceedings of the IEEK Conference
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    • 2001.06d
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    • pp.93-96
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    • 2001
  • In this paper, we present a vision algorithm and method for input image improvement and preprocessing of dented and raised characters on the sidewall of tires. we define optical condition between reflect coefficient and reflectance by the physical vector calculate. On the contrary this work will recognize the engraved characters using the computer vision technique. Tire input images have all most same grey levels between the characters and backgrounds. The reflectance is little from a tire surface. therefore, it's very difficult segment the characters from the background. Moreover, one side of the character string is raised and the other is dented. So, the captured images are varied with the angle of camera and illumination. For optimum input images, the angle between camera and illumination was found out to be with in 90。 .In addition, We used complex filtering with low-pass and high-pass band filters to improve input images, for clear input images. Finally we define equation reflect coefficient and reflectance. By doing this, we obtained good images of tires for pattern recognition.

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Development of Human Following Method of Mobile Robot Using QR Code and 2D LiDAR Sensor (QR 2D 코드와 라이다 센서를 이용한 모바일 로봇의 사람 추종 기법 개발)

  • Lee, SeungHyeon;Choi, Jae Won;Van Dang, Chien;Kim, Jong-Wook
    • IEMEK Journal of Embedded Systems and Applications
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    • v.15 no.1
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    • pp.35-42
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    • 2020
  • In this paper, we propose a method to keep the robot at a distance of 30 to 45cm from the user in consideration of each individual's minimum area and inconvenience by using a 2D LiDAR sensor LDS-01 as the secondary sensor along with a QR code. First, the robot determines the brightness of the video and the presence of a QR code. If the light is bright and there is a QR code due to human's presence, the range of the 2D LiDAR sensor is set based on the position of the QR code in the captured image to find and follow the correct target. On the other hand, when the robot does not recognize the QR code due to the low light, the target is followed using a database that stores obstacles and human actions made before the experiment using only the 2D LiDAR sensor. As a result, our robot can follow the target person in four situations based on nine locations with seven types of motion.

Neural Network-Based Human Identification Using Teeth Contours (치아 윤곽선 정보를 이용한 신경회로망 기반 신원 확인 방안)

  • Park, Sang-Jin;Park, Hyungjun
    • Korean Journal of Computational Design and Engineering
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    • v.18 no.4
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    • pp.275-282
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    • 2013
  • This paper proposes a method for human identification using teeth contours extracted from dental images that are captured from the frontal views of subjects each of who opens his or her mouth slightly. Each dental image has a black-colored region containing the subject's teeth contours which are usually different from subject to subject. This means that this black-colored region has bio-mimetic information useful for human identification. The basic idea of the method is to extract the upper and lower teeth contours from the dental image of each subject and to encode their geometric patterns using a back-propagation neural network model. After acquiring 400 teeth images form 10 university students, we used 300 images for the training data of the neural network model and 100 images for its verification. Experimental results have shown that the proposed neural network-based method can be used as an alternative solution for identification among a small group of humans with a low cost and simple setup.

Antiblurry Dejitter Image Stabilization Method of Fuzzy Video for Driving Recorders

  • Xiong, Jing-Ying;Dai, Ming;Zhao, Chun-Lei;Wang, Ruo-Qiu
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.11 no.6
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    • pp.3086-3103
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    • 2017
  • Video images captured by vehicle cameras often contain blurry or dithering frames due to inadvertent motion from bumps in the road or by insufficient illumination during the morning or evening, which greatly reduces the perception of objects expression and recognition from the records. Therefore, a real-time electronic stabilization method to correct fuzzy video from driving recorders has been proposed. In the first stage of feature detection, a coarse-to-fine inspection policy and a scale nonlinear diffusion filter are proposed to provide more accurate keypoints. Second, a new antiblurry binary descriptor and a feature point selection strategy for unintentional estimation are proposed, which brought more discriminative power. In addition, a new evaluation criterion for affine region detectors is presented based on the percentage interval of repeatability. The experiments show that the proposed method exhibits improvement in detecting blurry corner points. Moreover, it improves the performance of the algorithm and guarantees high processing speed at the same time.

Experimental Study on Variations in Behavior of Green Water and Flow Kinematics on Deck with Various Flare Angles (플레어 각도에 따른 청수현상의 발생과정 및 갑판 위 유동특성 변화에 대한 실험적 연구)

  • Lee, Gang Nam;Jung, Kwang Hyo;Suh, Sung Bu;Kim, Mun Sung
    • Journal of Ocean Engineering and Technology
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    • v.32 no.2
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    • pp.77-83
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    • 2018
  • In this study, a series of experiments were performed to investigate the variations in the behavior of green water generation and the flow kinematics of bubbly flow on deck with various flare angles. The experiments were conducted in a 2-D wave flume using a simplified model of a BW Pioneer FPSO operating in the Gulf of Mexico, with a 100-year return period wave condition. The green water phenomena were captured with a high speed CCD camera. The variations in the behavior of the green water generation were investigated with various flare angles, and the horizontal mean velocity profiles of bubbly flow on deck obtained using bubble image velocimetry (BIV) were provided. The differences in flow kinematics of bubbly flow on deck were analyzed with various flare angles.

Measurement of Breast Volume and the Area of Breast Base Using 3D Measurement System (3차원 측정시스템을 이용한 유방부피 및 유저면적의 측정)

  • 이현영;이옥경;홍경희
    • Journal of the Korean Society of Clothing and Textiles
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    • v.27 no.2
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    • pp.270-276
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    • 2003
  • Methodology was suggested to analyze breast volume, base area of breast bulk. and surface area of breast using the 3D measurement system. Thirty-seven middle-aged (30s-40s) women wearing 80A brassiere were participated in this study. Image of the upper body was captured by Phase-shifting moire. The posture of the subject was adjusted to get the full image of the right breast. Rapidform 2001 was used for the analysis of the images. The mean breast volume was 547.0㎤ and mean base area of breast bulk was 235. I$\textrm{cm}^2$ It was also found that the volume(r=0.169) and surface area of breast(r=10.242) were loosely correlated with the circumference difference between top and under breast. Therefore, it is noted that current selection criterion of cup size based on the difference in the two kinds of breast circumference is inadequate. The result of this study is expected to contribute to the design of ergonomic brassiere as well as surgical operations in the medical field.

TheReviser : A Gesture-based Editing System on a Digital Desk (TheReviser : 가상 데스크 상의 제스처 기반 문서 교정 시스템)

  • Jung, Ki-Chul;Kang, Hyun
    • The KIPS Transactions:PartB
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    • v.11B no.4
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    • pp.527-536
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    • 2004
  • TheReviser is a digital document revision application on a projection display, which allows us to interact a digital document with the same gestures used for paper documents revision. To enable these interactions, TheReviser should detect foreground objects such as hands or pens on a projection display, and should spot and recognize gesture commands from continuous movements of a user. To detect foreground objects from a complex background in various lighting conditions, we perform geometry and color calibration between a captured image and a frame buffer image. TheReviser uses an HMM-based gesture recognition method Experimental results show that the proposed application recognizes user's gestures on average 93.22% in test gesture sequences.

Visibility Enhancement of Underwater Image Using a Color Transform Model (색상 변환 모델을 이용한 수중 영상의 가시성 개선)

  • Jang, Ik-Hee;Park, Jeong-Seon
    • The Journal of the Korea institute of electronic communication sciences
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    • v.10 no.5
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    • pp.645-652
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    • 2015
  • In underwater, such as fish farm and sea, turbidity is increased by water droplets and various suspended, therefore light attenuation occurs depending on the depth also caused by the scattering effect of light float. In this paper, in order to improve the visibility of underwater images obtained from these aquatic environment, we propose a visibility enhancement method using a haze removal method based on dark channel prior and a trained color transform model. In order to train a color transform model, we used underwater pattern images captured from Pohang and Yeosu, and to measure the performance of the proposed method, we carried out experiment of visibility enhancement using underwater images collected from Yeosu, Geomundo and Philippines. The results show that the proposed method can improve the visibility of underwater images of various locations.