• 제목/요약/키워드: Real-time Recognition

검색결과 1,403건 처리시간 0.03초

레이저 테일러드 브랭크 용접의 실시간 품질판단 및 통계프로그램에 관한 연구 (A study on the real time quality estimation in laser tailored blank welding)

  • 박영환;이세헌;박현성
    • 대한기계학회:학술대회논문집
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    • 대한기계학회 2001년도 추계학술대회논문집A
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    • pp.791-796
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    • 2001
  • Welding using lasers can be mass-produced in high speed. In the laser welding, performing real-time evaluation of the welding quality is very important in enhancing the efficiency of welding. In this study, the plasma and molten metal which are generated during laser welding were measured using the UV sensor and IR sensor. The results of laser welding were classified into five categories such as optimal heat input, little low heat input, low heat input, focus off, and nozzle change. Also, a system was formulated which uses the measured signals with a fuzzy pattern recognition method which is used to perform real-time evaluation of the welding quality and the defects which can occur in laser welding. Weld quality prediction program was developed using previous weld results and statistical program which could show the trend of weld quality and signal was developed.

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SLM과 광굴절 결정(LiNbO$_3$)을 이용하여 실현된 실시간 칼라 패턴인식 시스템 (The real-time color pattern recognition system using an SLM and photorefractive crystal(LiNbO$_3$))

  • 윤진선;김남
    • 한국통신학회논문지
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    • 제27권3B호
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    • pp.267-274
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    • 2002
  • 본 논문에서는 SLM(TFT LCD)과 광굴절 결정을 이용하며 실시간으로 처리할 수 있는 칼라 패턴인식 시스템을 구현하였다. 이 시스템은 인식하고자 하는 문자패턴을 SLM을 이용하여 제어하고, 우수한 각도 선택성과 광굴절 특성을 갖는 LiNbO$_3$(두께 10mm) 결정을 기록 매질로 사용하였다. 제안된 광학 시스템에 의해 빨간색과 녹색 칼라 패턴의 모양 정보와 칼라 정보를 각각 다른 위치에서 실시간 처리로 확연히 판별해서 인식할 수 있었다.

스테레오 화상데이타의 정합기법 이용한 주행장애물의 인식 (Recognition of Obstacles under Dring Vehicles using Stereo Image matching Techniques)

  • 김종만;김원섭
    • 한국전기전자재료학회:학술대회논문집
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    • 한국전기전자재료학회 2007년도 추계학술대회 논문집
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    • pp.508-509
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    • 2007
  • For the safty driving of an automobile which is become individual requisites, a new Neural Network algorithm which recognized the load vehicles in real time is proposed. The proposed neural network technique is the real time computation method through the inter-node diffusion. The most reliable algorithm derived for real time recognition of vehicles, is a dynamic programming based algorithm based on sequence matching techniques that would process the data as it arrives and could therefore provide continuously updated neighbor information estimates.

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비주얼 서보잉을 위한 딥러닝 기반 물체 인식 및 자세 추정 (Object Recognition and Pose Estimation Based on Deep Learning for Visual Servoing)

  • 조재민;강상승;김계경
    • 로봇학회논문지
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    • 제14권1호
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    • pp.1-7
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    • 2019
  • Recently, smart factories have attracted much attention as a result of the 4th Industrial Revolution. Existing factory automation technologies are generally designed for simple repetition without using vision sensors. Even small object assemblies are still dependent on manual work. To satisfy the needs for replacing the existing system with new technology such as bin picking and visual servoing, precision and real-time application should be core. Therefore in our work we focused on the core elements by using deep learning algorithm to detect and classify the target object for real-time and analyzing the object features. We chose YOLO CNN which is capable of real-time working and combining the two tasks as mentioned above though there are lots of good deep learning algorithms such as Mask R-CNN and Fast R-CNN. Then through the line and inside features extracted from target object, we can obtain final outline and estimate object posture.

스테레오 비전 기반의 이동객체용 실시간 환경 인식 시스템 (Investigation on the Real-Time Environment Recognition System Based on Stereo Vision for Moving Object)

  • 이충희;임영철;권순;이종훈
    • 대한임베디드공학회논문지
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    • 제3권3호
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    • pp.143-150
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    • 2008
  • In this paper, we investigate a real-time environment recognition system based on stereo vision for moving object. This system consists of stereo matching, obstacle detection and distance estimation. In stereo matching part, depth maps can be obtained real road images captured adjustable baseline stereo vision system using belief propagation(BP) algorithm. In detection part, various obstacles are detected using only depth map in case of both v-disparity and column detection method under the real road environment. Finally in estimation part, asymmetric parabola fitting with NCC method improves estimation of obstacle detection. This stereo vision system can be applied to many applications such as unmanned vehicle and robot.

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필터뱅크를 이용한 한국어 숫자음 인식에 관한 연구 (A Study on the Recognition of Korean Digits using Filter-Bank)

  • 김홍식;한득영
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1989년도 추계학술대회 논문집 학회본부
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    • pp.481-483
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    • 1989
  • This paper is concentrated on the recognition of Korean Digits. The speech signals of each of digits are fed into computer through the 18 bandpass filters, AD converter. Spectrum input data are analyzed and used. BASIC program language is used for recognition performance and the result of recognition is outputed to computer screen and printer. In this paper, the strength and weakness of filter-bank analysis method is described and the technique of real-time recognition is argued. In this experiment, Ratio of recognition for speaker dependent recognition was about 97% and recognition time was also satisfied. Therefore, A way of speaker independent recognition will be presented and using for special communication in the future.

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A Decision Tree based Real-time Hand Gesture Recognition Method using Kinect

  • Chang, Guochao;Park, Jaewan;Oh, Chimin;Lee, Chilwoo
    • 한국멀티미디어학회논문지
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    • 제16권12호
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    • pp.1393-1402
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    • 2013
  • Hand gesture is one of the most popular communication methods in everyday life. In human-computer interaction applications, hand gesture recognition provides a natural way of communication between humans and computers. There are mainly two methods of hand gesture recognition: glove-based method and vision-based method. In this paper, we propose a vision-based hand gesture recognition method using Kinect. By using the depth information is efficient and robust to achieve the hand detection process. The finger labeling makes the system achieve pose classification according to the finger name and the relationship between each fingers. It also make the classification more effective and accutate. Two kinds of gesture sets can be recognized by our system. According to the experiment, the average accuracy of American Sign Language(ASL) number gesture set is 94.33%, and that of general gestures set is 95.01%. Since our system runs in real-time and has a high recognition rate, we can embed it into various applications.

MEMS 기술로 제작된 가스 센서 어레이를 이용한 유해가스 분류를 위한 간단한 통계적 패턴인식방법의 구현 (Implementation of simple statistical pattern recognition methods for harmful gases classification using gas sensor array fabricated by MEMS technology)

  • 변형기;신정숙;이호준;이원배
    • 센서학회지
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    • 제17권6호
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    • pp.406-413
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    • 2008
  • We have been implemented simple statistical pattern recognition methods for harmful gases classification using gas sensors array fabricated by MEMS (Micro Electro Mechanical System) technology. The performance of pattern recognition method as a gas classifier is highly dependent on the choice of pre-processing techniques for sensor and sensors array signals and optimal classification algorithms among the various classification techniques. We carried out pre-processing for each sensor's signal as well as sensors array signals to extract features for each gas. We adapted simple statistical pattern recognition algorithms, which were PCA (Principal Component Analysis) for visualization of patterns clustering and MLR (Multi-Linear Regression) for real-time system implementation, to classify harmful gases. Experimental results of adapted pattern recognition methods with pre-processing techniques have been shown good clustering performance and expected easy implementation for real-time sensing system.

증강현실 기반 아동 학습 어플리케이션을 위한 실시간 영상 인식 (Real-Time Object Recognition for Children Education Applications based on Augmented Reality)

  • 박강규;이강
    • 한국멀티미디어학회논문지
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    • 제20권1호
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    • pp.17-31
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    • 2017
  • The aim of the paper is to present an object recognition method toward augmented reality system that utilizes existing education instruments that was designed without any consideration on image processing and recognition. The light reflection, sizes, shapes, and color range of the existing target education instruments are major hurdles to our object recognition. In addition, the real-time performance requirements on embedded devices and user experience constraints for children users are quite challenging issues to be solved for our image processing and object recognition approach. In order to meet these requirements we employed a method cascading light-weight weak classification methods that are complimentary each other to make a resultant complicated and highly accurate object classifier toward practically reasonable precision ratio. We implemented the proposed method and tested the performance by video with more than 11,700 frames of actual playing scenario. The experimental result showed 0.54% miss ratio and 1.35% false hit ratio.

A Prototype Design for a Real-time VR Game with Hand Tracking Using Affordance Elements

  • Yu-Won Jeong
    • 한국컴퓨터정보학회논문지
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    • 제29권5호
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    • pp.47-53
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    • 2024
  • 본 연구는 어포던스 개념을 적용하여 가상 환경에서의 제스처 인식 과정에서 자연스러운 동작을 유도함으로써 상호작용과 몰입감을 향상하기 위한 인터랙티브 기술 활용을 제안한다. 이를 위해 샘플링 및 정규화 과정을 포함한 선분 인식 알고리즘을 활용하여 실제 손동작과 유사한 제스처를 인식하는 기법을 제안한다. 이러한 선분 인식은 본 논문에서 설계한 <VR Spell> 게임에서 마법진을 그리는 동작에 적용되었다. 실험 방법으로는 4개의 선분 인식 동작에 대한 인식률을 검증하였다. 본 논문은 실시간 핸드 트래킹 기술을 가상 환경, 특히 VR 게임과 같은 실감 콘텐츠에 적용하여 사용자에게 더 높은 몰입감과 재미를 추구하는 VR 게임을 제안하고자 한다.