• 제목/요약/키워드: Detecting Algorithm

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ALT기법을 이용한 ITO 코팅유리의 결함 검출 기법 개발 (Development of Scratch Detecting Algorithm for ITO Coated Glass using Adaptive Logical Thresholding Method)

  • 김면희;이상룡
    • 한국정밀공학회지
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    • 제20권8호
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    • pp.108-114
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    • 2003
  • This research describes a image-processing technique for the scratch detecting algorithm for ITO coated glass. We use the modified logical thresholding method (called adaptive logical thresholding method) for binarization of gray-scale glass image. This method is useful to the algorithm for detecting the scratch of ITO coated glass automatically without need of any prior information of manual fine-tuning of parameters.

Robot Fish Tracking Control using an Optical Flow Object-detecting Algorithm

  • Shin, Kyoo Jae
    • IEIE Transactions on Smart Processing and Computing
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    • 제5권6호
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    • pp.375-382
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    • 2016
  • This paper realizes control of the motion of a swimming robot fish in order to implement an underwater robot fish aquarium. And it implements positional control of a two-axis trajectory path of the robot fish in the aquarium. The performance of the robot was verified though certified field tests. It provided excellent performance in driving force, durability, and water resistance in experimental results. It can control robot motion, that is, it recognizes an object by using an optical flow object-detecting algorithm, which uses a video camera rather than image-detecting sensors inside the robot fish. It is possible to find the robot's position and control the motion of the robot fish using a radio frequency (RF) modem controlled via personal computer. This paper proposes realization of robot fish motion-tracking control using the optical flow object-detecting algorithm. It was verified via performance tests of lead-lag action control of robot fish in the aquarium.

레이저레이더 센서를 이용한 철도 건널목 지장물 검지 알고리즘 개발 (Algorithm Development of Level Crossing Obstacle Detection using Laser Radar Sensor)

  • 김영준;백종현;최규형
    • 전기학회논문지
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    • 제62권12호
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    • pp.1813-1819
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    • 2013
  • Existing level crossing obstacle detecting system was installed using a laser beam. Level crossing obstacle detecting system using a laser beam that has been a problem in relation to safety and maintainability failure according to weather conditions. We proposed laser radar level crossing obstacle detecting system as a way to overcome problem, and we developed an algorithm for this. Level crossing obstacle detecting system using a laser radar sensor algorithm is robust to external environment and a shadow zone does not exist. Sensor part of the laser radar level crossing obstacle detecting system of these is made up by the image processing unit and laser radar sensor, it operations by receiving train entering information from the control unit. In this paper, we proposed a detecting algorithm with calculation of the size of the laser radar sensor. Based on this, we were performance test on the basis of the scenario by making a prototype. In the future, laser radar level crossing obstacle detecting system to ensure the safety and reliability through the field test.

노상 주차 차량 탐지를 위한 YOLOv4 그리드 셀 조정 알고리즘 (YOLOv4 Grid Cell Shift Algorithm for Detecting the Vehicle at Parking Lot)

  • 김진호
    • 디지털산업정보학회논문지
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    • 제18권4호
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    • pp.31-40
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    • 2022
  • YOLOv4 can be used for detecting parking vehicles in order to check a vehicle in out-door parking space. YOLOv4 has 9 anchor boxes in each of 13x13 grid cells for detecting a bounding box of object. Because anchor boxes are allocated based on each cell, there can be existed small observational error for detecting real objects due to the distance between neighboring cells. In this paper, we proposed YOLOv4 grid cell shift algorithm for improving the out-door parking vehicle detection accuracy. In order to get more chance for trying to object detection by reducing the errors between anchor boxes and real objects, grid cells over image can be shifted to vertical, horizontal or diagonal directions after YOLOv4 basic detection process. The experimental results show that a combined algorithm of a custom trained YOLOv4 and a cell shift algorithm has 96.6% detection accuracy compare to 94.6% of a custom trained YOLOv4 only for out door parking vehicle images.

Bayesian Image Reconstruction Using Edge Detecting Process for PET

  • Um, Jong-Seok
    • 한국멀티미디어학회논문지
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    • 제8권12호
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    • pp.1565-1571
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    • 2005
  • Images reconstructed with Maximum-Likelihood Expectation-Maximization (MLEM) algorithm have been observed to have checkerboard effects and have noise artifacts near edges as iterations proceed. To compensate this ill-posed nature, numerous penalized maximum-likelihood methods have been proposed. We suggest a simple algorithm of applying edge detecting process to the MLEM and Bayesian Expectation-Maximization (BEM) to reduce the noise artifacts near edges and remove checkerboard effects. We have shown by simulation that this algorithm removes checkerboard effects and improves the clarity of the reconstructed image and has good properties based on root mean square error (RMS).

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Development of scratch detecting algorithm for ITO coated glass Using image processing technique

  • Kim, Myun-Hee;Bae, Joon-Young;Park, Se-Hong;Lee, Sang-Ryong
    • 한국정보디스플레이학회:학술대회논문집
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    • 한국정보디스플레이학회 2002년도 International Meeting on Information Display
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    • pp.849-851
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    • 2002
  • This research describes a image-processing technique for the scratch detecting algorithm for ITO coated glass. We use the modified logical thresholding method for binarization of gray-scale glass image. This method is useful to the algorithm for detecting the scratch of ITO coated glass automatically without need of any prior information of manual fine-tuning of parameters.

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상관함수 기반 굴삭기용 과부하 검출 기법 (An Overload Detecting Method for an Excavator Based on the Correlation Function)

  • 유창호;고남곤;최재원;서영봉
    • 제어로봇시스템학회논문지
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    • 제16권7호
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    • pp.703-710
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    • 2010
  • In this paper, an overload detecting algorithm for an excavator is presented. The proposed overload detecting algorithm is based on the time series analysis especially correlation function. The main purpose of this paper is to prevent damage or crack from the fatigue loaded on an excavator in advance. Generally, the larger data, the longer processing time, and the amount of the data used in this paper are also large, especially every sampling period, 1600 data are gathered and calculated. So this paper focuses on minimizing the number of required sensors by using the correlation function. From the cross correlation function, similar pattern sensors are eliminated and dissimilar pattern sensors are considered, and from the auto correlation function, the overload can be detected. To prove the efficiency of the proposed overload detecting algorithm, this paper shows the computer simulation results.

Moving Window 기반 굴삭기용 과부하 검출 알고리즘 (Moving Window Based Overload Detection Algorithm for Excavator)

  • 유창호;최재원;서영봉
    • 대한기계학회:학술대회논문집
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    • 대한기계학회 2007년도 춘계학술대회A
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    • pp.909-914
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    • 2007
  • In this paper, an overload detecting algorithm for an excavator is presented. The proposed overload detecting algorithm is based on the time series analysis especially moving window. The main purpose of this paper is to prevent a damage or crack from the fatigue in advance. 16 channel sensors data are considered and maximum stress is computed by a sensor fusion method every moving window. After the maximum stress every window is compared with a given threshold, this overload detecting algorithm decides overload or not.

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Advanced Lane Detecting Algorithm for Unmanned Vehicle

  • Moon, Hee-Chang;Lee, Woon-Sung;Kim, Jung-Ha
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2003년도 ICCAS
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    • pp.1130-1133
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    • 2003
  • The goal of this research is developing advanced lane detecting algorithm for unmanned vehicle. Previous lane detecting method to bring on error become of the lane loss and noise. Therefore, new algorithm developed to get exact information of lane. This algorithm can be used to AGV(Autonomous Guide Vehicle) and LSWS(Lane Departure Warning System), ACC(Adapted Cruise Control). We used 1/10 scale RC car to embody developed algorithm. A CCD camera is installed on top of vehicle. Images are transmitted to a main computer though wireless video transmitter. A main computer finds information of lane in road image. And it calculates control value of vehicle and transmit these to vehicle. This algorithm can detect in input image marked by 256 gray levels to get exact information of lane. To find the driving direction of vehicle, it search line equation by curve fitting of detected pixel. Finally, author used median filtering method to removal of noise and used characteristic part of road image for advanced of processing time.

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변류기 포화검출 알고리즘을 적용한 모선보호용 비율전류차동 계전방식 (A Percentage Differential Current Relaying Algorithm for Bus Protection Using Current Transformer Saturation Detecting Algorithm)

  • 강용철;윤재성;옥승훈
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2001년도 추계학술대회 논문집 전력기술부문
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    • pp.115-117
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    • 2001
  • A percentage current differential relaying algorithm is widely used for bus protection. However, it may maloperate external faults with CT saturation. This paper proposes a percentage current differential relaying algorithm for bus protection using CT saturation detecting algorithm. The CT saturation detecting algorithm uses difference of secondary current of CT and detects CT saturation. The proposed method distinguishes percentage differential relay operation caused by faults from percentage differential relay operation caused by CT saturations.

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