• Title/Summary/Keyword: Front detection

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Analysis of EMI Between Overlapped Railway Signalling Systems and Its Countermeasure (철도신호시스템 중첩운영으로 인한 전자파장해현상 분석 및 대책)

  • Kho, Young-Hwan;Yoon, Sun-Ho;Choi, Kyu-Hyoung
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.58 no.6
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    • pp.1116-1122
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    • 2009
  • ATS(Automatic Train Stop) system makes train stop when it runs over the speed limit and ensure the safe operation of train. Seoul Metro line 2 in Korea, which started its passenger service in 1982, has adopted ATS system for its signaling system. The ATS system has only a train stop function at the time of emergency, and Seoul Metro is planning to replaced them with ATC(Automatic Train Control)/ATO(Automatic Train Operation) system which can provide the dedicated speed control for headway reduction and automatic operation of train. Until all the ATS system is replaced with the new ATC system, both systems are to operate simultaneously at the same metro line. In this situation, ATS system sometimes reveals improper operation: train stops suddenly without any obstacles in front of it. These emergency stops cause interruption of passenger service, and abnormal abrasion of wheels and rail. This paper makes it clear that these interruptions are caused by EMI phenomena between ATS on-board device and ATC wayside device : Signal current flowing in AF track circuit of ATC is turn out to be a EMI source that prevent normal operation of the ATS on-board device. Although the two systems have different frequency-ranges (ATS system has frequency range between $78{\sim}130$[kHz] and ATC system has frequency range between $9.5{\sim}16.5$[kHz]), it turned out that EMI phenomena appears between the both systems. This is investigated by measuring the output signal from ATS on-board device passing over ATC wayside device. The FFT(Fast Fourier Transform) analysis of the signal reveals that AF track circuit signal is transmitted to the ATS on-board device and induce noise causing improper operation. The countermeasures to the EMI phenomena are examined in three ways; blocking EMI transmission, enforcement of EMS (Electromagnetic Susceptibility) of ATS on-board device, and blocking the EMI source. It is suggested that the practical solution be blocking EMI source temporarily, that is breaking AF track circuit signal when the trains with ATS on-board device pass over it. To this purpose, TODS(Train Occupation Detection System) is developed, and has made a success in preventing the EMI problem of Seoul Metro line 2.

Adaptive Vehicle License Plate Recognition System Using Projected Plane Convolution and Decision Tree Classifier (투영면 컨벌루션과 결정트리를 이용한 상태 적응적 차량번호판 인식 시스템)

  • Lee Eung-Joo;Lee Su Hyun;Kim Sung-Jin
    • Journal of Korea Multimedia Society
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    • v.8 no.11
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    • pp.1496-1509
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    • 2005
  • In this paper, an adaptive license plate recognition system which detects and recognizes license plate at real-time by using projected plane convolution and Decision Tree Classifier is proposed. And it was tested in circumstances which presence of complex background. Generally, in expressway tollgate or gateway of parking lots, it is very difficult to detect and segment license plate because of size, entry angle and noisy problem of vehicles due to CCD camera and road environment. In the proposed algorithm, we suggested to extract license plate candidate region after going through image acquisition process with inputted real-time image, and then to compensate license size as well as gradient of vehicle with change of vehicle entry position. The proposed algorithm can exactly detect license plate using accumulated edge, projected convolution and chain code labeling method. And it also segments letter of license plate using adaptive binary method. And then, it recognizes license plate letter by applying hybrid pattern vector method. Experimental results show that the proposed algorithm can recognize the front and rear direction license plate at real-time in the presence of complex background environments. Accordingly license plate detection rate displayed $98.8\%$ and $96.5\%$ successive rate respectively. And also, from the segmented letters, it shows $97.3\%$ and $96\%$ successive recognition rate respectively.

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Development of Recognition Application of Facial Expression for Laughter Theraphy on Smartphone (스마트폰에서 웃음 치료를 위한 표정인식 애플리케이션 개발)

  • Kang, Sun-Kyung;Li, Yu-Jie;Song, Won-Chang;Kim, Young-Un;Jung, Sung-Tae
    • Journal of Korea Multimedia Society
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    • v.14 no.4
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    • pp.494-503
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    • 2011
  • In this paper, we propose a recognition application of facial expression for laughter theraphy on smartphone. It detects face region by using AdaBoost face detection algorithm from the front camera image of a smartphone. After detecting the face image, it detects the lip region from the detected face image. From the next frame, it doesn't detect the face image but tracks the lip region which were detected in the previous frame by using the three step block matching algorithm. The size of the detected lip image varies according to the distance between camera and user. So, it scales the detected lip image with a fixed size. After that, it minimizes the effect of illumination variation by applying the bilateral symmetry and histogram matching illumination normalization. After that, it computes lip eigen vector by using PCA(Principal Component Analysis) and recognizes laughter expression by using a multilayer perceptron artificial network. The experiment results show that the proposed method could deal with 16.7 frame/s and the proposed illumination normalization method could reduce the variations of illumination better than the existing methods for better recognition performance.

The Realization on GAS Sensor Module for Inteligent Wireless Communication (지능형 무선통신용 가스 센서 모듈 구현)

  • Kim, Hyo-Chan;Weon, Young-Su;Cho, Hyung-Rae
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.11 no.6
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    • pp.123-132
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    • 2012
  • Gas sensors has been used very differently that depending on following purposes; Automotive (exhaust gas, fuel mixture gas, oxygen, particulates), agriculture / food industry (fresh, stored, CO2, humidity, NH3, nitrogen oxide gas, organic gas, toxic gas emitted from pesticides and insecticides), industrial / medical (chemical gas, hydrogen, oxygen and toxic gases), military (chemical weapon), environmental measurements (CO and other air pollution consisting of sulfur and nitrogen gas), residential (LNG, LPG, butane, indoor air, humidity). The types of industrial toxic substances are known about 700 species and many of these exist in gaseous form under normal conditions. he multi-gas detection sensors will be developed for casualties that detect the most important and find easy three kinds of gases in marine plant; carbon dioxide(CO2), carbon(CO), ammonia(NH3). Package block consists of gas sensing device minor ingredient, rf front end, zigbee chip. Develope interworking technology between the sensor and zigbee chip inside a package. Conduct a performance test through test jig about prototype zigbee sensor module with rf output power and unwanted emission test. This research task available early address when poisonous gas leaked from large industrial site and contribution for workers' safety at the enclosed space.

A study on the improvement of artificial intelligence-based Parking control system to prevent vehicle access with fake license plates (위조번호판 부착 차량 출입 방지를 위한 인공지능 기반의 주차관제시스템 개선 방안)

  • Jang, Sungmin;Iee, Jeongwoo;Park, Jonghyuk
    • Journal of Intelligence and Information Systems
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    • v.28 no.2
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    • pp.57-74
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    • 2022
  • Recently, artificial intelligence parking control systems have increased the recognition rate of vehicle license plates using deep learning, but there is a problem that they cannot determine vehicles with fake license plates. Despite these security problems, several institutions have been using the existing system so far. For example, in an experiment using a counterfeit license plate, there are cases of successful entry into major government agencies. This paper proposes an improved system over the existing artificial intelligence parking control system to prevent vehicles with such fake license plates from entering. The proposed method is to use the degree of matching of the front feature points of the vehicle as a passing criterion using the ORB algorithm that extracts information on feature points characterized by an image, just as the existing system uses the matching of vehicle license plates as a passing criterion. In addition, a procedure for checking whether a vehicle exists inside was included in the proposed system to prevent the entry of the same type of vehicle with a fake license plate. As a result of the experiment, it showed the improved performance in identifying vehicles with fake license plates compared to the existing system. These results confirmed that the methods proposed in this paper could be applied to the existing parking control system while taking the flow of the original artificial intelligence parking control system to prevent vehicles with fake license plates from entering.

Implementation of AI-based Object Recognition Model for Improving Driving Safety of Electric Mobility Aids (전동 이동 보조기기 주행 안전성 향상을 위한 AI기반 객체 인식 모델의 구현)

  • Je-Seung Woo;Sun-Gi Hong;Jun-Mo Park
    • Journal of the Institute of Convergence Signal Processing
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    • v.23 no.3
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    • pp.166-172
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    • 2022
  • In this study, we photograph driving obstacle objects such as crosswalks, side spheres, manholes, braille blocks, partial ramps, temporary safety barriers, stairs, and inclined curb that hinder or cause inconvenience to the movement of the vulnerable using electric mobility aids. We develop an optimal AI model that classifies photographed objects and automatically recognizes them, and implement an algorithm that can efficiently determine obstacles in front of electric mobility aids. In order to enable object detection to be AI learning with high probability, the labeling form is labeled as a polygon form when building a dataset. It was developed using a Mask R-CNN model in Detectron2 framework that can detect objects labeled in the form of polygons. Image acquisition was conducted by dividing it into two groups: the general public and the transportation weak, and image information obtained in two areas of the test bed was secured. As for the parameter setting of the Mask R-CNN learning result, it was confirmed that the model learned with IMAGES_PER_BATCH: 2, BASE_LEARNING_RATE 0.001, MAX_ITERATION: 10,000 showed the highest performance at 68.532, so that the user can quickly and accurately recognize driving risks and obstacles.

Realization on the Integrated System of Navigation Communication and Fish Finder for Safety Operation of Fishing Vessel (어선의 안전조업을 위한 항해통신 및 어탐기의 통합시스템 구현)

  • In-suk Kang;In-ung Ju;Jeong-yeon Kim;Jo-cheon Choi
    • Journal of Advanced Navigation Technology
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    • v.25 no.6
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    • pp.433-440
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    • 2021
  • The problem of maritime accidents due to the carelessness of fishing vessels, which is affected by the aging of fishing vessel operators. And there is navigation, communication and fish finder that is installed inside the narrow bridge of a fishing vessel. Therefore these system are monitors as many as of each terminal, which is bad influence on obscuring view of front sea from a fishing vessel bridge. In addition a large problem, it is occurs to reduce of the information recognition ability due to the confusion, which is can not check the display information each of screen equipments. Therefore, there has been demand to simply integrated the equipment, and it has wanted the integrated support system of these equipment. The display must be provided on a fishing vessels such as electronic charts, communications equipments and fish detection into one case. In this paper, the integrated system will be installed the GPS plotter, AIS, VHF-DSC, V-pass, fish finder and power supply in the narrow wheelhouse on a fishing vessel, which is configured in one case and operated by multi function display (MFD). The MFD is integrated to simplify for several multi terminals and provided necessary information on a single screen. This integration fishery support system will has improved in sea safety operation and fishery environment of fishing vessels by this implementation.

Implementation of AI-based Object Recognition Model for Improving Driving Safety of Electric Mobility Aids (객체 인식 모델과 지면 투영기법을 활용한 영상 내 다중 객체의 위치 보정 알고리즘 구현)

  • Dong-Seok Park;Sun-Gi Hong;Jun-Mo Park
    • Journal of the Institute of Convergence Signal Processing
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    • v.24 no.2
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    • pp.119-125
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    • 2023
  • In this study, we photograph driving obstacle objects such as crosswalks, side spheres, manholes, braille blocks, partial ramps, temporary safety barriers, stairs, and inclined curb that hinder or cause inconvenience to the movement of the vulnerable using electric mobility aids. We develop an optimal AI model that classifies photographed objects and automatically recognizes them, and implement an algorithm that can efficiently determine obstacles in front of electric mobility aids. In order to enable object detection to be AI learning with high probability, the labeling form is labeled as a polygon form when building a dataset. It was developed using a Mask R-CNN model in Detectron2 framework that can detect objects labeled in the form of polygons. Image acquisition was conducted by dividing it into two groups: the general public and the transportation weak, and image information obtained in two areas of the test bed was secured. As for the parameter setting of the Mask R-CNN learning result, it was confirmed that the model learned with IMAGES_PER_BATCH: 2, BASE_LEARNING_RATE 0.001, MAX_ITERATION: 10,000 showed the highest performance at 68.532, so that the user can quickly and accurately recognize driving risks and obstacles.

Considerations of Environmental Factors Affecting the Detection of Underwater Acoustic Signals in the Continental Regions of the East Coast Sea of Korea

  • Na, Young-Nam;Kim, Young-Gyu;Kim, Young-Sun;Park, Joung-Soo;Kim, Eui-Hyung;Chae, Jin-Hyuk
    • The Journal of the Acoustical Society of Korea
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    • v.20 no.2E
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    • pp.30-45
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    • 2001
  • This study considers the environmental factors affecting propagation loss and sonar performance in the continental regions of the East Coast Sea of Korea. Water mass distributions appear to change dramatically in a few weeks. Simple calculation with the case when the NKCW (North Korean Cold Water) develops shows that the difference in propagation loss may reach in the worst up to 10dB over range 5km. Another factor, an eddy, has typical dimensions of 100-200km in diameter and 150-200m in thickness. Employing a typical eddy and assuming frequency to be 100Hz, its effects on propagation loss appear to make lower the normal formation of convergence zones with which sonars are possible to detect long-range targets. The change of convergence zones may result in 10dB difference in received signals in a given depth. Thermal fronts also appear to be critical restrictions to operating sonars in shallow waters. Assuming frequency to be 200Hz, thermal fronts can make 10dB difference in propagation loss between with and without them over range 20km. An observation made in one site in the East Coast Sea of Korea reveals that internal waves may appear in near-inertial period and their spectra may exist in periods 2-17min. A simulation employing simple internal wave packets gives that they break convergence zones on the bottom, causing the performance degradation of FOM as much as 4dB in frequency 1kHz. An acoustic experiment, using fixed source and receiver at the same site, shows that the received signals fluctuate tremendously with time reaching up to 6.5dB in frequencies 1kHz or less. Ambient noises give negative effects directly on sonar performance. Measurements at some sites in the East Coast Sea of Korea suggest that the noise levels greatly fluctuate with time, for example noon and early morning, mainly due to ship traffics. The average difference in a day may reach 10dB in frequency 200Hz. Another experiment using an array of hydrophones gives that the spectrum levels of ambient noises are highly directional, their difference being as large as 10dB with vertical or horizontal angles. This fact strongly implies that we should obtain in-situ information of noise levels to estimate reasonable sonar performance. As one of non-stationary noise sources, an eel may give serious problems to sonar operation on or under the sea bottoms. Observed eel noises in a pier of water depth 14m appear to have duration time of about 0.4 seconds and frequency ranges of 0.2-2.8kHz. The 'song'of an eel increases ambient noise levels to average 2.16dB in the frequencies concerned, being large enough to degrade detection performance of the sonars on or below sediments. An experiment using hydrophones in water and sediment gives that sensitivity drops of 3-4dB are expected for the hydrophones laid in sediment at frequencies of 0.5-1.5kHz. The SNR difference between in water and in sediment, however, shows large fluctuations rather than stable patterns with the source-receiver ranges.

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