• Title/Summary/Keyword: 주행알고리즘

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The Character Recognition System of Mobile Camera Based Image (모바일 이미지 기반의 문자인식 시스템)

  • Park, Young-Hyun;Lee, Hyung-Jin;Baek, Joong-Hwan
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.11 no.5
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    • pp.1677-1684
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    • 2010
  • Recently, due to the development of mobile phone and supply of smart phone, many contents have been developed. Especially, since the small-sized cameras are equiped in mobile devices, people are interested in the image based contents development, and it also becomes important part in their practical use. Among them, the character recognition system can be widely used in the applications such as blind people guidance systems, automatic robot navigation systems, automatic video retrieval and indexing systems, automatic text translation systems. Therefore, this paper proposes a system that is able to extract text area from the natural images captured by smart phone camera. The individual characters are recognized and result is output in voice. Text areas are extracted using Adaboost algorithm and individual characters are recognized using error back propagated neural network.

A Study on Automatic Detection of Speed Bump by using Mathematical Morphology Image Filters while Driving (수학적 형태학 처리를 통한 주행 중 과속 방지턱 자동 탐지 방안)

  • Joo, Yong Jin;Hahm, Chang Hahk
    • Journal of Korean Society for Geospatial Information Science
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    • v.21 no.3
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    • pp.55-62
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    • 2013
  • This paper aims to detect Speed Bump by using Omni-directional Camera and to suggest Real-time update scheme of Speed Bump through Vision Based Approach. In order to detect Speed Bump from sequence of camera images, noise should be removed as well as spot estimated as shape and pattern for speed bump should be detected first. Now that speed bump has a regular form of white and yellow area, we extracted speed bump on the road by applying erosion and dilation morphological operations and by using the HSV color model. By collecting huge panoramic images from the camera, we are able to detect the target object and to calculate the distance through GPS log data. Last but not least, we evaluated accuracy of obtained result and detection algorithm by implementing SLAMS (Simultaneous Localization and Mapping system).

A Study on a Diagnosis System for HSR Turnout Systems (II) (고속철도 분기기 시스템 진단 시스템에 관한 연구(II))

  • Kim, Youngseok;Yoon, Yeonjoo;Back, Inchul;Ryu, Youngtae;Han, Hyunsu;Hwang, Ankyu;Kang, Hyungseok;Lee, Jongwoo
    • Journal of the Korean Society for Railway
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    • v.20 no.2
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    • pp.223-233
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    • 2017
  • The railway turnout system is one of the most important systems that set train routes. Turnout system integrity should be guaranteed for robust train operation. To diagnose the turnout system status, LVDT and accelerometers are installed on a turnout system in a high speed line. The LVDT and accelerometers produce signals containing physical meaning of the turnout systems. The LVDT produces the displacement of the rail gauge and vibration when point moving or a train passes on turnout systems and the accelerometer produces impact forces induced by wheel sets. We performed data extraction from the measured signals and parameterized the extracted signals into meaningful quantities. The parameters are used for classifying whether the turnout status is normal. We proposed two methods for the classification, one uses probabilistic distribution and the other artificial neuron networks. The probabilistic distribution is used for the parameter being classified by the quantities and the artificial neuron networks for the form classification. Finally, we show how to learn the normal status of a turnout system.

Vision-Based Fast Detection System for Tunnel Incidents (컴퓨터 시각을 이용한 고속 터널 유고감지 시스템)

  • Lee, Hee-Sin;Jeong, Sung-Hwan;Lee, Joon-Whoan
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.9 no.1
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    • pp.9-18
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    • 2010
  • Our country has so large mountain area that the tunnel construction is inevitable and the need of incident detection that provides safe management of tunnels is increasing. In this paper, we suggest a tunnel incident detection system using computer vision techniques, which can detect the incidents in a tunnel and provides the information to the tunnel administrative office in order to help safe tunnel operation. The suggested system enhances the processing speed by using simple processing algorithm such as image subtraction, and ensures the accuracy of the system by focused on the incident detection itself rather than its classification. The system is also cost effective because the video data from 4 cameras can be simultaneously analyzed in a single PC-based system. Our system can be easily extended because the PC-based analyzer can be increased according to the number of cameras in a tunnel. Also our web-based structure is useful to connect the other remotely located tunnel incident systems to obtain interoperability between tunnels. Through the experiments the system has successfully detected the incidents in real time including dropped luggage, stoped car, traffic congestion, man walker or bicycle, smoke or fire, reverse driving, etc.

Implementation of a Speech Recognition System for a Car Navigation System (차량 항법용 음성인식 시스템의 구현)

  • Lee, Tae-Han;Yang, Tae-Young;Park, Sang-Taick;Lee, Chung-Yong;Youn, Dae-Hee;Cha, Il-Hwan
    • Journal of the Korean Institute of Telematics and Electronics S
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    • v.36S no.9
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    • pp.103-112
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    • 1999
  • In this paper, a speaker-independent isolated world recognition system for a car navigation system is implemented using a general digital signal processor. This paper presents a method combining SNR normalization with RAS as a noise processing method. The semi-continuous hidden markov model is adopted and TMS320C31 is used in implementing the real-time system. Recognition word set is composed of 69 command words for a car navigation system. Experimental results showed that the recognition performance has a maximum of 93.62% in case of a combination of SNR normalization and spectral subtraction, and the performance improvement rate of the system is 3.69%, Presented noise processing method showed good speech recognition performance in 5dB SNR in car environment.

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Predictive Algorithm of Self-Control System using Load Control Model applied to Automobile Dynamic (하중모델을 이용한 자동차 운동 분석과 자율 예측 시스템 알고리즘)

  • Wang, Hyun-Min;Woo, Kwang-Joon
    • Journal of the Institute of Electronics Engineers of Korea SC
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    • v.47 no.4
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    • pp.61-68
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    • 2010
  • Appling high technology of aerospace to automobile, so it is able to progress safety which is a goal of future automobile and to approach development of self-control automobile. This is realized dynamic model of airplane at DFCS(Digital Flight Control System). The DFCS calculates control values for self-control flight. If this high technology applies to automobile, then it is able to be maneuvered automobile like UAV's self-control flight. In this paper is reanalyzed automobile dynamic applied load control model used high-tech of airplane. It analyzes riding comfortable according to movement of automobile using the load control model, presents method of solution for improvement riding comfortable and presents example of self-control system used the load control model for self-control driving.

Forecasting of Traffic Situation using Internet (인터넷을 이용한 교통상황예보)

  • Hong, You-Sik;Choi, Myeong-Bok
    • Journal of the Korean Institute of Intelligent Systems
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    • v.13 no.3
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    • pp.300-309
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    • 2003
  • The Japanese developed the first Car navigation system in 1981 with the advent of Honda, which was known as the car inertial navigation system. Now days, It is possible to search the shortest route to and from places and arrival time using the internet via cell phone to the driver based on GIS and GPS. However, even with a good navigation system, it losses the shortest route when there is an average speed of the vehicle being between S-15 kilometers. Therefore, in order to improve the vehicle waiting time and average vehicle speed, we are suggesting an optimal green time algorithm using fuzzy adaptive control, where there are different traffic intersection lengths, and lanes. In this paper, to be able to assist the driver and forecast the optimal traffic information with regards to the road conditions; dangerous roads, construction work and estimation of arrival time at their destination using internet.

Indoor Localization by Matching of the Types of Vertices (모서리 유형의 정합을 이용한 실내 환경에서의 자기위치검출)

  • Ahn, Hyun-Sik
    • Journal of the Institute of Electronics Engineers of Korea SC
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    • v.46 no.6
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    • pp.65-72
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    • 2009
  • This paper presents a vision based localization method for indoor mobile robots using the types of vertices from a monocular image. In the images captured from a camera of a robot, the types of vertices are determined by searching vertical edges and their branch edges with a geometric constraints. For obtaining correspondence between the comers of a 2-D map and the vertex of images, the type of vertices and geometrical constraints induced from a geometric analysis. The vertices are matched with the comers by a heuristic method using the type and position of the vertices and the comers. With the matched pairs, nonlinear equations derived from the perspective and rigid transformations are produced. The pose of the robot is computed by solving the equations using a least-squares optimization technique. Experimental results show that the proposed localization method is effective and applicable to the localization of indoor environments.

Road Sign Tracking using Affine-AR Model and Robust Statistics (어파인-자기 회귀 모델과 강인 통계를 사용한 교통 표지판 추적)

  • Yoon, Chang-Yong;Cheon, Min-Kyu;Lee, Hee-Jin;Kim, Eun-Tai;Park, Mig-Non
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.46 no.5
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    • pp.126-134
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    • 2009
  • This paper describes the vision-based system to track road signs from within a moving vehicle. The proposed system has the standard architecture with particle filter due to its robust tracking performance in complex environment. In the case of tracking road signs in real environment, it has a great difficulty in predicting time series data by reason of an occlusion due to an obstacle and the rapid change of objects on roads. To overcome this problem and improve the tracking performance, this paper proposes the algorithm using an autoregressive model as an state transition model which has affine parameters as states and using robust statistics for determining occlusion due to obstacles. The experiments of this paper show that the proposed method is efficient for real time tracking of road signs and performs well in road signs under occlusion due to obstacles.

A Performance Improvement on Navigation Applying Measurement Estimation in Urban Weak Signal Environment (도심에서의 측정치 추정을 적용한 항법성능 향상 연구)

  • Park, Sul Gee;Cho, Deuk Jae
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.18 no.11
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    • pp.2745-2752
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    • 2014
  • In recent years, Transport Demand Management has been conducted for the efficient management of transport. In ITS applications in particular, the prerequisite is accurate and reliable positioning. However, the major problems are satellite signal outage, and multipath. This paper proposes that outage and multipath measurement can be detected and estimated using elevation angle and signal to noise ratio data association relation in stand-alone GPS. In order to verify the performance of the proposed method, it is then evaluated by the car test. the evaluation test environment has low accuracy and unreliable positioning because of signal outage or multipath such as steep hill and high buildings. In the evaluation test result, 918times abnormal signal occurred and it was confirmed that the proposed method showed more improved 9.48m(RMS) horizontal positioning error than without proposed method.