• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.8
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• pp.843-850
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• 2016

This paper introduces a novel modulation scheme for vehicular communication in taking advantage of existing LED lights available on a car. Our proposed 2-Phase Shift Keying (2-PSK) is a spatial modulation approach in which a pair of LED light sources in a car (either rear LEDs or front LEDs) is used as a transmitter. A typical camera (i.e. low frame rate at no greater than 30fps) that either a global shutter camera or a rolling shutter camera can be used as a receiver. The modulation scheme is a part of our Image Sensor Communication proposal submitted to IEEE 802.15.7r1 (TG7r1) recently. Also, a neural network approach is applied to improve the performance of LEDs detection and decoding under the noisy situation. Later, some analysis and experiment results are presented to indicate the performance of our system

• Journal of the Korea Society of Computer and Information
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• v.17 no.12
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• pp.49-60
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• 2012

In this paper, we propose a hardware design for correction of barrel distortion using the nearest coordinates in the corrected image. Because it applies the nearest distance on corrected image rather than adjacent distance on distorted image, the picture quality is improved by the image whole area, solve the staircase phenomenon in the exterior area. But, because of additional arithmetic operation using design of bilinear interpolation, required arithmetic operation is increased. Look up table(LUT) structure is proposed in order to solve this, coordinate rotation digital computer(CORDIC) algorithm is applied. The results of the synthesis using Design compiler, the design of implementing all processes of the interpolation method with the hardware is higher than the previous design about the throughput, In case of the rear camera, the design of using LUT and hardware together can reduce the size than the design of implementing all processes with the hardware.

• Journal of Auto-vehicle Safety Association
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• v.5 no.1
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• pp.56-61
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• 2013

This paper presents a development of the Advanced Emergency Braking (AEB) Algorithm for passenger vehicles. The AEB is the system to slow the vehicle and mitigate the severity of an impact when a rear end collision probability is increased. To mitigate a rear end collision, the AEB comprises of a millimeter wave radar sensor, CCD camera and vehicle parameters of which are processed to judge the likelihood of a collision occurring. The main controller of the AEB algorithm is composed of the two control stage: upper and lower level controller. By using the collected obstacle information, the upper level controller of the main controller decides the control mode based not only on parametric division, but also on physical collision capability. The lower level controller determines warning level and braking level to maintain the longitudinal safety. To decide the braking level, Last Ponit To Brake and Steer (LPTB/LPTS) are compared with current driving statues. To demonstrate the control performance of the proposed AEBS algorithm's, closed-loop simulation of the AEBS was conducted by using the Matlab simlink and CarSim software.

• Journal of Korean Society for Quality Management
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• v.50 no.3
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• pp.533-543
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• 2022

Purpose: The purpose of this study is to identify and resolve the causes of defects in the unmanned aerial vehicle launch system(propulsion wire fracture, rear rail deformation) and to prevent recurrence. Methods: The causes of the two defects were derived through fault tree analysis for each of the two defects and fault reproduction tests. In the case of propulsion wire, the installation of a high speed camera to check the behavior of wire was the driving force behind the defect resolution. Results: The results of this study are as follows; It was determined that the thickness of the washer was less than the maximum tolerance of the pulley was the cause of the propulsion wire fracture defect. Failure to comply with the launch procedure and insufficient safety margin were judged as the cause of the rear rail deformation defect. Accordingly, the configuration was changed to remove each defect. Conclusion: The case of this study was conducted to eliminate defects in the launch system for UAV. The causes of defects were estimated through fault tree analysis. After the configuration change, Structural analysis and launch tests were performed to demonstrate the safety and effectiveness of the modified configuration. As a result, the effect of the modified configuration was verified.

• Journal of Korea Society of Industrial Information Systems
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• v.13 no.4
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• pp.1-13
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• 2008

In this paper, we propose a method to solve a problem in binarizing the rear number plate image captured by a camera on a moving vehicle. An image may be shadowed by the cavernous structure of the rear side of a moving vehicle and it makes us hard to get a high quality of binary image. Therefore, we first detect a shadow edge and then divide an image into the shadow part and non-shadow part by the edge. Finally, the binary image is obtained by binarizing each part and merging them In this paper, we do comparative work on a group of binarization methods including our method, the method suggested by Zheng, the method using block binarization, and the method using labeling. The result shows that our method achieves better performance than others in most cases.

• Journal of the Korea Society of Computer and Information
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• v.17 no.1
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• pp.97-104
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• 2012

Natural User Interface(NUI) technologies introduce new trends in using devices such as computer and any other electronic devices. In this paper, an augmented reality on a mobile device is implemented by using face detection, recognition and motion tracking. The face detection is obtained by using Viola-Jones algorithm from the images of the front camera. The Eigenface algorithm is employed for face recognition and face motion tracking. The augmented reality is implemented by overlapping the rear camera image and GPS, accelerator sensors' data with the 3D graphic object which is correspond with the recognized face. The algorithms and methods are limited by the mobile device specification such as processing ability and main memory capacity.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.23 no.10
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• pp.1265-1273
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• 1999

PIV(Particle Image Velocimetry) velocity field measurements inside the snout of a1/10 scale model of the Zn plating process were carried out at the strip speed $V_s=1.5m/s$. Aluminum powder particles ($1{\mu}m$) and atomized olive oil ($3{\mu}m$) were used as seeding particles to simulate the molten Zinc flow and deoxidization gas flow, respectively. A pulsed Nd:Yag laser and a $2K{\times}2K$ high-resolution CCD camera were synchronized for the PIV velocity field measurement. From flow visualization study, it is found that the liquid flow in the Zn pot is dominantly governed by the uprising flow caused by the rotating sink roll, with its effect on the steel strip inside the snout largely diminished by installing of the snout. The deoxidization gas flow in front of the strip inside the snout can be characterized by a large-scale vortex rotating clockwise direction formed by the moving strip. In the rear side of the strip, a counter-clockwise vortex is formed and some of the flow entrained by the moving strip impinges on the free surface of molten zinc. The liquid flow in front of the strip is governed by the flow entering the snout, caused by the spinning sink roll. Just below the free surface a counter-clockwise vortex is formed near the snout wall. The moving strip affects dominantly the flow behind the strip inside the snout, and large amount of the liquid flow follows the moving strip toward the sink roll. The thickness of the flow following the strip is very thin in the front side due to the uprising flow, however thick boundary layer is formed in the rear side of the strip. Its thickness is increased as moving downstream toward the sink roll. Inside the snout, the deoxidization gas flow above the free surface is much faster than the liquid flow in the zinc pot. Due to the larger influx of the flow following the moving strip in the rear side of the strip, higher percentage of imperfection can be anticipated on the rear surface of the strip.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.05a
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• pp.339-342
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• 2012

최근 자동차 산업의 발달로 후방카메라의 보급과 더불어 안전/보안 관련 제품이 출시되고 있다. 대부분의 후방카메라 설치는 많은 부품과 배선들이 들어간다는 단점이 있으며 배선이 길어질수록 노이즈가 발생한다. 본 연구는 차량의 후방을 감시하는 후방카메라에 관한 시스템으로 MOST 네트워크를 이용하여 설계하였다. 동기 및 비동기 데이터를 동시에 전송할 수 있는 MOST(Media Oriented Systems Transport) 네트워크는 최근 자동차 멀티미디어 시스템에 가장 광범위하게 사용되고 있는 통신 시스템이다. MOST150은 주로 링 형태로 연결되어지며 마스터 역할을 하는 장치가 반드시 하나 존재하고 여러 개의 슬레이브 장치들이 존재한다. 본 논문에서는 MOST150 네트워크에서 차량용 카메라로부터 들어오는 영상을 적용하고, 광 케이블을 통해 노이즈 발생 및 배선의 복잡성을 줄여 운전자가 정확하고 실시간으로 원활한 영상 데이터를 얻을 수 있는 시스템을 설계 및 구현하였다.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.803-807
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• 2003

Tele-operation and remote monitoring techniques are essential and important technologies for performing the inspection and repair tasks effectively in nuclear power plants. This paper presents the application of a mobile robot for the remote monitoring and inspection of the Calandria faces, where human access is limited because of the high-level radioactive environments during full power operation. The mobile robot was designed with reconfigurable crawler type of wheels attached on the front and rear side in order to pass through the ditch. The extendable mast, mounted on the mobile robot, can be extended up to 8 m vertically. This robot was also equipped a visible CCD/thermal infrared inspection head module and a stereo camera module for the enhancement of visual inspection.

• IEMEK Journal of Embedded Systems and Applications
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• v.12 no.2
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• pp.113-120
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• 2017

In this paper, we present a night-time vehicle detection method using CNN (Convolutional Neural Network) classification. The camera based night-time vehicle detection plays an important role on various advanced driver assistance systems (ADAS) such as automatic head-lamp control system. The method consists mainly of thresholding, labeling and classification steps. The classification step is implemented by existing CIFAR-10 model CNN. Through the simulations tested on real road video, we show that CNN classification is a good alternative for night-time vehicle detection.