• Journal of the Korean Society of Industry Convergence
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• v.24 no.6_2
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• pp.699-706
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• 2021

Existing license plate recognition system is used as an optical character recognition method, but a method of using deep learning has been proposed in recent studies because it has problems with image quality and Korean misrecognition. This requires a lot of data collection, but the collection of license plates is not easy to collect due to the problem of the Personal Information Protection Act, and labeling work to designate the location of individual license plates is required, but it also requires a lot of time. Therefore, in this paper, to solve this problem, five types of license plates were created using a virtual Korean license plate generation program according to the notice of the Ministry of Land, Infrastructure and Transport. And the generated license plate is synthesized in the license plate part of collectable vehicle images to construct 10,147 learning data to be used in deep learning. The learning data classifies license plates, Korean, and numbers into individual classes and learn using YOLOv5. Since the proposed method recognizes letters and numbers individually, if the font does not change, it can be recognized even if the license plate standard changes or the number of characters increases. As a result of the experiment, an accuracy of 96.82% was obtained, and it can be applied not only to the learned license plate but also to new types of license plates such as new license plates and eco-friendly license plates.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.557-560
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• 2021

In the face of the COVID-19 pandemic, the Korean Government announced the Korean New Deal as a national development strategy to overcome the economic recession from the pandemic crisis and lead the global action aginst sturctural changes. The Green New Deal related with the energy aims to achieve net-zero emissions and accelerates the transition towards a low-carbon and green economy. To this end, the government plans to promete an increased use of renewable energy in the the society at large. This paper introduces a compact-binary power plant using unused thermal energy and a control system based on Neural Network in order to accelerate the transition towards a low-carbon and green economy. It is expected that he compact-binary power plant accelerate introduction of renewable energy along with solar and wind power.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.4 no.1
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• pp.23-31
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• 2011

In this paper, the intelligent smart monitor system is implemented for the next generation vehicle. to mitigate the numerous effects of distractions within the vehicle, it is vital to put critical information where the driver can use it without affection focus on the road ahead. Audible alarms are useful supplements when used in conjunction with visual displays. But driving is an overwhelmingly visual task. To optimize a vehicle's active safety systems, more than just audible alarms are necessary. The driver needs a visual interface that focuses his or her attention on the road ahead. The most commonly viewed information in a vehicle is from the instrument cluster, where speed, tachometer, fuel, engine temperature, fuel gauge, turn indicators and warning lights provide the driver with an array of fundamental information. TFT LCD, LCD Back light led, plane mirror, lens and controllers parts were designed to intelligent integrated smart monitor system. Finally, in this paper, we analyze intelligent integrated smart monitor system for driver safety vehicles.

• Korean Journal of Cognitive Science
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• v.25 no.1
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• pp.51-71
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• 2014

This paper presents an image enhancement method in real road traffic scenes. The images captured by the camera on the car cannot keep the color constancy as illumination or weather changes. In the real environment, these problems are more worse at back light conditions and at night that make more difficult to the applications of the vision-based intelligent vehicles. Using the existing image enhancement methods without considering the position and intensity of the light source and their geometric relations the image quality can even be deteriorated. Thus, this paper presents a fast and effective method for image enhancement resembling human cognitive system which consists of 1) image preprocessing, 2) color-contrast evaluation, 3) alpha blending of over/under estimated image and preprocessed image. An input image is first preprocessed by gamma correction, and then enhanced by an Automatic Color Enhancement(ACE) method. Finally, the preprocessed image and the ACE image are blended to improve image visibility. The proposed method shows drastically enhanced results visually, and improves the performance in traffic sign detection of the vision based intelligent vehicle applications.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.1
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• pp.55-69
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• 2017

Recently, the IoT (Internet of Things) environment is being developed rapidly through network which is linked to intellectual objects. Through the IoT, it is possible for human to intercommunicate with objects and objects to objects. Also, the IoT provides artificial intelligent service mixed with knowledge of situational awareness. One of the industries based on the IoT is a car industry. Nowadays, a self-driving vehicle which is not only fuel-efficient, smooth for traffic, but also puts top priority on eventual safety for humans became the most important conversation topic. Since several years ago, a research on the recognition of the surrounding environment for self-driving vehicles using sensors, lidar, camera, and radar techniques has been progressed actively. Currently, based on the WAVE (Wireless Access in Vehicular Environment), the research is being boosted by forming networking between vehicles, vehicle and infrastructures. In this paper, a research on the recognition of a traffic signs on highway was processed as a part of the awareness of the surrounding environment for self-driving vehicles. Through the traffic signs which have features of fixed standard and installation location, we provided a learning theory and a corresponding results of experiment about the way that a vehicle is aware of traffic signs and additional informations on it.

• Electronics and Telecommunications Trends
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• v.12 no.3 s.45
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• pp.11-17
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• 1997

ITS(Intelligent Transportation System)는 H/W 중심의 차량 및 교통 기반 기설에 통신.전자.제어.컴퓨터 등 S/W 중심의 기술을 적용하여, 각 차량 및 교통 시설(신호등, 도로, 교통 안내 표지판, 도로 상황판 등)들이 상호 보완적으로 작동할 수 있게 함으로써, 기존의 도로 교통 시설의 이용 효과를 극대화하고, 그 안정성을 향상시키며, 교통 수요 관리를 목적으로 사용자에게 교통 정보를 제공하는 지능형 종합 기술 체계이다. 이러한 최첨단 도로교통 관리의 ITS를 이용한 서비스는 각 나라마다 달리 정의되는데, 우리나라에서는 첨단교통관리시스템(ATMS), 첨단교통정보시스템(ATIS), 상용차량 운행관리 시스템(CVO), 차량 및 도로 시스템(AVCS) 그리고 첨단 대중교통 시스템(APTS)의 5개 분야로 나누어진다(1). 이 다섯가지 ITS 서비스 시스템은 공통적으로 정보 수집, 정보 처리, 정보 전달, 정보 통신 기능을 가지고 있다. 즉, 각종 검지기, 차량 단말, 노변 단말 등의 수집 장치에서 수집된 정보(정보 수집)는 관련 통신 방식(정보 통신)을 통하여 중앙 정보 처리 센터에 전달되어 그 서비스 요구 사항에 따라 처리(정보 처리)되고, 생성된 정보는 해당되는 통신 채널을 거쳐(정보 통신) 각종 사용자 단말기에게 제공(정보 전달)된다. 본 논문에서는 이와 같은 ITS체계의 정의, 목표 및 서비스 종류에 대하여 설명하였으며 교통 정보를 수집하고 처리하여 전달하는 과정과 이에 요구되는 통신 체계에 대하여 알아본다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.6
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• pp.1441-1448
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• 2013

The propose of this study is to apply establish the foundation for development of elder driver friendly smart cluster. At first, vehicle dashboard trends were analyzed. Secondly, we presents the structure of elder driver friendly smart cluster and explains android based meter cluster. also, we shows the implementation details and experimental result of elder driver friendly smart cluster system. And we presents a summary and conclusions.

• Journal of the Korean Society for Nondestructive Testing
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• v.29 no.4
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• pp.308-315
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• 2009

Because the attenuation of AE signal in composite materials is relatively higher than that of metallic materials, it is required to develop a damage assessment technique less affected by the attenuation property of composite materials in order to use AE sensing as a damage detection method. In the signal processing procedure, it is profitable to use the leading wave that arrives first because the leading wave is less influenced by the boundary conditions. Using wavelet transform, we investigated the frequency characteristics of impact induced AE signals focused on the leading wave in advance and chose the key factors to discriminate the damaged condition quantitatively. In this research, we established a damage assessment technique using the sharing percentage of the wavelet detail components of AE signal, and conducted a low-velocity impact test on composite laminates to confirm the feasibility of the proposed signal processing method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.12B
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• pp.1574-1585
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• 2011

This paper proposes a real-time algorithm for speed limit sign recognition for advanced safety vehicle system. The proposed algorithm uses Block-DCT in extracting features from a given ROI(Region Of Interest) instead of using entire pixel values as in previous works. The proposed algorithm chooses parts of the DCT coefficients according to the proposed discriminant factor, uses correlation coefficients and variances among ROIs from training samples to reduce amount of arithmetic operations without performance degradation in classification process. The algorithm recognizes the speed limit signs using the information obtained during training process by calculating LDA and Mahalanobis Distance. To increase the hit rate of recognition, it uses accumulated classification results computed for a sequence of frames. Experimental results show that the hit rate of recognition for sequential frames reaches up to 100 %. When compared with previous works, numbers of multiply and add operations are reduced by 69.3 % and 67.9 %, respectively. Start after striking space key 2 times.

• Journal of Sensor Science and Technology
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• v.10 no.1
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• pp.42-51
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• 2001

In this study, the effects of embedded optical fibers on the static properties under tensile load and dynamic properties under fatigue load of composite laminates were investigated by experimental tests and finite element analysis. Based on the results, it can be concluded that the embedded optical fiber sensors do not have significant effects on the structural integrity of the smart composite structures except when the sensors are embedded perpendicular to the adjacent reinforcing fibers under fatigue loading. An intensity-based optical fiber sensor was embedded in the crossply composite laminates to monitor the fatigue damage by detecting the stiffness changes of the laminates. The result of this experiment has shown that the intensity-based optical fiber sensor has large potential to monitor the fatigue damage of composite structures by detecting the stiffness changes of the structures with simple and inexpensive instruments and without complex post-processing of measured signals. In addition, the optical fiber sensor showed good resistance to fatigue loading and wide sensing ranges of stiffness.