• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.3
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• pp.115-122
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• 2016

This paper proposes a system to detect driver's cognitive state by internal and external information of vehicle. The proposed system can measure driver's eye gaze. This is done by concept of information delivery and mutual information measure. For this study, we set up two web-cameras at vehicles to obtain visual information of the driver and front of the vehicle. We propose Gestalt principle based selective attention model to define information quantity of road scene. The saliency map based on gestalt principle is prominently represented by stimulus such as traffic signals. The proposed system assumes driver's cognitive resource allocation on the front scene by gaze analysis and head pose direction information. Then we use several feature algorithms for detecting driver's characteristics in real time. Modified census transform (MCT) based Adaboost is used to detect driver's face and its component whereas POSIT algorithms are used for eye detection and 3D head pose estimation. Experimental results show that the proposed system works well in real environment and confirm its usability.

• 한국정보디스플레이학회:학술대회논문집
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• 2005.07a
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• pp.381-384
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• 2005

Driver IC is one of the key components on the LCD monitor and LCD/TV. The function of the driver IC is to transfer and forward the input signals to LCD panel module. Inside driver IC, there are several operating units which process the input signals and generate the appropriate size and resolution to the LCD panel module. LCD panel module will display these input signals. However, there are some difficulties which driver IC designer, LCD monitor and LCD/TV maker will face. Thus, this article addresses the function and difficulties on driver IC.

• The Journal of the Korea institute of electronic communication sciences
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• v.6 no.3
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• pp.439-444
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• 2011

In this paper, we implemented the intelligent smart monitor system for next generation which is most commonly viewed information in a vehicle from the instrument cluster, where speed, tachometer, fuel, engine temperature, fuel gauge, turn indicators and warning lights and provide the driver with an array of informations. Designed Smart HUD(Head-Up-Display) monitor system is composed TFT LCD, LCD Back light led, plane mirror, lens and controllers parts and it was assembled to intelligent integrated smart monitor system. Finally, we analyze intelligent integrated smart monitor system for driver safety vehicles and present the possibility to apply to smart intelligent HUD total monitor system for next generation.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.12
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• pp.123-129
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• 2014

In accordance with the development of various convergence devices, cameras are being used in many types of the systems such as security system, driver assistance device and so on, and a lot of people are exposed to these system. Therefore the system should be able to recognize the human behavior and support some useful functions with the information that is obtained from detected human behavior. In this paper we use a machine learning approach based on 2D image and propose the human behavior pattern recognition methods. The proposed methods can provide valuable information to support some useful function to user based on the recognized human behavior. First proposed one is "phone call behavior" recognition. If a camera of the black box, which is focused on driver in a car, recognize phone call pose, it can give a warning to driver for safe driving. The second one is "looking ahead" recognition for driving safety where we propose the decision rule and method to decide whether the driver is looking ahead or not. This paper also shows usefulness of proposed recognition methods with some experiment results in real time.

• Journal of information and communication convergence engineering
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• v.18 no.2
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• pp.75-81
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• 2020

Approximately 1.3 million people die from traffic accidents each year, and smartphone usage while driving is one of the main causes of such accidents. Therefore, detection of smartphone usage by drivers has become an important part of distracted driving detection. Previous studies have used single camera-based methods to collect the driver images. However, smartphone usage detection by employing a single camera can be unsuccessful if the driver occludes the phone. In this paper, we present a driver smartphone usage detection system that uses multiple cameras to collect driver images from different perspectives, and then processes these images with ensemble convolutional neural networks. The ensemble method comprises three individual convolutional neural networks with a simple voting system. Each network provides a distinct image perspective and the voting mechanism selects the final classification. Experimental results verified that the proposed method avoided the limitations observed in single camera-based methods, and achieved 98.96% accuracy on our dataset.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.10
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• pp.27-34
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• 1993

In this paper, a driver system is designed and implemented to achieve 4-level gray scale CH TFEL(Thin Film ElectroLuminescent) flat panel display. To implement the driver system, commercial EL driver IC chips are used to apply high voltage pulses to the EL panel and a high voltage switching circuit is designed for the EL driver IC. A new method of reducing storage delay time of transistor is proposed to obtain a reliable switching circuit. The controller for EL driver and switching circuit is also designed. The designed driving scheme applicable to EL display with 4-level gray scale is based on the linear characteristics of brightness vs. frequency of AC TFEL. By experiment, it has been shown that the brightness of AC TEFL display with the implemented driving system is controlled by the level of gray scale.

• Proceedings of the KIEE Conference
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• 2007.04a
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• pp.193-195
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• 2007

It will be able to deliver quickly information it measures a weight the numerous vehicles at real-time for the managers. It does the Graphic LCD driver development for in Factory automation embeded system and introduces the plan and an embodiment of process shipping automation system.

• Journal of Information Processing Systems
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• v.2 no.3 s.4
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• pp.137-142
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• 2006

A large portion of the embedded system development process involves the integration of hardware and software. Unfortunately, communication across the hardware/software boundary is tedious and error-prone to create. This paper presents an automatic hardware/software interface generation system. As the front-end of hardware/software co-design frameworks, a system designer defines XML specifications for hardware functions. Our system generates hardware/software interfaces including Device Driver, Driver API, and Device Controller from these specifications. Embedded software designers can easily use hardware just like system libraries. Our system reduces the mistakes and errors that can be occurred when a software programmer directly connects software to hardware, and supports balancing labors between hardware developers and software programmers. Moreover, this system can be used as the back-end for a hardware/software co-design framework.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.4
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• pp.173-179
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• 2017

Autobike is insufficient of car navigation informations and high of accident dangerousness comparing to car. So if a system providing autobike driver's driving information and e-call function is developed using smart helmet consisting of collision perception sensor, rear camera, bluetooth communication module, MCU and HUD, It is very useful and can decrease of person's damage and handle expeditious traffic accident during autobike accident. In this paper, when this, "Providing system of autobike driver's information and e-call function", software is developed, a proper analysis and design method for practical affairs try to be presented due to showing software development analysis method, architecture of hardware block-diagram, flowchart and UI design.

• Journal of Information Processing Systems
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• v.13 no.4
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• pp.951-969
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• 2017

In this paper, we newly propose a traffic information service model that collects traffic information sensed by an individual vehicle in real time by using a smart device, and which enables drivers to share traffic information on all roads in real time using an application installed on a smart device. In particular, when the driver requests traffic information for a specific area, the proposed driver-personalized service model provides him/her with traffic information on the driving directions in advance by predicting the driving directions of the vehicle based on the learning of the driving records of each driver. To do this, we propose a traffic information management model to process and manage in real time a large amount of online-generated traffic information and traffic information requests generated by each vehicle. We also propose a road node-based indexing technique to efficiently store and manage location-based traffic information provided by each vehicle. Finally, we propose a driving learning and prediction model based on the hidden Markov model to predict the driving directions of each driver based on the driver's driving records. We analyze the traffic information processing performance of the proposed model and the accuracy of the driving prediction model using traffic information collected from actual driving vehicles for the entire area of Seoul, as well as driving records and experimental data.