• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.6
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• pp.96-106
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• 2020

To solve the limitation of traffic monitoring that occur from embedded sensor such as loop and piezo sensors, the thermal imaging camera was installed on the roadside. As the length of Class 1(passenger car) is getting longer, it is becoming difficult to classify from Class 3(2-axle truck) by using an embedded sensor. The collected images were labeled to generate training data. A total of 17,536 vehicle images (640x480 pixels) training data were produced. CNN (Convolutional Neural Network) was used to achieve vehicle classification based on thermal image. Based on the limited data volume and quality, a classification accuracy of 97.7% was achieved. It shows the possibility of traffic monitoring system based on AI. If more learning data is collected in the future, 12-class classification will be possible. Also, AI-based traffic monitoring will be able to classify not only 12-class, but also new various class such as eco-friendly vehicles, vehicle in violation, motorcycles, etc. Which can be used as statistical data for national policy, research, and industry.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.466-469
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• 2013

Cars that are currently available to the operator to ensure convenience and safety for electronics devices now on the market supply is developed. The current car black box of electronics service, parking, is to help when reversing. The black box is necessary at the time of the accident. After-market through a lot of these are advertised. However, these products are known only to the rear or the front of the picture, as well, at the time of driving, the accident and the front left and right lateral images of the boundary of the car can not be confirmed. Electronics devices on the market, but they can not give this problem solving. In this paper, we propose these to the algorithm-around view of the driver's operation of the vehicle after the car sideways, left and right of the room with integrated video Black Box is designed to provide.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.1
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• pp.42-50
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• 2016

Recently, researches about the communication between LED array and the camera (alias 'Visual-MIMO'), have been actively conducted, and the application to the vehicle and a smart phone is expected to be maximized. Since the bit error may occur if the ISI is severe in a LED array, it is necessary to switch from the multiplexing to the diversity mode. In this paper, according to the use or not of a reference array pattern, a method for determining the transition time to the diversity mode is suggested and verified. When using the reference pattern, it determines the transition time to the diversity mode from the multiplexing using the brightness information of the received image. If the reference array pattern is not used, the size of LED array compared to the entire image according to the distance is used and the size of the LED array at the distance of a severe ISI may be used for the determination of transition time to the diversity. Finally, the proposed method is verified through the simulation and hardware experiments as well as by analyzing the performance in accordance with the ISI level and the distance.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.11 no.1
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• pp.74-81
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• 1998

It is not good joint that today's traffic control system that the course of traffic volume increase tendency is followed, in the traffic volume is approched into the time of my car. Accordingly when we analyzed the existing traffic signal control system, the traffic signal system is developed from the machine type that the motor was centered, to get up to date, to the intelligence electron signal control system. But yet, when we have a test and a A/S on the control circuit, the circuit that is designed to the center IC and ROM are complicated. Also, the time of pass lamp that the car line stream is going, can not extended automatically a time till the traffic volume is decreased to the same direction. This theme must be a real time intelligence control system that the time of pass lamp can extend aumatically. The circuit of sequence ladder diagram on the traffic signal control of a crossroads that is desinged, can be satisfied the complicated vehicle order. Therefore when the circuit is changed, the new developed system is economical with that dosen't needs any of components to require the circuit equipment, and the time is saved with needlessness of the circuit wiring again, and have a much trustworthy. The control method of pass signal lamp in the car line stream connecting among PLC and Relay and Temp Sensor, can be changed to hand operation and to semi-automation and to all-automation. New intelligence traffic signal system is composed with all-together system of T Sensor + Video Camera + IBM PC that is able to guiding the establishment of traffic order.

• Journal of the Korea Society for Simulation
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• v.18 no.4
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• pp.9-20
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• 2009

Navigation system providing route-guidance and traffic information is one of the most widely used driver-support system these days. Most of the navigation system is based on the 2D map paradigm so the information is ed and encoded from the real world. As a result it imposes a cognitive burden to the driver to interpret and translate the ed information to real world information. As a new concept of navigation system, augmented-reality navigation system (AR navigation) is suggested recently. It provides navigational guidance by imposing graphical information on real image captured by camera mounted on a vehicle in real-time. The ultimate goal of navigation system is to assist the driving task with least driving workload whether it is based on the abstracted graphic paradigm or realistic image paradigm. In this paper, we describe the comparative studies on how map navigation and AR navigation affect for driving tasks by experimental research. From the result of this research we obtained a basic knowledge about the two paradigms of navigation systems. On the basis of this knowledge, we are going to find the optimal design of navigation system supporting driving task most effectively, by analyzing characteristics of driving tasks and navigational information from the human-vehicle interface point of view.

• Journal of Korean Tunnelling and Underground Space Association
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• v.25 no.3
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• pp.245-259
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• 2023

The purpose of this paper is to examine the most recent tunnel scanning systems to obtain insights for the development of non-contact mobile inspection system. Tunnel scanning systems are mostly being developed by adapting two main technologies, namely laser scanning and image scanning systems. Laser scanning system has the advantage of accurately recreating the geometric characteristics of tunnel linings from point cloud. On the other hand, image scanning system employs computer vision to effortlessly identify damage, such as fine cracks and leaks on the tunnel lining surface. The analysis suggests that image scanning system is more suitable for detecting damage on tunnel linings. A camera-based tunnel scanning system under development should include components such as lighting, data storage, power supply, and image-capturing controller synchronized with vehicle speed.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.4
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• pp.349-355
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• 2015

Underwater robots generally show better performances for tasks than humans under certain underwater constraints such as. high pressure, limited light, etc. To properly diagnose in an underwater environment using remotely operated underwater vehicles, it is important to keep autonomously its own position and orientation in order to avoid additional control efforts. In this paper, we propose an efficient method to assist in the operation for the various disturbances of a remotely operated vehicle for the diagnosis of underwater structures. The conventional AHRS-based bearing estimation system did not work well due to incorrect measurements caused by the hard-iron effect when the robot is approaching a ferromagnetic structure. To overcome this drawback, we propose a sensor fusion algorithm with the camera and AHRS for estimating the pose of the ROV. However, the image information in the underwater environment is often unreliable and blurred by turbidity or suspended solids. Thus, we suggest an efficient method for fusing the vision sensor and the AHRS with a criterion which is the amount of blur in the image. To evaluate the amount of blur, we adopt two methods: one is the quantification of high frequency components using the power spectrum density analysis of 2D discrete Fourier transformed image, and the other is identifying the blur parameter based on cepstrum analysis. We evaluate the performance of the robustness of the visual odometry and blur estimation methods according to the change of light and distance. We verify that the blur estimation method based on cepstrum analysis shows a better performance through the experiments.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.37 no.4
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• pp.11-19
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• 2000

Real-time extraction of traffic information such as the number of vehicles passing, speed, road-occupancy rate, distance between vehicles, and vehicle types from the traffic scenes acquired from the camera on the road, is a core component of the intelligent transportation system(lTS) We present a scheme of extracting the traffic informations based on the spatio-temporal image analysis, which is robust to the variation of weather conditions and the shades. The images of two detection regions for each traffic lane are classified into one of the three categories: the road, the vehicle, and the shade, using the statistical and structural features Quantitative traffic informations are retrieved by analysing the two spatio-temporal images. Since only the local images of detection regions are processed, the real-time operation of more than 30 frames per second is realized while ensuring the detection performance robust to the operating condition.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.49 no.1
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• pp.88-93
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• 2012

Lane detection methods using camera, which are part of the driver assistance system, have been developed due to the growth of the vehicle technologies. However, lane detection methods are often failed by varying road conditions such as rainy weather and degraded lanes. This paper proposes a method for lane detection which is robust in varying road condition. Lane candidates are extracted by intensity comparison and lane detection filter. Hough transform is applied to compute the lane pair using lane candidates which is straight line in image. Then, a curved lane is calculated by using B-Snake algorithm. Also, weighting value is computed using previous lane detection result to detect the lanes even in varying road conditions such as degraded/missed lanes. Experimental results proved that the proposed method can detect the lane even in challenging road conditions because of weighting process.

• The KIPS Transactions:PartB
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• v.12B no.4 s.100
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• pp.387-394
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• 2005

This paper describes an idea for determining self-localization using visual landmark. The critical geometric dimensions of a pentagon are used here to locate the relative position of the mobile robot with respect to the pattern. This method has the advantages of simplicity and flexibility. This pentagon is also provided nth a unique identification, using invariant features and colors that enable the system to find the absolute location of the patterns. This algorithm determines both the correspondence between observed landmarks and a stored sequence, computes the absolute location of the observer using those correspondences, and calculates relative position from a pentagon using its (ive vortices. The algorithm has been implemented and tested. In several trials it computes location accurate to within 5 centimeters in less than 0.3 second.