• Journal of Korea Multimedia Society
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• v.14 no.12
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• pp.1536-1543
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• 2011

Video stabilization is a very important step for vision based applications in the vehicular technology because the accuracy of these applications such as obstacle distance estimation, lane detection and tracking can be affected by bumpy roads and oscillation of vehicle. Conventional methods suffer from either the zooming effect which caused by a camera movement or some motion of surrounding vehicles. In order to overcome this problem, we propose a novel video stabilization method using FOE(Focus of Expansion). When a vehicle moves, optical flow diffuses from the FOE and the FOE is equal to an epipole. If a vehicle moves with vibration, the position of the epipole in the two consecutive frames is changed by oscillation of the vehicle. Therefore, we carry out video stabilization using motion vector estimated from the amount of change of the epipoles. Experiment results show that the proposed method is more efficient than conventional methods.

• Smart Media Journal
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• v.4 no.1
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• pp.39-43
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• 2015

A vehicle black box helps to investigate the cause of accident by recording time, and videos as wells as shock information of the time of accident Lately, intelligent black box with accident prevention as well as existing functions is being studied. This paper proposes an applicable algorithm for vehicle black boxes that prevent any accident likely to occur while a car is parked, like robbery, theft or hit-and-run. Proposed algorithm provides object recognition, face detection and alarm as the object approaches car. Tests on the algorithm prove that it can recognize an approaching object, identify and set alarm if needed, depending on each risk level.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.2
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• pp.760-771
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• 2012

In this paper, a blind spot of motor car, and the put case that is driven the miniature model motor system, when make practical application of the permanent magnet synchronous motors(PMSM) braking and having had the ability that can all absorb regenerative power by means of electric brake which is occurred. a tow system of a miniature model motor traction system is established by 1C1M methods to control individually permanent magnet synchronous motors (PMSM) of each motor. vector control method is applied in order to improve ride quality of motor car and the efficient use of energy. it was obtained excellent experiment results from the simulations as a function of momentum load and miniature model. Also, this study is investigated the regenerative braking power securities of permanent magnet synchronous motors, speed detection to stop electric brake at extremely very low speed and motor control method of algorithm.

• Journal of Korea Spatial Information System Society
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• v.11 no.1
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• pp.137-144
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• 2009

Understanding lane markings in a live video captured from a moving vehicle is essential to build services for intelligent vehicles such as LDWS(Lane Departure Warning Systems), unmanned vehicles, video-based car navigation systems. In this paper, we present a novel approach to recognize the color of lane markings and the lane number that he/she is driving on. More specifically, we present a background-color removal approach to understand the color of lane markings for various illumination conditions, such as backlight, sunset, and so on. In addition, we present a probabilistic network approach to decide the lane number. According to our experimental results, the proposed idea shows promising results to detect lane number in a various illumination conditions and road environments.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.3
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• pp.651-658
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• 2015

Recently, lots of research works have been actively focused on the self-driving car. In order to implement the self-driving car, lots of fusion techniques should be merged and, specially, it is noted that a vehicle-attached camera can provide several useful functionalities such as traffic lights recognition, pedestrian detection, stop-line recognition including simple driving records. Accordingly, as one of the efficient tools for the self-driving car implementation, this paper proposes a mathematical model for estimating effectively the road distance with a vehicle-attached black box camera. The proposed model can be effectively used for estimating the road distance by using the height of black box camera or the widths of the referenced road line and the observed road line. Through several simulations, it is shown that the proposed model is effective in estimating the road distance.

• Journal of the Korea Society of Computer and Information
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• v.17 no.11
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• pp.33-38
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• 2012

An free-fall object is received only force of gravity. Movement that only accept gravity is free-fall movement, and a free-falling object is free falling body. In other words, free falling body is only freely falling objects under the influence of gravity, regardless of the initial state of objects movement. In this paper, we assume, ignoring the resistance of the air, and the free-fall acceleration by the height does not change within the range of the short distance in the vertical direction. Under these assumptions, we can know about time and maximum height to reach the peak point from jumping vertically upward direction, time and speed of the car return to the starting position, and time and speed when the car fall to the ground. It can be measured by jumping degree and risk of accident from car or motorcycle in telematics.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.39 no.2
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• pp.235-240
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• 2015

Active Safety system is requested on the market of the medium and heavy duty commercial vehicle over 4.5ton beside the market of passenger car with advancement of the digital equipment proportionally. Unlike the passenger car, the mounting position of camera in case of the medium and heavy duty commercial vehicle is relatively high, it is disadvantaged conditions for lane recognition in contradiction to passenger car. In this work, we show the method of lane recognition through the Sobel edge, based on the spatial domain processing, Hough transform and color conversion correction. Also we suggest the low error method of front vehicles recognition in order to reduce the detection error through Haar-like, Adaboost, SVM and Template matching, etc., which are the object recognition methods by frontal camera vision. It is verified that the reliability over 98% on lane recognition is obtained through the vehicle test.

• Journal of the Korea Society of Computer and Information
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• v.12 no.5
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• pp.313-319
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• 2007

In this paper, we propose a novel method to extract an area of car licence plate and codes of vehicle number from a photographed car image using features on vertical edges and a new Fuzzy neural network algorithm to recognize extracted codes. Prewitt mask is used in searching for vertical edges for detection of an area of vehicle number plate and feature information of vehicle number palate is used to eliminate image noises and extract the plate area and individual codes of vehicle number. Finally, for recognition of extracted codes, we use the proposed Fuzzy neural network algorithm, in which FCM is used as the learning structure between input and middle layers and Max_Min neural network is used as the learning structure within inhibition and output layers. Through a variety of experiments using real 150 images of vehicle, we showed that the proposed method is more efficient than others.

• Journal of the Korea Society of Computer and Information
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• v.25 no.3
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• pp.117-127
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• 2020

Recently, proving insurance fraud has become increasingly difficult because it occurs intentionally and secretly via organized and intelligent conspiracy by specialists such as medical personnel, maintenance companies, insurance planners, and insurance subscribers. In the case of car accidents, it is difficult to prove intentions; in particular, an insurance company with no investigation rights has practical limitations in proving the suspicions. This paper aims reveal that the detection of organized and conspired insurance fraud, which had previously been difficult, could be dramatically improved through conspiring insurance fraud detection modeling using social network analysis and visualization of the relation between suspected group entities and by seeking developmental research possibilities of data analysis techniques.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.6
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• pp.599-608
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• 2017

Cracks on the asphalt road surface can affect the speed of the car, the consumption of fuel, the ride quality of the road, and the durability of the road surface. Such cracks in roads can lead to very dangerous consequences for long periods of time. To prevent such risks, it is necessary to identify cracks and take appropriate action. It takes too much time and money to do it. Also, it is difficult to use expensive laser equipment vehicles for initial cost and equipment operation. In this paper, we propose an effective detection method of road surface defect using ROI (Region of Interest) setting and cany edge detection method using UAV image. The results of this study can be presented as efficient method for road surface flaw detection and maintenance using UAV. In addition, it can be used to detect cracks such as various buildings and civil engineering structures such as buildings, outer walls, large-scale storage tanks other than roads, and cost reduction effect can be expected.