• Journal of Korea Multimedia Society
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• v.8 no.11
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• pp.1496-1509
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• 2005

In this paper, an adaptive license plate recognition system which detects and recognizes license plate at real-time by using projected plane convolution and Decision Tree Classifier is proposed. And it was tested in circumstances which presence of complex background. Generally, in expressway tollgate or gateway of parking lots, it is very difficult to detect and segment license plate because of size, entry angle and noisy problem of vehicles due to CCD camera and road environment. In the proposed algorithm, we suggested to extract license plate candidate region after going through image acquisition process with inputted real-time image, and then to compensate license size as well as gradient of vehicle with change of vehicle entry position. The proposed algorithm can exactly detect license plate using accumulated edge, projected convolution and chain code labeling method. And it also segments letter of license plate using adaptive binary method. And then, it recognizes license plate letter by applying hybrid pattern vector method. Experimental results show that the proposed algorithm can recognize the front and rear direction license plate at real-time in the presence of complex background environments. Accordingly license plate detection rate displayed $98.8\%$ and $96.5\%$ successive rate respectively. And also, from the segmented letters, it shows $97.3\%$ and $96\%$ successive recognition rate respectively.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 1998.04a
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• pp.271-276
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• 1998

To apply the wear resistant steel plate for heavy duty vehicle, the wear characterisms of various kinds of commercial steel plates were invesigated by dry sand/rubber wheel tester which was tested under scratch abrasion mode. The wear tested pnaterials were boron steels which were manufactured by thereto machanical control process (TMCP) in order to achieve higher hardness. As the result of the test, wear resistance of steel plate increases with the hardness and carbon content. The wear loss of wear resistance steel plate (Hv440) is a half times than tinat of SWS490A (Hv160) steel plate in dry sand-rubber wheel test and the result in field test is similar to this dry sand/rubber wheel test result. Therefore, dry sand/rubber wheel tester can be used to predict the scratch abrasion life of the parts for heavy duty vehicle.

• Proceedings of the KSME Conference
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• 2003.04a
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• pp.1566-1571
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• 2003

The cold plate used for a CEU(Control Electronics Unit) of an EV(Electric Vehicle) is extremely important since the dissipation of the heat generated from power devices like IGBT(Insulated Gate Bipolar Transistor) and diode has a significant effect on the performance as well as the durability of the CED. The cold plate consists of seven power devices, and coolant flows through the passage bonded to a groove of the cold plate. In order to find out heat transfer and pressure drop characteristics, series of numerical analyses for the cold plate with enhanced coolant passages were conducted. Based on results of the numerical analyses, an improved model of the cold plate has been proposed. The experiments under the various conditions have been conducted to compare the performance of the proposed cold plate to the present one. As a result of the numerical analyses together with the experiments, the ideal design of the cold plate could be offered.

• Computers and Concrete
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• v.32 no.2
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• pp.207-215
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• 2023

This paper investigates wave propagation in functionally graded carbon nano-reinforced composite (FG-CNTRC) plates under the influence of temperature based on Reddy' plate model. The material properties of Carbon Nanotubes (CNTs) are size-dependent, and the volume fraction of CNTs varies only along the thickness direction of the plate for different CNTs reinforcement modes. In addition, the material properties of CNTs can vary for different temperature parameters. By solving the eigenvalue problem, analytical dispersion relations can be derived for CNTRC plates. The partial differential equations for the system are derived from Lagrange's principle and higher order shear deformation theory is used to obtain the wave equations for the CNTRC plate. Numerical analyses show that the wave propagation properties in the CNTRC plate are related to the volume fraction parameters of the CNTRC plate and the distribution pattern of the CNTs in the polymer matrix. The effects of different volume fractions of CNTs and the distribution pattern of carbon nanotubes along the cross section (UD-O-X plate) are discussed in detail.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.3D
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• pp.349-352
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• 2006

To cope with traffic congestion, traffic accidents and lack of parking facilities, caused by dramatic increase in total vehicle number, vigorous researches on managing vehicles efficiently are done, both domestically and internationally. The vehicle license plate recognition makes effective management of traffic possible, with its wide application in many fields, covering from speed enforcement, collecting toll, stolen vehicle detection to parking management. The vehicle license plate recognition system causes high cost for collecting training data. Many researches are done by using the virtual sample method, which can be effective for utilizing limited number of training data by generating virtual sample. This paper investigates techniques to improve the performance of vehicle license plate recognition by using the training data's annexation. Also, popular methods for virtual sample creation used for text recognition algorithm are analyzed and their effectiveness is verified.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.10a
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• pp.564-567
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• 2004

In this thesis, a method is proposed to extract the car plate at the rear side of vehicle using blobs. We first extract the blobs in the input images using intensity variations and calculate the minimum horde. rectangle (MBR) of each blobs. It is followed that we select groups of blobs having similar width, centroid. And then, we try to detect the border lines of car plate and verify whether the area is a car plate or not using NN.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.6 no.1
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• pp.6-17
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• 2013

Recently, the color of vehicle license plate has been changed from green to white. Thus the vehicle plate recognition system used for parking management systems, speed and signal violation detection systems should be robust to the both colors. This paper presents a vehicle license plate recognition system, which works on both of green and white plate at the same time. In the proposed system, the image of license plate is taken from a captured vehicle image by using morphological information. In the next, each character region in the license plate image is extracted based on the vertical and horizontal projection of plate image and the relative position of individual characters. Finally, for the recognition process of extracted characters, PCA(Principal Component Analysis) and LDA(Linear Discriminant Analysis) are sequentially utilized. In the experiment, vehicle license plates of both green background and white background captured under irregular illumination conditions have been tested, and the relatively high extraction and recognition rates are observed.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.9
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• pp.1531-1540
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• 2016

In this paper, we propose vehicle license plate recognition system based on Radial Basis Function Neural Networks (RBFNNs) with the use of local binarization functions and canny edge algorithm. In order to detect the area of license plate and also recognize license plate numbers, binary images are generated by using local binarization methods, which consider local brightness, and canny edge detection. The generated binary images provide information related to the size and the position of license plate. Additionally, image warping is used to compensate the distortion of images obtained from the side. After extracting license plate numbers, the dimensionality of number images is reduced through Principal Component Analysis (PCA) and is used as input variables to RBFNNs. Particle Swarm Optimization (PSO) algorithm is used to optimize a number of essential parameters needed to improve the accuracy of RBFNNs. Those optimized parameters include the number of clusters and the fuzzification coefficient used in the FCM algorithm, and the orders of polynomial of networks. Image data sets are obtained by changing the distance between stationary vehicle and camera and then used to evaluate the performance of the proposed system.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.7
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• pp.718-723
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• 2014

In this paper, we developed the inspection system of electric vehicle battery plate using image processing. Four cameras are used for acquiring the principal parts of the plate, and several steps of image processing for extracting significant dimensions of the plate such as widths and lengths. As a preceding step, calibration of four cameras is carried for compensating distorted images using dot-arrayed sheet. Coordinate systems for four cameras are defined where one coordinate system is assigned to the reference coordinate system to which the others are relatively described. Line information of the edge in the windowed image is extracted using elaborate edge-detection algorithm, and finally the intersection points between lines are extracted to calculate widths and lengths of the plate from which the error status of the battery plate is decided.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.8
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• pp.89-96
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• 2017

This Paper proposes a vehicle detection system and a license plate recognition system from CCTV images installed on public roads. Since the environment of this system acquires the image in the general road environment, the stable condition applied to the existing vehicle entry / exit system is not given, and the input image is distorted and the resolution is irregular. At the same time, the viewing angle of the input image is more wide, so that the computation load is high and the recognition accuracy of the plate is likely to be lowered. In this paper, we propose an improved method to detect and recognize a license plate without a separate input control devices. The vehicle and license plate were detected based on the HOG feature descriptor, and the characters inside the license plate were recognized using the k-NN algorithm. Experimental environment was set up for the roads more than 45m away from the CCTV, Experiments were carried out on an entry vehicle capable of visually identifying license plate and Experimental results show good results of the proposed method.