• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.5
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• pp.379-387
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• 2001

We proposed an enhanced extraction method of vehicle plate, in which both the brightness variation of gray and the Hue value of HSI color model were used. For the extraction of the vehicle plate from a vehicle image, first of all, candidate regions for the vehicle plate were extracted from the image by using the property of brightness variation of the image. A real place region was determined among candidate regions by the density of pixels with the Hue value of green and white. For- extracting the feature area containing characters from the extracted vehicle plate, we used the histogram-based approach of individual characters. And we proposed and applied for the recognition of characters the enhanced ART2 algorithm which support the dynamical establishment of the vigilance threshold with the genera]iced union operator of Yager. In addition, we propose an enhanced SOSL algorithm which is integrated both enhanced ART2 and supervised learning methods. The performance evaluation was performed using 100's real vehicle images and the evaluation results demonstrated that the extraction rates of tole proposed extraction method were improved, compared with that of previous methods based un brightness variation, RGB and HSI individually . Furthermore, the recognition rates of the proposed algorithms were improved much more than that of the conventional ART2 and BP algorithms.

• 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.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.05a
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• pp.918-923
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• 2007

Currently, automotive industries improve the vehicle performance and reduce the development period of vehicle using each module part for the high quality and performance of vehicles. However each component part doesn't generate the noise and vibration problems, sometime these problems are generated on the assembly status between vehicle chassis frame and each module part. On this study, in order to analysis the dynamic characteristics of a shield door module that is a typical module part of vehicles, the acquisition and evaluation process about the vibration and noise of shield door module is developed. Also the possibility to apply to shield door module of the developed process is verified by the comparison with the dynamic characteristics between plastic and steel module plate.

• Journal of Auto-vehicle Safety Association
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• v.10 no.1
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• pp.6-11
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• 2018

Recently, many drivers of two-wheeled motorcycles in leisure and express delivery industries etc. brought increasing issues for the motorcycle safety. This paper has studied the structural safety of two-wheeled motorcycles considering the regulations for stand, rear registration plate and anti-tampering measures. The authors have investigated and compared a variety of international and domestic regulations and specifications for structural safety of those components. Detailed experimental procedures of stand, mounting for rear registration plate and anti-tampering measures are proposed to secure the two-wheeled motorcycle safety and the outcomes of this study can be used to confirm the Korean motor vehicle safety standards.

• Proceedings of the KSR Conference
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• 2002.10b
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• pp.1041-1046
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• 2002

A railway open deck plate girder bridge without ballast should support relatively heavier vehicle loads compared with its self-weight. For such a reason, actual dynamic response of the bridge is considerably differing with normal prediction because additional masses added from vehicle to a bridge have an effect on the dynamic characteristics of the bridge. These differences affect to the estimation of a natural frequency change that adopted for one of the evaluation technique of strength decrease, and these make trouble to the analysis of a natural frequency from the field test data that measured at the bridge subjected to a running vehicle. In this study, classification of mass participation ratio for each component of open deck plate girder bridge without ballast and the comparison according to the change of vibration characteristics for the case of subjected to a running vehicle were accomplished.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.408-410
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• 2014

In this paper a license plate area extraction of labeling the vehicle images is proposed. Studies on license plate recognition systems have largely been conducted and there is a tendency of increasing license plate recognition rates. In this paper a license plate region is extracted from an image labeling for the region of interest and research on technology for labeling sample image using the Otsu algorithm to binary.

• Smart Media Journal
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• v.9 no.2
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• pp.92-98
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• 2020

This paper proposes a vehicle license plate recognition system using light weight deep learning models without high-end server. The proposed license plate recognition system consists of 3 steps: [license plate detection]-[character area segmentation]-[character recognition]. SSD-Mobilenet was used for license plate detection, ResNet with localization was used for character area segmentation, ResNet was used for character recognition. Experiemnts using Samsung Galaxy S7 and LG Q9, accuracy showed 85.3% accuracy and around 1.1 second running time.

• International Journal of Naval Architecture and Ocean Engineering
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• v.9 no.1
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• pp.55-65
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• 2017

Underwater torpedo has control fin with very low aspect ratio due to launching from limited size of cylindrical torpedo tube. If the aspect ratio of control fin of underwater vehicle is very low three-dimensional flow around control fin largely reduces control forces. In this study, the end plate was applied to reduce the three-dimensional flow effects of partially movable control fin of underwater vehicle. Through numerical simulations the flow field around control fin was examined with and without end plate for different flap angles. The pressure, vorticity, lift and torque on the control fin were analyzed and compared to experiments. The comparison have shown a reasonable agreement between numerical and experimental results and the effect of end plate on a low aspect ratio control fin. When the end plate was attached to the movable control fin, the lift increased and the actuator shaft torque did not significantly change. As this means less consumption of the actuator shaft torque compared to the control fin that has the same control force, the inner actuator capacity can be reduced and energy consumption can be saved. Considering this, it is expected to be effectively applied to the control fin design of underwater vehicles such as torpedoes.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1107-1109
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• 1996

In this paper, we discuss the automatic recognition system of vehicle types and licence plate numbers using artificial neural networks, which will be used as vehicle identifier. We confine to expose the vehicle licence number for violating bus lane and stolen cars. Therefore, the vehicle height, width and distribution profile are used as the feature parameters of vehicle type. This system is composed of two parts: one is an image preprocessor of vehicle images and the other one is a pattern classifier by neural networks. The experimental results show that our method has good results for the recognition of vehicle types and numbers.

• Proceedings of the Korea Information Processing Society Conference
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• 2012.04a
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• pp.429-431
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• 2012

Vehicle-logo recognition technology is very important in vehicle automatic recognition technique. The intended application is automatic recognition of vehicle type for secure access and traffic monitoring applications, a problem not hitherto considered at such a level of accuracy. Vehicle-logo recognition can improve Vehicle type recognition accuracy. So in this paper, introduces how to vehicle-logo recognition. First introduces the region of the license plate by algorithm and roughly located the region of car emblem based on the relationship of license plate and car emblem. Then located the car emblem with precision by the distance of Hausdorff. On the base, processing the region by morphologic, edge detection, analysis of connectivity and pick up the PCA character by lowing the dimension of the image and unifying the PCA character. At last the logo can be recognized using the algorithm of support vector machine. Experimental results show the effectiveness of the proposed method.