• Proceedings of the IEEK Conference
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• 2000.07b
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• pp.785-788
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• 2000

The recognition system of a car plate is largely classified as the extraction and recognition of number plate. In this paper, we extract the number plate domain by using a thresholding method as a preprocess step. The computation of the density in a given mask provides a clue of a candidate domain whose density ratio corresponds to the properties of the number plate obtained in the best condition. The contour of the number plate for the recognition of the texts of number plate is extracted by operating Kohonen Algorithm in a localized region. The algorithm reduces noises around the contour. The recognition system with the density computation and Kohonen Algorithm shows a high performance in the real system in connection with a car number plate.

• Journal of Korea Multimedia Society
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• v.18 no.10
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• pp.1172-1179
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• 2015

A wireless license plate region extracting module is proposed for LPR system controlling multiple gates. This module is cheaply implemented using Raspberry Pi which is open source and high performance. First, as the upper 1/3 of the captured image is discarded as it has no useful information on license plate. Using the OpenCV libraries the edge image is got by Canny algorithm after applying Gaussian filtering to gray image, and the labeling is conducted for 4 consecutive numbers in license plate. These numbers are located using various decision equations, and expanding the numbers region the final license plate region can be extracted. The result image is transferred to Server using wifi direct. Using the proposed module it becomes easy to set up and maintain the LPR system. The experimental results showed that the successful extracting rate was 98.4% using 500 car images with 640 × 480 resolution.

• Structural Engineering and Mechanics
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• v.53 no.1
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• pp.131-146
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• 2015

In the present paper a three-dimensional non-linear truss element and a short computer program for the modeling and predicting approximate lateral deflections in thin glass plates by the method of incremental loading are proposed. Due to the out-of-plane large deflections of thin glass plates compared to the plate thickness within each loading increment, the equilibrium and stiffness conditions are written with respect to the deformed structure. An application is presented on a thin fully tempered monolithic rectangular glass plate, laterally supported around its perimeter subjected to uniform wind pressure. The results of the analysis are compared with published experimental results and found to have satisfactory approximation. It is also observed that the large deflections of a glass plate lead to a part substitution of the bending plate behavior by a tensioned membrane behavior which is favorable.

• Journal of the Korea Society of Computer and Information
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• v.12 no.6
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• pp.261-268
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• 2007

In this paper, We propose a new technique extract efficiently a car number plate based on edge projection. In order to obtain the region of car number plate, we use a motive that the luminance differences between the number plate background and characters. And, we introduce a projection technique to obtain character parts based on edge image. In vertical direction. we propose a shape matching method. Specially the new number plate standard has more characters than the old one in horizontal direction and, it is efficiently used to extract the number plate. Therefore, the proposed technique is useful to the new number plate standard. In simulation results. We have illustrated that our algorithm can recognize different number plates with a success ration of 90%.

• Journal of Information Processing Systems
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• v.12 no.1
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• pp.100-108
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• 2016

In this paper, we propose a method to achieve improved number plate detection for mobile devices by applying a multiple convolutional neural network (CNN) approach. First, we processed supervised CNN-verified car detection and then we applied the detected car regions to the next supervised CNN-verifier for number plate detection. In the final step, the detected number plate regions were verified through optical character recognition by another CNN-verifier. Since mobile devices are limited in computation power, we are proposing a fast method to recognize number plates. We expect for it to be used in the field of intelligent transportation systems.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2003.10b
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• pp.36-39
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• 2003

Due to the strength and biocompatibility requirement, the stainless steel SUS 316L is widely used for trauma internal fixation device. SUS 316L can be hardened and strengthened only by cold work. In this work, the material compression test is performed both in laboratory and computer simulation by a FEM analysis software DEFORM to correlate the hardness to strain. This data is then used for preform design and predict the hardness of the finish bone plate forging. Finally, we compared the hardness between the actual forging and computer analysis results. Although the predicted hardness from computer simulation. is 55HV higher than the final forging sample, we can get good compatibility on the hardening tendency of cold forging.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2006.05a
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• pp.792-795
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• 2006

In this paper, we propose a method of vehicle license plate recognition on PDA for illegal parking car regulation. we classified three kinds of vehicle license plates being used down to date since the introduction of each vehicle license Plate using features of each one. And we recognized vehicle license plates segmentation the AreaName, the AreaCode, the TypeCharacter and the Numbers. A 88.7% recognition accuracy was obtained through the experiment of the proposed vehicle license plate recognition system using the obtained images of PDA.

• JSTS:Journal of Semiconductor Technology and Science
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• v.1 no.2
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• pp.132-139
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• 2001

We considered the uniformity of fabricated micromirror arrays by characterizing the fabrication process and calculating the appropriate driving voltages of micromirrors used as virtual photomask in maskless photolithography. The uniformity of the micromirror array in terms of driving voltage and optical characteristics is adversely affected by factors, such as the air gap between the bottom electrode and the mirror plate, the spring shape and the deformation of the mirror plate or torsion spring. The thickness deviation of the photoresist sacrificial layer, the misalignment between mirror plate and bottom electrode, the aluminum deposition condition used to produce the spring and the mirror plate, and initial mirror deflection were identified as key factors. Their importance lies in the fact that they are related to air gap deviations under the mirror plate, asymmetric driving voltages in left and right mirror directions, and the deformation of the Al sring or mirror plate after removal of the sacrificial layer. The plasma ashing conditions used for removing the sacrificial layer also contributed to the deformation of the mirror plate and spring. Driving voltages were calculated for the pixel operation of the micromirror array, and the non-uniform characteristics of fabricated micromirrors were taken into consideration to improve driving performance reliability.

• Journal of the Korea Society of Computer and Information
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• v.27 no.4
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• pp.19-26
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• 2022

With the recent development of intelligent transportation systems, car license plate recognition systems are being used in various fields. Such systems need to guarantee real-time performance to recognize the license plate of a driving car. Also, they should keep a high recognition rate even in problematic situations such as small license plates in low-resolution and unclear image due to distortion. In this paper, we propose a real-time car license plate recognition system that improved processing speed using object detection algorithm based on anchor-free method and text recognition algorithm based on Convolutional Neural Network(CNN). In addition, we used Spatial Transformer Network to increase the recognition rate on the low resolution or distorted images. We confirm that the proposed system is faster than previously existing car license plate recognition systems and maintains a high recognition rate in a variety of environment and quality images because the proposed system's recognition rate is 93.769% and the processing speed per image is about 0.006 seconds.

• Proceedings of the Korea Information Processing Society Conference
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• 2009.11a
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• pp.333-334
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• 2009

In this paper, I propose the novel method based on Labeled Hough transform and GLCM(Grey-Level Co-occurrence Matrix) for license plate detection. A lot of conventional methods have been proposed to detect the license plate, but those are useless in order to detect the license plate well in case of dark or unstable images. Histogram equalization is preprocessed to each image before applying this method. As a result, the license plate is detected accurately