• Journal of the Korea Society of Computer and Information
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• v.13 no.6
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• pp.273-278
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• 2008

Cars attaching new license plates are increasing after introducing the new format of car license plate in Korea. Therefore, a car new license plate recognition system is required for various fields using automatic recognition of car license plates, automatic parking management systems and arrest of criminal or missing vehicles. In this paper, we proposed an intelligent new car license plate recognition method for the various fields. The proposed method is as follows. First of all, an acquired color image from a surveillance camera is converted to a gray level image and binarized by block binarization method. Second, noises of the binarized image removed by morphological characteristics of cars and then license plate area is extracted. Third, individual characters are extracted from the extracted license plate area using Grassfire algorithm. lastly, the extracted characters are learned and recognized by a fuzzy ART algorithm for final car license plate recognition. In the experiment using 100 car images, we could see that the proposed method is efficient.

• The Journal of the Korea institute of electronic communication sciences
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• v.5 no.5
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• pp.471-476
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• 2010

In this paper, we propose an effective method that recognizes the vehicle license plate using RGB color information and back-propagation neural network algorithm. First, the image of the vehicle license plate is adjusted by the Mean of Blue values in the vehicle plate and two candidate areas of Red and Green region are classified by calculating the differences of pixel values and the final Green area is searched by back-propagation algorithm. Second, our method detects the area of the vehicle plate using the frequence of the horizontal and the vertical histogram. Finally, each of codes are detected by an edge detection algorithm and are recognized by error back-propagation algorithm. In order to evaluate the performance of our proposed extraction and recognition method, we have run experiments on a new car plates. Experimental results showed that the proposed license plate extraction is better than that of existing HSI information model and the overall recognition was effective.

• The Journal of the Korea institute of electronic communication sciences
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• v.5 no.3
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• pp.304-308
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• 2010

In this paper, we propose a new method of recognizing the vehicle license plate using color space, morphological characteristics and ART2 algorithm. Morphological characteristics of old and/or new style vehicle license plate among the candidate regions are applied to remove noise areas using 8-directional contour tracking algorithm, then follow by the extraction of vehicle plate. From the extracted license plate area, plate morphological characteristics of each region are removed. After that, labeling algorithm to extract the individual characters are then combined. The classified individual character and numeric codes are applied to the ART2 algorithm for the learning and recognition. In order to evaluate the performance of our proposed extraction and recognition of vehicle license method, we have run experiments on 100 green plates and white plates. Experimental results shown that the proposed license plate extraction and recognition method was effective.

• International Journal of Aeronautical and Space Sciences
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• v.11 no.3
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• pp.227-233
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• 2010

In this study, a genetic algorithm was utilized to optimize the stacking sequence of a composite plate subjected to a high velocity impact. The aim is to minimize the maximum backplane displacement of the plate. In the finite element model, we idealized the impactor using solid elements and modeled the composite plate by shell elements to reduce the analysis time. Various tests were carried out to investigate the effect of parameters in the genetic algorithm such as the type of variables, population size, number of discrete variables, and mutation probability.

• The Journal of the Korea Contents Association
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• v.11 no.3
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• pp.1-8
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• 2011

Automatic vehicle license plate recognition technology is widely used in gate control and parking control of vehicles, and police enforcement of illegal vehicles. However inherent geometric information of the license plate can be transformed in the vehicle images due to the slant and the sunlight or lighting environment. In this paper, a distortion invariant vehicle license plate extraction and recognition algorithm is proposed. First, a binary image reserving clean character strokes can be achieved by using a DoG filter. A plate area can be extracted by using the location of consecutive digit numbers that reserves distortion invariant characteristic. License plate is recognized by using neural networks after geometric distortion correction and image enhancement. The simulation results of the proposed algorithm show that the accuracy is 98.4% and the average speed is 0.05 seconds in the recognition of 6,200 vehicle images that are obtained by using commercial LPR system.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.8
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• pp.713-717
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• 2015

In this paper, we propose camber monitoring system which is using on hot rolling process. In roughing mill which is one of the rolling part in hot rolling process, steel plate can be bended in width direction under the imbalance of rolling condition. This bending of steel plate in width direction is called as camber. In order to measure the camber, first, cameras which are installed over transport pathway of steel plate take pictures of whole shape of steel plate. And location value of steel plate edge is extrated from these pictures by edge detection algorithm. But, there are a lot of noises which are generated by such as water sprays, dusts, peripheral equipments in these pictures, and these noises make edge detection difficult. In order to solve this kind of problem, we developed a direction selective edge detection algorithm, and applicated in our camber monitoring system. As a result, we got stable results in spite of process noises.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.7
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• pp.1248-1254
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• 2010

Authors conducted a deduction of some parameters using the magnetic equivalent circuit method and a verification study of the thrust force control algorithm of a rotary-typed small-scaled linear induction motor for a railway transit. In a LIM, it is possible to express the parameters of the magnetic equivalent circuit into a function of the shape of the secondary aluminium plate and the airgap between the LIM primary core and the secondary aluminium plate. It means that the LIM properties can be changed considerably by the shape of the secondary aluminium plate and the airgap between the LIM primary core and the secondary aluminium plate. So, authors analyzed a tendency of changes of the magnetic equivalent circuit parameters and the LIM characteristics by changing of the airgap of the secondary aluminium plate of a rotary-typed small-scaled LIM. And authors conducted a verification study of the indirect vector control algorithm with constant slip frequency by using the rotary-typed small-scaled LIM tester set on the basis of the calculated LIM parameters. Finally authors accomplished a research on applicability for LIM railway transit.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.1037-1038
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• 2008

Since the characters are not clear always due to lighting conditions, sometimes only a part of the characters are detected and the boundary of the number plate is not completely shown. To solve this problem, this paper presents a new efficient algorithm for segmenting the number plate using the topological relationship among the characters in the number plate and its outer contour. The boundary of the number plate is estimated using the detected characters and detected by testing the connectivity of the vertical and horizontal edges. The superior performance of the proposed algorithm has been proved by the experiments.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.15 no.2 s.95
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• pp.232-238
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• 2005

This paper proposed an optimal plate spring design for the optical pickup suspension. This method requires an analytic solution of plate spring suspension and it can be obtained by Castigliano's theorem and moment equilibrium. However, it is very complex due to the many design variables coupled and some constraints such as pitching angle in focusing motion caused by the characteristics of plate spring. Because of the complex formulation of the analytical solution that is used as the design objective, the genetic algorithm is used to find the optimal design value satisfying design constraints.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1997.04a
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• pp.434-439
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• 1997

This paper presents the active control of a flexible plate vibration. The plate was excited by white noise point force and the control was performed by one or two piezo ceramic actuator bonded to the surface of the plate. An adaptive controller based on filtered-x or multiple filtered-x LMS algorithm was used and the controller was defined by minimizing the square of the response of error sensor. In the experiment, PZT sensor was used as an error sensor while white noise was applied as a disturbance. In the case of multiple channel control, more than 22 dB of vibration reduction was achieved. Results indicate that the vibration of a flexible plate could be controlled effectively when the piezo ceramic actuator was used with multiple filtered-x LMS algorithm.