• Journal of computational fluids engineering
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• v.14 no.1
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• pp.70-77
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• 2009

In this study, time-dependent numerical analysis was carried out to investigate the plasma jet impingement on a flat plate, and a compressible form of two-dimensional inviscid gas dynamics equations were solved using the flux corrected transport algorithm. The mathematical modeling of Joule heating in the polycarbonate capillary bore and the mass ablation from the bore wall was incorporated in the numerical analysis and the series of computation was performed for three cases depending on the distance of the opposing plate from the capillary exit. The computational results reveal that the presence of the opposing plate does not affect the flow conditions inside the capillary when compared to the case of open-air plasma discharge. In the exterior region, the flow structure shows the typical supersonic underexpanded jet which consists of the strong Mach disk in front of the opposing plate and the barrel shock at the side of the jet. It is found that the shock evolution becomes more quasi-steady when the plate distance decreases. Also, the effects of the distance between the capillary bore exit and the opposing plate on the flow conditions along the opposing plate are investigated and the pressure variation on the plate shows more complicated interaction between the plasma discharge and the opposing plate when the location of plate becomes closer to the capillary exit.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.5
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• pp.2509-2528
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• 2019

There are various styles of license plates for different countries and use cases that require style-specific methods. In this paper, we propose and illustrate a multi-style license plate recognition system. The proposed system performs a series of processes for license plate candidates detection, structure classification, character segmentation and character recognition, respectively. Specifically, we introduce a license plate structure classification process to identify its style that precedes character segmentation and recognition processes. We use a K-Nearest Neighbors algorithm with pre-training steps to recognize numbers and characters on multi-style license plates. To show feasibility of our multi-style license plate recognition system, we evaluate our system for multi-style license plates covering single line, double line, different backgrounds and character colors on Korean and the U.S. license plates. For the evaluation of Korean license plate recognition, we used a 50 minutes long input video that contains 138 vehicles of 6 different license plate styles, where each frame of the video is processed through a series of license plate recognition processes. From two experiments results, we show that various LP styles can be recognized under 50 ms processing time and with over 99% accuracy, and can be extended through additional learning and training steps.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.3
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• pp.1-8
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• 2016

We propose an adaptive histogram stretching algorithm for application to a car's personal recorder. The algorithm was used for pre-processing to detect the license plate region in an image from a personal recorder. The algorithm employs a Probability Density Function (PDF) and Cumulative Distribution Function (CDF) to analyze the distribution diagram of the images. These two functions are calculated using an image obtained by sampling at a certain pixel interval. The images were subjected to different levels of stretching, and experiments were done on the images to extract their characteristics. The results show that the proposed algorithm provides less deterioration than conventional algorithms. Moreover, contrast is enhanced according to the characteristics of the image. The algorithm could provide better performance than existing algorithms in applications for detecting search regions for license plates.

• Journal of Korean Association for Spatial Structures
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• v.7 no.5
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• pp.67-74
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• 2007

The unsymmetrically layered artificial material model is consistently introduced to find the optimum topologies of the plate structures. Reissner-Mindlin (RM) plate theory is adopted to formulate the present 9-node plate element considering the first-order shear deformation of the plates. In the topology optimization process, the strain energy to be minimized is employed as the objective function and the initial volume of structures is adopted as the constraint function. In addition, the resizing algorithm based on the optimality criteria is used to update the hole size introduced in the proposed artificial material model. Several numerical examples are rallied out to investigate the performance of the proposed technique. From numerical results, the proposed topology optimization techniques are found to be very effective to produce the optimum topology of plate structures. In particular, the proposed unsymmetric stiffening layer model make it possible to produce more realistic stiffener design of the plate structures.

• Journal of the Korea Convergence Society
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• v.12 no.1
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• pp.29-35
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• 2021

License plate recognition plays a key role in intelligent transportation systems. Therefore, it is a very important process to efficiently detect the number and character areas. In this paper, we propose a method to effectively detect license plate number area by applying deep learning and semantic image segmentation algorithm. The proposed method is an algorithm that detects number and text areas directly from the license plate without preprocessing such as pixel projection. The license plate image was acquired from a fixed camera installed on the road, and was used in various real situations taking into account both weather and lighting changes. The input images was normalized to reduce the color change, and the deep learning neural networks used in the experiment were Vgg16, Vgg19, ResNet18, and ResNet50. To examine the performance of the proposed method, we experimented with 500 license plate images. 300 sheets were used for learning and 200 sheets were used for testing. As a result of computer simulation, it was the best when using ResNet50, and 95.77% accuracy was obtained.

• Transactions of Materials Processing
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• v.22 no.5
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• pp.250-257
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• 2013

A series of finite element analyses of the rolling process were performed and a neural network algorithm was employed to calculate the amount of ski-effect for an arbitrary thickness of incoming material in the roll gap. Pilot hot plate rolling tests were also conducted to verify the usefulness of the finite element analyzes conducted in this study. In these experiments, plates with thicknesses varying from 25 to 65 mm were tested. In addition, a number of rolling reductions of up to 31% were examined. Finally, a number of circumferential upper and lower rolls were investigated. Experimental validations demonstrated that the neural network algorithm predicted the proper amount of ski when rolling conditions(material thickness, reduction ratio, roll velocity differential) changed arbitrarily.

• Journal of the Korea institute for structural maintenance and inspection
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• v.6 no.3
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• pp.139-149
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• 2002

An explicit direct time integration method based solution algorithm is proposed to predict dynamic postbuckling response of thin plates. Based on the von Karman's plate equations and Marquerre's shallow shell theory, a rectangular plate finite element is formulated and utilized in this study. The element formulation takes into account geometrical nonlinearity and initial deflection of plates. The solution algorithm employs the central difference method. Using the computer program developed by the authors, dynamic postbuckling behavior of elastic thin plates under impact loading is investigated by considering the time variation of load and load duration. The efficiency of the proposed solution algorithm is examined through illustrative numerical examples.

• Journal of the Society of Naval Architects of Korea
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• v.31 no.4
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• pp.139-146
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• 1994

In this paper a feasible way toward the automation for plate forming by line heating method is proposed. For this a mechanical model representing the line heating phenomenon is adopted and a reasonable algorithm is introduced to search the heating path under the given heating conditions, which can produce the surface very similar to the given surface. A computer program system has been developed according to the proposed algorithm here. It has been applied to two curved shapes to show its validity. From the results it has been found that the proposed algorithm and the developed computer program system give a good result and can be a possible way getting to the automation system of plate forming by the line heating method.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.1583-1584
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• 2007

To test the performance of the proposed algorithm, images of seventy vehicle were tested. The success rates for license plate and character recognition were approximately 98.4% and 96.3%, respectively.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2006.11a
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• pp.203-207
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• 2006

Nowadays, Cars are continuing to grow at an alarming rate but they also cause many problems such as traffic accident, pollutions and so on. One of the most effective methods that prevent traffic accidents is the use of traffic monitoring systems, which are already widely used in many countries. The monitoring system is beginning to be used in domestic recently. An intelligent monitoring system generates photo images of cars as well as identifies cars by recognizing their plates. That is, the system automatically recognizes characters of vehicle plates. An automatic vehicle plate recognition consists of two main module: a vehicle plate locating module and a vehicle plate number identification module. We study for a vehicle plate number identification module in this paper. We use image preprocessing, feature extraction, multi-layer neural networks for recognizing characters of vehicle plates and we present a feature-comparison method for improving the performance of vehicle plate number identification module. In the experiment on identifying vehicle plate number, 300 images taken from various scenes were used. Of which, 8 images have been failed to identify vehicle plate number and the overall rate of success for our vehicle plate recognition algorithm is 98%.