• The Journal of the Korea institute of electronic communication sciences
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• v.12 no.4
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• pp.651-656
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• 2017

In this study, we designed the system that helps drivers check all information about parking space at the entrance and find out whether the places is available or not, because the system has 'Image recognition function' which can even recognize car number plates exactly. Besides, we place the webcam close to the car number plate, so that car number can be identified more quickly. Finally, since we set the webcam high, the system keeps us from parking wrong places by displaying on the screen.

• The Journal of the Korea institute of electronic communication sciences
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• v.12 no.6
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• pp.1093-1098
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• 2017

In this study, we designed the system that helps drivers check all information about parking space at the entrance and find out whether the places is available or not, because the system has 'Image recognition function' which can even recognize car number plates exactly. Besides, we place the webcam close to the car number plate, so that car number can be identified more quickly. Finally, since we set the webcam high, the system keeps us from parking wrong places by displaying on the screen.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.12
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• pp.1114-1125
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• 2013

License Plate Detection (LPD) is a key component in automatic license plate recognition system. Despite the success of License Plate Recognition (LPR) methods in the past decades, the problem is quite a challenge due to the diversity of plate formats and multiform outdoor illumination conditions during image acquisition. This paper aims at automatical detection of car license plates via image processing techniques. In this paper, we proposed a real-time and robust method for license plate detection using Heuristic Energy Map(HEM). In the vehicle image, the region of license plate contains many components or edges. We obtain the edge energy values of an image by using the box filter and search for the license plate region with high energy values. Using this energy value information or Heuristic Energy Map(HEM), we can easily detect the license plate region from vehicle image with a very high possibilities. The proposed method consists two main steps: Region of Interest (ROI) Detection and License Plate Detection. This method has better performance in speed and accuracy than the most of existing methods used for license plate detection. The proposed method can detect a license plate within 130 milliseconds and its detection rate is 99.2% on a 3.10-GHz Intel Core i3-2100(with 4.00 GB of RAM) personal computer.

• Journal of Broadcast Engineering
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• v.25 no.5
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• pp.776-788
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• 2020

In this paper, a vehicle type recognition system using deep learning and a license plate recognition system are proposed. In the existing system, the number plate area extraction through image processing and the character recognition method using DNN were used. These systems have the problem of declining recognition rates as the environment changes. Therefore, the proposed system used the one-stage object detection method YOLO v3, focusing on real-time detection and decreasing accuracy due to environmental changes, enabling real-time vehicle type and license plate character recognition with one RGB camera. Training data consists of actual data for vehicle type recognition and license plate area detection, and synthetic data for license plate character recognition. The accuracy of each module was 96.39% for detection of car model, 99.94% for detection of license plates, and 79.06% for recognition of license plates. In addition, accuracy was measured using YOLO v3 tiny, a lightweight network of YOLO v3.

• Journal of Broadcast Engineering
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• v.24 no.5
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• pp.713-725
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• 2019

Automatic License Plate Recognition (ALPR) is a technology required for many applications such as Intelligent Transportation Systems and Video Surveillance Systems. Most of the studies have studied were about the detection and recognition of license plates on cars, and there is very little about detecting and recognizing license plates on motorbikes. In the case of a car, the license plate is located at the front or rear center of the vehicle and is a straight or slightly sloped license plate. Also, the background of the license plate is mainly monochromatic, and license plate detection and recognition process is less complicated. However since the motorbike is parked by using a kickstand, it is inclined at various angles when parked, so the process of recognizing characters on the motorbike license plate is more complicated. In this paper, we have developed a 2-stage YOLOv2 algorithm to detect the area of a license plate after detection of a motorbike area in order to improve the recognition accuracy of license plate for motorbike data set parked at various angles. In order to increase the detection rate, the size and number of the anchor boxes were adjusted according to the characteristics of the motorbike and license plate. Image warping algorithms were applied after detecting tilted license plates. As a result of simulating the license plate character recognition process, the proposed method had the recognition rate of license plate of 80.23% compared to the recognition rate of the conventional method(YOLOv2 without image warping) of 47.74%. Therefore, the proposed method can increase the recognition of tilted motorbike license plate character by using the adjustment of anchor boxes and the image warping which fit the motorbike license plate.

• Journal of Digital Convergence
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• v.16 no.9
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• pp.173-178
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• 2018

The vehicle collision speed in mid and high range can be checked by EDM(Event Driven memory) data recorded when the air bag works. But it's difficult to estimate the low speed of vehicle collision. And estimating the speed is important because the injury level can be changed by the impact speed. The study proposed an estimating algorithm by analysing the images recorded in car blackbox instrument. Low speed rear collision accidents simulated with wire winding motor for various vehicle types. The study estimated the impact speed with the ratio of the distance change between two vehicles and the length change of the number plate of front vehicle. The closer the vehicles are, the larger the plate length is. You can estimate the impact speed with the ratio. The impact speed is calculated with the initial distance for a specific length of number plate in the algorithm. The results can be applied to the linear rear collision because the angle of impact was not considered in this study.

• Journal of Adhesion and Interface
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• v.6 no.3
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• pp.10-18
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• 2005

The hard coatings on the polycarbonate plate were performed with the object of substitution the glass in the car to the polycarbonate plate. In this research, tetraethyl orthosilicate (TEOS), methyltriethoxysilane (MTES) were used to prepare the coatings by sol-gel process. The optimum conditions and formulation to get the excellent physical properties were determined. The pretreatment condition of polycarbonate plate, the mole ratio of TEOS and MTES, selection of the solvent, the aging time, the amount of acid catalyst, and the number of folds of coating were characterized. Pretreatment with poly(methyl methacrylate) was very effective to increase the adhesion strength. The smooth coating which got the 2 H class in pencil hardness was formed in this research by sol-gel process.

• Journal of the Korean Society of Safety
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• v.30 no.6
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• pp.1-6
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• 2015

The actual condition is that environmental pollution due to the development of various industries has recently become a serious issue. An interest in improving the gas mileage is rising due to an increase in the number of vehicles in the era of high oil price in particular. In order to solve this problem, priority should be given to light-weight design of car body, However, at present, a design method enabling the conventional steel plate to be replaced is direly needed in order to guarantee passengers' safety according to excessive light-weight design of car body. In this study, in order to apply a design method that could realize fuel savings and environmental pollution prevention through an improvement in gas mileage together with meeting the safety requirements for vehicles, it was supposed that CFRP/Al composites member would be used as primary structural member. And to this end, it was intended to obtain optimum design data by experimentally implementing external impulsive load applied to the car body. According to results of impact test of CFRP/Al composites member, a collapsed shape of folding, crack, and bending occurred. So, it was possible to find that energy was observed. And in case of specimen having an angle of $90^{\circ}$ in the outermost layer and stack sequence of $[90^{\circ}{_2}/0^{\circ}2]s$, its collapsed length was shown to be short. Therefore, it was possible to find that the absorbed energy was shown to be higher by 20% or above at the maximum.

• Journal of Broadcast Engineering
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• v.26 no.4
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• pp.453-462
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• 2021

A lot of license plate data is required for car number recognition. License plate data needs to be balanced from past license plates to the latest license plates. However, it is difficult to obtain data from the actual past license plate to the latest ones. In order to solve this problem, a license plate recognition study through deep learning is being conducted by creating a synthetic license plates. Since the synthetic data have differences from real data, and various data augmentation techniques are used to solve these problems. Existing data augmentation simply used methods such as brightness, rotation, affine transformation, blur, and noise. In this paper, we apply a style transformation method that transforms synthetic data into real-world data styles with data augmentation methods. In addition, real license plate data are noisy when it is captured from a distance and under the dark environment. If we simply recognize characters with input data, chances of misrecognition are high. To improve character recognition, in this paper, we applied the DeblurGANv2 method as a quality improvement method for character recognition, increasing the accuracy of license plate recognition. The method of deep learning for license plate detection and license plate number recognition used YOLO-V5. To determine the performance of the synthetic license plate data, we construct a test set by collecting our own secured license plates. License plate detection without style conversion recorded 0.614 mAP. As a result of applying the style transformation, we confirm that the license plate detection performance was improved by recording 0.679mAP. In addition, the successul detection rate without image enhancement was 0.872, and the detection rate was 0.915 after image enhancement, confirming that the performance improved.

• Journal of Auto-vehicle Safety Association
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• v.8 no.4
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• pp.6-11
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• 2016

The objective of this study is to present the inspection standards of motorcycle lamps affecting motorcycle traffic accident in night time. The inspection standards of motorcycle lamps recommended by CITA International Motor Vehicle Inspection Committee are surveyed. Also, the domestic safety standards of motorcycle and inspection standards of passenger car are considered. The inspection standard and method with principal reasons of rejections of head-lamp, number plate lamp, front-rear position lights, stop lamp and direction indicators of motorcycles are suggested.