• Journal of Korea Society of Digital Industry and Information Management
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• v.16 no.4
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• pp.19-28
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• 2020

Vehicle license plate recognition system is not generalized in Malaysia due to the loose character layout rule and the varying number of characters as well as the mixed capital English characters and italic English words. Because the italic English word is hard to segmentation, a separate method is required to recognize in Malaysian license plate. In this paper, we propose a mixed character level and word level English license plate recognition algorithm using deep learning neural networks. The difference of Gaussian method is used to segment character and word by generating a black and white image with emphasized character strokes and separated touching characters. The proposed deep learning neural networks are implemented on the LPR system at the gate of a building in Kuala-Lumpur for the collection of database and the evaluation of algorithm performance. The evaluation results show that the proposed Malaysian English LPR can be used in commercial market with 98.01% accuracy.

• Journal of Korea Multimedia Society
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• v.25 no.4
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• pp.568-574
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• 2022

In this paper, direction normalization and CNN deep learning are used to develop a more reliable license plate recognition system. The existing license plate recognition system consists of three main modules: license plate detection module, character segmentation module, and character recognition module. The proposed system minimizes recognition error by adding a direction normalization module when a detected license plate is inclined. Experimental results show the superiority of the proposed method in comparison to the previous system.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.11a
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• pp.281-283
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• 2022

화물 선박의 전복사고가 매해 발생하고 있음에도 화물을 측정하지 않고 서류에 의존하는 방식으로 화물을 선적하고 있습니다. 우리는 사고의 원인을 사전에 차단할 수 있는 자동 계측 시스템을 연구하였습니다. 본 논문의 시스템은 LiDAR 센서를 이용하여 비규격 화물이 멈추지 않고 자동 계측되어 인력과 시간의 소요를 줄이고 산출된 체적과 3D 모델을 제공합니다. 게다가 화물 차량에 실린 화물을 내리지 않고도 화물의 체적을 산출할 수 있어 항만의 효율성을 향상할 수 있을 것으로 기대합니다.

• Journal of Korea Society of Digital Industry and Information Management
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• v.19 no.4
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• pp.127-136
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• 2023

Many research results on the traffic enforcement of illegal driving of twowheeled motor vehicles using license plate recognition are introduced. Deep learning convolutional neural networks can be used for character and word recognition of license plates because of better generalization capability compared to traditional Backpropagation neural networks. In the plates of twowheeled motor vehicles, the interdependent government and city words are included. If we implement the mutually independent word recognizers using error correction rules for two word recognition results, efficient license plate recognition results can be derived. The CPU based convolutional neural network without library under real time processing has an advantage of low cost real application compared to GPU based convolutional neural network with library. In this paper twowheeled motor vehicle license plate recognition algorithm is introduced using CPU based deep-learning convolutional neural network. The experimental results show that the proposed plate recognizer has 96.2% success rate for outdoor twowheeled motor vehicle images in real time.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.2
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• pp.95-101
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• 2014

This paper explains effective tracking method for a vehicle cutting in a line on the road automatically. The method employs KLT based on optical flow using play-back image sequence. Main contribution of this paper is play-back image sequence that is in order image frames for rewind direction from a reference point in time. The moment when recognizing camera can read a license plate very well can usually be the reference point in time. The biggest images of object traced can usually be obtained at this moment also. When optic flow is applied, the bigger image of the object traced can be obtained, the more feature points can be obtained. More many feature points bring good result of tracking object. After the recognizing cameras read a license plate on the vehicle suspected of cut-in-line violation, and then the system extracts the play-back image sequence from the tracking cameras for watching wide range. This paper compares using play-back image sequence as normal method for tracking to using play-forward image sequence as suggested method on the results of the experiment and also shows the suggested algorithm has a good performance that can be applied to the unmanned system for watching cut-in-line violation.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.2
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• pp.93-104
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• 2023

Currently, the permanent road traffic volume surveys under Road Act are conducted using a intrusive Automatic Vehicle Classification (AVC) equipments to classify 12 categories of vehicles. However, intrusive AVC equipment inevitably have friction with vehicles, and physical damage to sensors due to cracks in roads, plastic deformation, and road construction decreases the operation rate. As a result, accuracy and reliability in actual operation are deteriorated, and maintenance costs are also increasing. With the recent development of ITS technology, research to replace the intrusive AVC equipment is being conducted. However multiple equipments or self-built DB operations were required to classify 12 categories of vehicles. Therefore, this study attempted to prepare a method for classifying 12 categories of vehicles using vehicle specification information of the Vehicle Management Information System(VMIS), which is collected and managed in accordance with Motor Vehicle Management Act. In the future, it is expected to be used to upgrade and diversify road traffic statistics using vehicle specifications such as the introduction of a road traffic survey system using Automatic Number Plate Recognition(ANPR) and classification of eco-friendly vehicles.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.465-468
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• 2022

The incidence of traffic accidents is increasing every year, and Korea is among the top OECD countries. In order to improve this, various road traffic laws are being implemented, and various traffic control methods using equipment such as unmanned speed cameras and traffic control cameras are being applied. However, as drivers avoid crackdowns by detecting the location of traffic control cameras in advance through navigation, a mobile crackdown system that can be cracked down is needed, and research is needed to increase the recognition rate of vehicle license plates on the side of the road for accurate crackdown. This paper proposes a method to improve the vehicle number recognition rate on the road side by applying a gradient correction algorithm using image processing. In addition, custom data learning was conducted using a CNN-based YOLO algorithm to improve character recognition accuracy. It is expected that the algorithm can be used for mobile traffic control cameras without restrictions on the installation location.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.5
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• pp.877-884
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• 2023

In this study, when another vehicle is parked in a designated space where a personal vehicle can park and a defined personal use time, an ultrasonic object recognition sensor is used to determine vehicle entry, and a camera sensor recognizes a license plate. If the vehicle is not recognized by the individual vehicle owner, the "private parking lot operation block" of the application server receives the individual phone number based on the National Police Agency's Vehicle Number Information Inquiry Open API. Afterwards, when parking is processed, the non-right holder receives the approval of the parking right holder, parks for the recognized time, and deposits the parking fee into the public account of the city hall. Through this study, it was possible to find an operation processing method that can most effectively manage parking in the city center in a private parking space recognized by the city hall.

• KAPE Magazine
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• no.9 s.145
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• pp.4-5
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• 2008

농림수산식품부는 수입 축산물의 유통흐름을 투명하게 파악하고 위해 축산물 회수 기반을 보다 확고하게 하기 위하여 식육가공.판매업체에 대해 판매처, 수입신고필증번호 등을 기재한 거래명세서 발급을 의무화하는 것을 주요내용으로 하는 "축산물가공처리법 시행규칙"을 지난 8월 14일 입법예고 하였다. 이에 둔갑판매 방지와 위해 축산물 회수 조치 기틀이 마련될 것으로 기대된다.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.11a
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• pp.77-80
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• 2000

본 논문에서는 새로운 학습알고리즘의 비선형 주요성분분석 신경망을 이용한 데이터의 효율적인 특징추출에 대하여 제안하였다. 제안된 학습알고리즘에서는 모멘트와 동적터널링을 조합하여 이용함으로써 최적해로의 수렴에 따른 발진을 억제하고 빠른 수렴속도로 전역최적해에 수렴되도록 학습시킬 수 있다. 제안된 학습알고리즘을 이용하여 128$\times$128 픽셀의 얼굴영상과 256$\times$128 픽셀의 자동차번호판 영상을 대상으로 시뮬레이션 한 결과, 기울기하강의 학습알고리즘을 이용한 기존 비선형 주요성분분석 신경망보다 우수한 수렴성능과 특징추출성능이 있음을 확인 할 수 있었다.