• Proceedings of the KIEE Conference
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• 2003.11c
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• pp.528-531
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• 2003

Recognition of licence plate becomes a key issue to many traffic related application such as road traffic monitoring or parking lots access control. In this paper, the brightness, YIQ and HSI methods were used to locate a license. After the characters in license plate were extracted, template matching method was applied for character recognitions. 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 99%, and 96%, respectively

• 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

• Journal of the Korean Society for Library and Information Science
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• v.44 no.2
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• pp.263-283
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• 2010

Free Use License is an effective means of allowing many people to freely use works in the public domain. It can also prevent copyright infringement problems. This article analyzes the current service and domestic and foreign technology as it applies to free use license. It then proposes a plan which incorporates diverse requirements including technical aspects. Strategies are formulated from the technical, service and the resources connection perspectives for applying license in addition to searching and using licensed works. This article suggests a three-stage utilization plan to encourage the use of free use license. First, a connection plan between digital archiving and free use license, is developed. Then, a connection plan between UCI identifier and free use license is developed, and finally, the plan for the use of public resources is presented.

• The KIPS Transactions:PartC
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• v.11C no.6 s.95
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• pp.739-746
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• 2004

License mechanisms are the key elements in almost all DRM(digital rights management) systems. The license mechanisms are designed for the clear identification and enforcement of contents, principals, and usage rules in DRM systems. But current license mechanisms are lacking in the flexibility for the secure and efficient sharing of the contents among the members of a group such as a family or a part of an enterprise. This paper suggests a new license mechanism for efficient and secure sharing of contents in DRM systems among the members of a group. We named it member/group license mechanism. The mechanism extends the current license mechanisms by introducing new concepts such as group licenses, member licenses, and derivation relationships between licenses.

• Korean Journal of Clinical Pharmacy
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• v.23 no.1
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• pp.71-76
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• 2013

Background (Purpose): The objective of this study was to investigate regulations on pharmacist and other healthcare professional license examination in Korea. Specific aim was focused on the implementation of new regulatory system governing pharmacist license examination particularly on naming of the subjects, method of the examination, and discrimination of pass or fail. Method: Laws and regulations of Korea on the examination system were retrieved from sources posted in Ministry of Government Legislation. Results: Two major regulatory differences were found between pharmacist and other healthcare professionals license examination systems. Firstly, the regulation on pharmacist license examination was ruled by the enforcement ordinance of parent law (Pharmacy Law) while it was ruled by enforcement regulation of parent law (Medical Law). Secondly, minimum grade requirement for pharmacist and other healthcare professionals was differently set up: 40% for each single subject in pharmacist and average of 40% for each group of several subjects in other healthcare professionals. Conclusion: Since pharmacist profession has drastically changed from drug-makers to drug-users during the recent decades, it is desirable to have the regulations on pharmacist license examination system amended in harmony with other laws and regulations of Korea and other major developed countries. Two-step examination for pharmacist license appears worthwhile to implement for balancing the two key functions of the pharmacist being drug-makers and drug-users.

• Journal of the Korean Society of Industry Convergence
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• v.24 no.5
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• pp.555-562
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• 2021

In this paper, we propose a sorting method for extracting accurate license plate information, which is currently used in Korea, after detecting objects using YOLO. We propose sorting methods for the five types of vehicle license plates managed by the Ministry of Land, Infrastructure and Transport by classifying the plates with the number of lines, Korean characters, and numbers. The results of experiments with 5 license plates show that the proposed algorithm identifies all license plate types and information by focusing on the object with high reliability score in the result label file presented by YOLO and deleting unnecessary object information. The proposed method will be applicable to all systems that recognize license plates.

• Journal of Information Technology Services
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• v.20 no.6
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• pp.97-105
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• 2021

Recently, with the development of IT technology, unmanned systems are being introduced in many industrial fields, and one of the most important factors for introducing unmanned systems in the automobile field is vehicle licence plate recognition(VLPR). The existing VLPR algorithms are configured to use image processing for a specific type of license plate to divide individual areas of a character within the plate to recognize each character. However, as the number of Korean vehicle license plates increases, the law is amended, there are old-fashioned license plates, new license plates, and different types of plates are used for each type of vehicle. Therefore, it is necessary to update the VLPR system every time, which incurs costs. In this paper, we use an object detection algorithm to detect character regardless of the format of the vehicle license plate, and apply a handwritten Hangul recognition(HHR) algorithm to enhance the recognition accuracy of a single Hangul character, which is called a Hangul unit. Since Hangul unit is recognized by combining initial consonant, medial vowel and final consonant, so it is possible to use other Hangul units in addition to the 40 Hangul units used for the Korean vehicle license plate.

• International Journal of Computer Science & Network Security
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• v.22 no.11
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• pp.121-126
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• 2022

The number of vehicles has increased exponentially over the past 20 years due to technological advancements. It is becoming almost impossible to manually control and manage the traffic in a city like Karachi. Without license plate recognition, traffic management is impossible. The Framework for License Plate Detection & Recognition to overcome these issues is proposed. License Plate Detection & Recognition is primarily performed in two steps. The first step is to accurately detect the license plate in the given image, and the second step is to successfully read and recognize each character of that license plate. Some of the most common algorithms used in the past are based on colour, texture, edge-detection and template matching. Nowadays, many researchers are proposing methods based on deep learning. This research proposes a framework for License Plate Detection & Recognition using a custom YOLOv5 Object Detector, image segmentation techniques, and Tesseract's optical character recognition OCR. The accuracy of this framework is 0.89.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.10
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• pp.3490-3507
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• 2014

License plate detection (LPD) is one of the most important aspects of an automatic license plate recognition system. Although there have been some successful license plate recognition (LPR) methods in past decades, it is still a challenging problem because of the diversity of plate formats and outdoor illumination conditions in image acquisition. Because the accurate detection of license plates under different conditions directly affects overall recognition system accuracy, different methods have been developed for LPD systems. In this paper, we propose a license plate detection method that is rapid and robust against variation, especially variations in illumination conditions. Taking the aspects of accuracy and speed into consideration, the proposed system consists of two stages. For each stage, Haar-like features are used to compute and select features from license plate images and a cascade classifier based on the concatenation of classifiers where each classifier is trained by an AdaBoost algorithm is used to classify parts of an image within a search window as either license plate or non-license plate. And it is followed by connected component analysis (CCA) for eliminating false positives. The two stages use different image preprocessing blocks: image preprocessing without adaptive thresholding for the first stage and image preprocessing with adaptive thresholding for the second stage. The method is faster and more accurate than most existing methods used in LPD. Experimental results demonstrate that the LPD rate is 98.38% and the average computational time is 54.64 ms.

• The KIPS Transactions:PartD
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• v.9D no.6
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• pp.1113-1118
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• 2002

In recognition system of the car license plate, the most important is to extract the image of the license plate from a car image. In this paper, we use ACL (Adaptive Color Luminance) algorithm to extract the license plate image from a car image. The ACL algorithm that uses color and luminance information of a car image is used to extract the image of the license plate. In this paper, color, luminance and other related information of a car image are used to extract the image of the license plate from that of a car. In this reason, we call it the ACL algorithm. The ACL algorithm uses color, luminance information and other related information of a license plate. These informations are avaliable to exact the image of the license plate. The rate of extracting the image of the license plate from a car is 97%. The experimental result of the ACL algorithm for the character region is 92%.