• 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.

• Journal of the Korea Society of Computer and Information
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• v.26 no.9
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• pp.49-55
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• 2021

In this paper, an enhanced 2-stage vehicle license plate detection scheme using object segmentation is proposed to detect accurately the rotated license plates due to the inclined photographing angles in real-road situations. With the previous 3-stage vehicle license plate detection pipeline model, the detection accuracy is likely decreased as the license plates are declined. To resolve this problem, we propose an enhanced 2-stage model by replacing the frontal two processing stages which are for detecting vehicle area and vehicle license plate respectively in only rectangular shapes in the previous 3-stage model with one step to detect vehicle license plate in arbitrarily shapes using object segmentation. According to the comparison results in terms of the detection accuracy of the proposed 2-stage scheme and the previous 3-stage pipeline model against the rotated license plates, the accuracy of the proposed 2-stage scheme is improved by up to about 20% even though the detection process is simplified.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.12
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• pp.451-460
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• 2018

Open source software is used in various ways when developing new softwares all around the world. It requires rights and responsibilities as a form of an open source software license. Because the license is a contract between original software developers of the open source software and users, we must follow it and extremely cautious to avoid copyright infringement. In particular, we must verify license compatibility when we develop new software using the existing open source softwares. However, license violation issues always occur and lead to lawsuits so that they are having an adverse effect on the open source software ecosystem. Thus, in this paper, we propose a method, OSLC-Vid, to identify license violations whether compatibility issues exist between open source softwares. The proposed method is verified by the experiments to detect actual license violation cases.

• Journal of Korea Multimedia Society
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• v.8 no.11
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• pp.1496-1509
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• 2005

In this paper, an adaptive license plate recognition system which detects and recognizes license plate at real-time by using projected plane convolution and Decision Tree Classifier is proposed. And it was tested in circumstances which presence of complex background. Generally, in expressway tollgate or gateway of parking lots, it is very difficult to detect and segment license plate because of size, entry angle and noisy problem of vehicles due to CCD camera and road environment. In the proposed algorithm, we suggested to extract license plate candidate region after going through image acquisition process with inputted real-time image, and then to compensate license size as well as gradient of vehicle with change of vehicle entry position. The proposed algorithm can exactly detect license plate using accumulated edge, projected convolution and chain code labeling method. And it also segments letter of license plate using adaptive binary method. And then, it recognizes license plate letter by applying hybrid pattern vector method. Experimental results show that the proposed algorithm can recognize the front and rear direction license plate at real-time in the presence of complex background environments. Accordingly license plate detection rate displayed $98.8\%$ and $96.5\%$ successive rate respectively. And also, from the segmented letters, it shows $97.3\%$ and $96\%$ successive recognition rate respectively.

• Journal of the Korean Society for information Management
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• v.21 no.1
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• pp.1-22
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• 2004

Along with the increased use of e-journal since mid of 1990's, there has been a sharp increase of license contracting in the library. However the librarians who have no enough knowledge nor technology to handle the licensing are experiencing difficulties in the process. The study intended to help them understand the practical problems of license contracting between library and vendors, and proposed guidelines for developing model license for e-journal based on the licensing principles of IFLA and ALA.

• Proceedings of the IEEK Conference
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• 2003.07d
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• pp.1291-1294
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• 2003

This paper presents an approach to extract license plates from parking regulation images which is captured in various photographing direction and complex background. first, we search each row at regular intervals starting from the bottom of a license-plate image, and we set up a rough region for a certain zone in which the sign of intensity vector changes frequently enough and color of license plate is detected enough, assuming it as a candidate location of a license plate. And then, we extract an elaborate area of a license plate by horizontally and vertically projecting vertical edges. Here, tar types of the private and the public, are easily classified according to the color of extracted plates. To evaluate proposed method, we used 200 actual regulation images. As a result, the proposed method showed extraction rate of 96%, which is 9% higher than the previous method using only intensity vector.

• Proceedings of the Korea Contents Association Conference
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• 2003.11a
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• pp.218-222
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• 2003

A technology that recognize the car license plate have accomplished a lot of developments for latest several years. Key technology for correct recognition is correct abstraction of plate area. Existent studies have used horizontal/vertical edge, some geometrical characteristics of license plate, and the color information. But, in case of extracting a plate using above characteristics, correct extraction of a license plate inclined by sight which see license plate is difficult. Therefore, this paper is propose new method that correctly extract license plate using the color information and linear regression method.

• Journal of Korea Multimedia Society
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• v.18 no.10
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• pp.1172-1179
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• 2015

A wireless license plate region extracting module is proposed for LPR system controlling multiple gates. This module is cheaply implemented using Raspberry Pi which is open source and high performance. First, as the upper 1/3 of the captured image is discarded as it has no useful information on license plate. Using the OpenCV libraries the edge image is got by Canny algorithm after applying Gaussian filtering to gray image, and the labeling is conducted for 4 consecutive numbers in license plate. These numbers are located using various decision equations, and expanding the numbers region the final license plate region can be extracted. The result image is transferred to Server using wifi direct. Using the proposed module it becomes easy to set up and maintain the LPR system. The experimental results showed that the successful extracting rate was 98.4% using 500 car images with 640 × 480 resolution.

• Journal of the Korea Society of Computer and Information
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• v.21 no.3
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• pp.33-38
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• 2016

Research on the development of key technologies of social work protection and content mashup tools has been carried out as an R&D project granted by the Korea Copyright Commission from 2013. The research aims to provide efficiency of the production environment of the secondary work of the digital contents as well as a systematic solution to the regulation-related problems. The essential features of the distribution management system for cooperative works developed though this study are the decision of the selling prices reflecting various license fee factors and the transparent distribution of the license fees. This paper represents a model which can automatically calculate the amount of the license fee in each derivative stage, independently of the license fee policies on each of the subsidiary contents when N-th works are producted on the basis of a previously approved first work.

• Journal of the Optical Society of Korea
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• v.14 no.4
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• pp.368-375
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• 2010

Unlike document images, license plate images are mostly captured under uneven lighting conditions. In particular, a shadowed region has sharp intensity variation and sometimes that region has very high intensity by reflected light. This paper presents a new technique for thresholding license plate images. This approach consists of three parts. In the first part, it performs a rough thresholding and classifies the type of license plate to adjust some parameters optimally. Next, it identifies a shadow type and binarizes license plate images by adjusting the window size and location according to the shadow type. And finally, post-processing based on the cluster analysis is performed. Experimental results show that the proposed method outperformed five well-known methods.