• Proceedings of the Korean Society of Computer Information Conference
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• 2023.01a
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• pp.407-408
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• 2023

In this paper, we intend to develop a multimodal algorithm that secures recognition performance of over 95% in daytime illumination environments and secures recognition performance of over 90% in bad weather (rainfall and snow) and night illumination environments.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.5
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• pp.1052-1061
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• 2003

In this paper, we propose the car plate recognition using SOM algorithm and describe the parking control system using the proposed car plate recognition. The recognition of car plate was investigated by means of the SOM algorithm. The morphological information of horizontal and vertical edges was used to extract a plate area from a car image. In addition, the 4-direction contour tracking algorithm was applied to extract the specific area, which includes characters from an extracted plate area. The extracted characteristic area was recognized by using the SOM algorithm. In this paper, 50 car images were tested. The extraction rate obtained by the proposed extraction method showed better results than that from the color information of RGB and HSI, respectively. And the car plate recognition using SOM algorithm was very efficient. We develop the parking control system using the proposed car plate recognition that shows performance improvement by the experimental results.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.648-651
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• 2003

In this paper, we propose the recognition system of a license plate using SOM algorithm. The recognition of license plate was investigated by means of the SOM algorithm. The morphological information of horizontal and vertical edges was used to extract a plate region from a car image. In addition, the 4-direction contour tracking algorithm was applied to extract the specific area, which includes characters from an extracted plate area. Therefore, we proposed how to extract license plate region using morphological information and how to recognize the character string using SOM algorithm. In this paper, 50 car images were tested. The extraction rate obtained by the proposed extraction method showed better results than that from the color information of RGB and HSI, respectively. And the license plate recognition using SOM algorithm was very efficient.

• Journal of Korean Institute of Industrial Engineers
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• v.22 no.3
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• pp.441-458
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• 1996

Many researches on feature recognition have been performed up to now, but the general solution for recognizing arbitrary features has not been developed. The most popular research area in feature recognition is automatic extraction of 2.5 dimensional features, because they are frequently used in manufacturing field. In this paper, a faster and more convenient 2.5 dimensional feature recognition algorithm is proposed using a new strategy which is quite different from the existing ones. The proposed algorithm takes process planning into consideration. The algorithm is implemented in C++. By applying the algorithm to practical complicate examples, we verify that the algorithm is working very well.

• Proceedings of the KIEE Conference
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• 1995.07b
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• pp.1002-1005
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• 1995

This paper presents an enhanced preprocessing and recognition algorithm for automatic vehicle license plate recognition system. The algorithm first applies horizontal gradient filter followed by thresholding and mathematical morphology operation for preprocessing. The final stage of the preprocessing is the application of connected component analysis in order to estimate the license plate region. For the recognition of the serial numbers of the plates, we developed a very effective algorithm. We call this zerocrossing count algorithm. This paper presents a detail of this algorithm and compare the performance with a template matching algorithm which utilizes correlation coefficient.

• International journal of advanced smart convergence
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• v.11 no.4
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• pp.47-56
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• 2022

Recently bank card number recognition plays an important role in improving payment efficiency. In this paper we propose a new bank-card number identification algorithm. The proposed algorithm consists of three modules which include edge detection, candidate region generation, and recognition. The module of 'edge detection' is used to obtain the possible digital region. The module of 'candidate region generation' has the role to expand the length of the digital region to obtain the candidate card number regions, i.e. to obtain the final bank card number location. And the module of 'recognition' has Convolutional deep learning Neural Network (CNN) to identify the final bank card numbers. Experimental results show that the identification rate of the proposed algorithm is 95% for the card numbers, which shows 20% better than that of conventional algorithm or method.

• The Transactions of the Korean Institute of Electrical Engineers C
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• v.53 no.10
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• pp.515-522
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• 2004

In this study, we tried to investigate that the advantages of SOM(Self Organizing Map) algorithm such as data accumulation ability and the degradation trend trace ability would be adaptable to the analysis of partial discharge pattern recognition. For the purpose, we analyzed partial discharge data obtained from the typical artificial defects in GIS and XLPE power cable system through SOM algorithm. As a result, partial discharge pattern recognition could be well carried out with an acceptable error by use of Kohonen map in SOM algorithm. Also, it was clarified that the additional data could be accumulated during the operation of the algorithm. Especially, we found out that the data accumulation ability of Kohonen map could make it possible to suggest new patterns, which is impossible through the conventional BP(Back Propagation) algorithm. In addition, it is confirmed that the degradation trend could be easily traced in accordance with the degradation process. Therefore, it is expected to improve on-site applicability and to trace real-time degradation trends using SOM algorithm in the partial discharge pattern recognition

• 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.

• MALSORI
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• no.50
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• pp.123-137
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• 2004

In this paper, we consider the implementation of connected digit recognition system using tree structured lexicon model. To implement efficiently the fixed or variable length digit recognition system, finite state network (FSN) is required. We merge the word network algorithm that implements the FSN with lexical tree search algorithm that is used for general speech recognition system for fast search and large vocabulary systems. To find the efficient modeling of digit recognition system, we investigate some performance changes when the lexical tree search is applied.

• Journal of Intelligence and Information Systems
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• v.9 no.2
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• pp.1-18
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• 2003

The automatic recognition of transport containers using image processing is very hard because of the irregular size and position of identifiers, diverse colors of background and identifiers, and the impaired shapes of identifiers caused by container damages and the bent surface of container, etc. We proposed and evaluated the novel recognition algorithm of container identifiers that overcomes effectively the hardness and recognizes identifiers from container images captured in the various environments. The proposed algorithm, first, extracts the area including only all identifiers from container images by using CANNY masking and bi-directional histogram method. The extracted identifier area is binarized by the fuzzy binarization method newly proposed in this paper and by applying contour tracking method to the binarized area, container identifiers which are targets of recognition are extracted. We proposed and applied the ART2-based RBF network for recognition of container identifiers. The results of experiment for performance evaluation on the real container images showed that the proposed algorithm has more improved performance in the extraction and recognition of container identifiers than the previous algorithms.