• Proceedings of the Korean Society for Language and Information Conference
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• 1995.02a
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• pp.127-132
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• 1995

• Journal of the Korean Graphic Arts Communication Society
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• v.6 no.1
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• pp.41-57
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• 1988

Recently, it Is required to develop OCR(Optical Character Reader) along with the progress of the information processing system for Hangeul. Characters have to be recognized clearly so that OCR can be applied, Structure analysis method and lump method are used for the recognition of characters, and OCR is now available for the recognition of printed characters and handwritten alphanumeric characters having simple structure by them However, It is known that there should be much more study on the development of handwritten Hangout's OCR. This paper proposed a new method for the handwritten Hangout character recognition. The units of Initial consonant of Hangout are separated and then recognized from the utilization of the position- Information of Hangeul's units from the normalized patterns using the regression line theory. It is carried out for the extraction of the block which exists in the virtual Initial consonant region from the normalized input patterns and the calculation on maximum value (${\beta}$) of likelihood after comparing the features of separated subpattern with the initial consonant dictionary.

• Journal of the Semiconductor & Display Technology
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• v.16 no.3
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• pp.111-115
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• 2017

Terahertz waves are superior to conventional X-ray or Magnetic Resonance Tomography(MRI), and the amount of information that can be transmitted is as large as thousands of times that conventional X-ray or MRI. In addition, Terahertz waves have great performance in analyzing an object which have some layered structure. By using this advantage, we can extract the letters of a page by analyzing information such as absorption amount and reflection amount by irradiating a closed book with pulses of various frequencies within gap of a terahertz wave. However, in the image of each page using the Terahertz wave might be obtained various kinds of noise and the different character occlusion region. So, to extract letters from the terahertz image, we must take the noise and occlusion region away. We have been working to enhancement the image quality in various ways, and keep on studying de-noising processing for enhancement about the image quality and high resolution. Finally, we also keep on studying about OCR(Optical Character Recognition) technology, which based on pattern matching technique, to read letters.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.5
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• pp.162-167
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• 1994

The binary image normalization method in image processing can be used in several fields, Especially, its high speed processing method and its hardware implmentation is more useful, A normalization process of each character in character recognition requires a lot of processing time. Therefore, the research was done as a part of high speed process of OCR (optical character reader) implementation as a pipeline structure with host computer in hardware to give temporal parallism. For normalization process, general purpose CPU,MC68000, was used to implement it. As a result of experiment, the normalization speed of the hardware is sufficient to implement high speed OCR which the recognition speed is over 140 characters per second.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.18 no.9
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• pp.1358-1367
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• 1993

In this paper, OMR system based on image processing is developed which improve the performance of conventional OMR system based on line-scan method. Based on this OMR system, real-time OCR system which recognizes alphanumerics is also developed. We propose the OMCR system which recognize the mark and numerals at the same time. Besides, we improve the input system using constrained 7-segment type handwritten numeral instead of mark to solve the problem caused by miswriting the mark. In summary, we verified the reai-time recognition performance of developed OMCR system using application form for admission, answer sheet for college entrance examination and receipt sheet.

• 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.

• The Transactions of the Korea Information Processing Society
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• v.6 no.7
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• pp.1713-1723
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• 1999

Optical character recognition(OCR) might be the most plausible method in building database out of printed matters. This paper describes the points to be considered when one selects an OCR system in order to build database. Based on the considerations, we evaluated four commercial OCR systems, and chose one which shows the best recognition rate to build OCT-text database. The subject text, the KT-test collection, is a set of abstracts from proceedings of different printing quality, fonts, and formats. KT-test collection is also provided with typed text database. Recognition rate was calculated by comparing the recognition result with the typed text. No preprocessing such as learning and slant correction was applied to the recognition process in order to simulate a practical environment. The result shows 90.5% of character recognition rate over 970 abstracts. This recognition rate is still insufficient for practical use. The errors in OCR texts are different from those of manually typed texts. In this paper, we classify the errors in OCR texts for the further research.

• The Transactions of the Korea Information Processing Society
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• v.3 no.5
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• pp.1273-1280
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• 1996

In order perform high accuracy recognition of text recognition systems, the recognized text must be processed through a post-processing stage using contextual information. We present a system that combines multiple knowledge sources to post-process the output of an optical character recognition(OCR) system. The multiple knowledge sources include characteristics of word, wrongly recognized types of Hangul characters, and Hangul word learning In this paper, the wrongly recognized characters which are made by OCR systems are collected and analyzed. We imput a Korean dictionary with approximately 15 0,000 words, and Korean language texts of Korean elementary/middle/high school. We found that only 10.7% words in Korean language texts of Korean elementary/middle /high school were used in a Korean dictionary. And we classified error types of Korean character recognition with OCR systems. For Hangul word learning, we utilized indexes of texts. With these multiple knowledge sources, we could predict a proper word in large candidate words.

• Proceedings of the Korean Information Science Society Conference
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• 2001.04b
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• pp.544-546
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• 2001

이 논문은 OCR(Optical Character Reader)로 인식된 한글 문서에서의 오인식 경향을 분석하고, 이를 이용한 한글 단어 검색 방법을 제안한다. OCR로 인식된 많은 야의 한글 문서를 기반으로 자모별 인식 빈도수를 계산하고 이를 바탕으로 초성, 중성, 중성별 인식 혼동 행렬(confusion matrix)을 구성하였다. 또한 인식 정보를 적절히 이용하기 Bayes 정리를 이용하였다. 질의어에 대한 오인식 단어의 검색 방법을 제시하고 혼동 행렬과 이 검색 방법을 바탕으로 OCR 기반 단어 검색 시스템을 구축하였다.

• Journal of Korea Society of Industrial Information Systems
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• v.12 no.1
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• pp.95-100
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• 2007

In the steel & iron processing line, some characters are marked for the material management in the surface of material. This paper describes about the developed results of vision system for the recognition of material management characters, which was included in the slab image. Our vision system for the character recognition includes that CCD camera system which acquire slab image, optical transmission system which transmit captured image to the long distance, input and output system for the interface with existing system and monitoring system for the checking of recognition results. We have installed our vision system at the continuous casting line and tested. Also, we have performed inspection of durability, reliability and recognition rate. Through the testing, we have confirmed that our system have high recognition rate, 97.4%.