• 한국멀티미디어학회논문지
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• 제23권11호
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• pp.1361-1371
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• 2020

Fonts have developed as a visual element, and their influence has rapidly increased around the world. Research on font automation is actively being conducted mainly in English because Hangul is a combination character and the structure is complicated. In the previous study to solve this problem, the stroke element of the character was automatically extracted by applying the object detection by component. However, the previous research was only for similarity, so it was tested on various print style fonts, but it has not been tested on other characters. In order to extract the stroke elements of all characters and fonts, we performed a performance analysis experiment according to the expansion character in the Hangul stroke element extraction training. The results were all high overall. In particular, in the font expansion type, the extraction success rate was high regardless of having done the training or not. In the character expansion type, the extraction success rate of trained characters was slightly higher than that of untrained characters. In conclusion, for the perfect Hangul stroke element extraction model, we will introduce Semi-Supervised Learning to increase the number of data and strengthen it.

• Journal of the Korean Data and Information Science Society
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• 제14권3호
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• pp.525-533
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• 2003

In this paper we introduce some existing preprocessing algorithm for character recognition and consider feature extraction method for the recognition of low resolution document. Image recognition of low resolution document including fax images can be frequently misclassified due to the blurring effect, slope effect, noise and so on. In order to overcome these difficulties in the character recognition we considered a mesh feature extraction and contour direction code feature. System for automatic character recognition were suggested.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.297-297
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• 2000

This paper proposed character recognition method by using DB Matching and Artificial Neural Network at the Gerber files. Gerber files are file for make PCB. But we also use the file to a program of extraction PCB position data. If the Gerber file recognized a character, the extraction PCB position data will be faster and also when the recognition rate is high, it can be possible to automatic extraction. We apply to the construction PCB Gerber file program and Simulation results are presented to verify the usefulness of the method.

• 한국정보처리학회논문지
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• 제1권3호
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• pp.311-318
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• 1994

시각신경계의 특정추출 기구인 수용영역 즉, RF(Receptive Field)모델을 이용하여 한자의 획의 분리 및 추출에 관한 방법을 제안한다. 한자의 복잡한 정보에 대한 분리 추출과 데이터베이스화 등은 더욱 명백한 처리과정을 필요로하고 있다. 본 기법의 특 징은 망막과 대뇌 시각영역의 특징추출 기구인 수용영역을 모델링 하였고 신경세포 입력 방식에 따라 국소적인 처리에서 얻어진 정보를 대국적인 처리로 통합 추출하는 것으로서 그 기능성과 유효성을 확인할 수 있었다.

• 한국통신학회:학술대회논문집
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• 한국통신학회 1991년도 추계종합학술발표회논문집
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• pp.77-80
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• 1991

This paper proposes a new feature extraction method which is effectively used in character recognition, and validate the effectiveness through various computational methods for similiarity degree. To get feature vectors used in this method, Hough transform is applied to character image, which is used for edge extraction in image processing. By that transformation technique, strokes could be extracted and feature vectors constructed suitably. The characteristic of this method is solving the difficulties in stroke extraction through transform space analysis, which is induced by noise and blurring, and representing high recognition rate 99.3% within 10 candidates in relative low dimension.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1994년도 Proceedings of the Korea Automatic Control Conference, 9th (KACC) ; Taejeon, Korea; 17-20 Oct. 1994
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• pp.302-306
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• 1994

This paper describes how to recognize hand written Hangeul character using the stroke order of the elementary segment. The recognition system is constructed of parts : character input part, segment disassembling part, character element extraction part and character recognition part. The character input part reads the character and performs thinning algorithm. In the segment disassembling part, the input character is disassembled into elementary segments using the direction codes and the feature parameters. In the character element extraction part, we extract the character element using the stroke order and the knowledge rule. Finally, we able to recognize the hand written Hangeul characters by assembling the character elements, in the character recognition part.

• 대한전자공학회논문지
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• 제25권9호
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• pp.1091-1101
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• 1988

In this paper, a method to segment each character and extract figure from Korean documents is proposed. At first, each character string is extracted by means of iterative horizontal propagation, shrink algorithm and run-length algorithm. Individual character region is extracted by iterative horizontal and vertical manipulation. Next, characters of right pitch are searched. Each character is segmented by the position information. Overlapped character is segmented on the ground of the width of already extracted character. The rest are extracted as special characters of half pitch. Using 9 data input in the form of 840 X 600 from Korean monthly magazine, experiment was simulated. Extraction rate of character is 100%, and that of individual character is 98%. Judging from these results, efficiency on extracting character region and segmenting individual character is proved.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 1999년도 추계종합학술대회 논문집
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• pp.1081-1084
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• 1999

This paper proposes a method of extracting automobile license plate information using color image processing and separation of character regions. The hue and saturation of color information is need for license plate extraction and the specified standard location ratio is need for character region separation. Simulation results show that the proposed algorithm can detect license plates and separate character regions successfully.

• 한국산업정보학회논문지
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• 제8권2호
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• pp.14-20
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• 2003

본 논문에서는 카메라로 획득한 문서영상에 대해 조명의 영향에 관계없이 고속으로 문자영역을 추출하는 알고리즘을 제안하였다. 카메라 문서는 스캐너 문서와는 달리 주변 환경이나 조명의 영향으로 인하여 문자영역을 추출하는 것이 매우 어렵다. 먼저 영상 사전처리 단계에서 컬러영상을 명도영상으로 변환한 후 조명의 영향에 무관하게 배경 그림으로부터 문자 영역을 정확히 추출하기 위해서 명도레벨 정규화를 사용하였다. 또한 배경 그림 및 잡음은 제거하고 문자 획의 손실 없이 문자 영역을 추출하기 위하여 국소-적응적-이진화-방법(local adaptive binarization method)을 새롭게 개발하여 문서영상을 이진화시켰다. 문자영역 추출 단계에서는 수평 및 수직 투영과 연결요소 정보에 의해 문자열, 단어 및 개별 문자 영역을 단계적으로 추출하였다. 제안된 방법의 타당성을 검증하기 위하여 ETRI에서 구축한 한글/영어/숫자/특수기호가 혼합된 현장 문서영상 DB를 가지고 실험해 보았다.

• 한국콘텐츠학회논문지
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• 제2권1호
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• pp.59-67
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• 2002

본 논문에서는 입력의 자동화 및 교육을 위한 문자 익히기 시스템을 위하여 자소의 특징 추출과 유사도 함수를 정의하여 한글에 대한 미적평가를 수행하였다. 이를 위해 한글 문자의 자소에 대한 특징 추출 및 유사도 함수를 정의 한 후 표준 문자와 입력 문자가 얼마나 유사한지를 평가하는 방법을 제안하였다. 표준 문자와 입력 문자의 획에 대한 특징 추출 및 유사도 함수를 정의하였으며, 다양한 입력 문자 패턴에 대해 표준 문자 패턴과 얼마나 유사한지를 실험한 결과 예상한 값과 유사하게 일치하는 실험 결과를 얻을 수 있었다. 또한 일반 사람들의 미적 평가 결과와 제안한 방법의 실험 결과가 유사하게 일치한다는 결과도 얻을 수 있었다.