• Journal of the Korean Institute of Telematics and Electronics
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• v.26 no.12
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• pp.1956-1964
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• 1989

In this paper, a new method of Hangul recognition is proposed to solve the problems of misrecognition owing to the contacts of FCEs (Fundamental Character Elements) in a Hangul pattern. Structures of FCFs are represented with PAG(Programmed Array Grammar) to recognize an input pattern on 2-D. array of pels., and the unnecessary deformation of the conventional approach can be eliminated by using PEACE parsing which extracts primitives and computes attributes in the course of analyzing the structure of an input pattern. Also, primitive transformation at contacts can afford to confirm all the possible structures of an input pattern and solve the problem of misrecognition owing to the contacts of FCEs. The recognition rate of proposed method for printed Hangul characters shows 96.2% for 1978 Gothic-letters and 92.0% for 1920 Myng-style-letters, respectively.

• Journal of information and communication convergence engineering
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• v.1 no.1
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• pp.53-57
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• 2003

Chaos theory is a study researching the irregular, unpredictable behavior of deterministic and non-linear dynamical system. The interpretation using Chaos makes us evaluate characteristic existing in status space of system by tine series, so that the extraction of Chaos characteristic understanding and those characteristics enables us to do high precision interpretation. Therefore, This paper propose the new method which is adopted in extracting character features and recognizing characters using the Chaos Theory. Firstly, it gets features of mesh feature, projection feature and cross distance feature from input character images. And their feature is converted into time series data. Then using the modified Henon system suggested in this paper, it gets last features of character image after calculating Box-counting dimension, Natural Measure, information bit and information dimension which are meant fractal dimension. Finally, character recognition is performed by statistically finding out the each information bit showing the minimum difference against the normalized pattern database. An experimental result shows 99% character classification rates for 2,350 Korean characters (Hangul) using proposed method in this paper.

• The Journal of the Korea Contents Association
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• v.10 no.1
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• pp.10-18
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• 2010

Due to a large number of classes in Hangul character recognition, it is usual to use the six-type preclassification stage. After the preclassification, the first consonent, vowel, and last consonent can be classified separately. Though each of three components has a few of classes, classification errors occurs often due to shape similarity such as 'ㅔ' and 'ㅖ'. So this paper proposes a hierarchical recognition method which adopts multi-stage tree structures for each of 6-types. In addition, to reduce the interference among three components, the method uses the recognition results of first consonents and vowel as features of vowel classifier. The recognition accuracy for the test set of PHD08 database was 98.96%.

• Journal of the Korea Society of Computer and Information
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• v.21 no.9
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• pp.27-36
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• 2016

Recognition of grapheme is a very important process in the recognition within 'Hangul(Korean written language)' letters using phoneme recognition. It is because the success or failure in the recognition of phoneme greatly affects the recognition of letters. For this reason, it is reported that separation of phonemes is the biggest difficulty in the phoneme recognition study. The current study separates and suggests the new phonemes that used the connective elements that are helpful for dividing phonemes, recommends the features for recognition of such suggested phonemes, databases this, and carried out a set of experiments of recognizing phonemes using the suggested features. The current study used 350 letters in the experiment of phoneme separation and recognition. In this particular kind of letters, there were 1,125 phonemes suggested. In the phoneme separation experiment, the phonemes were divided in the rate of 100%, and the phoneme recognition experiment showed the recognition rate of 98% in recognizing only 14 phonemes into different ones.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.9
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• pp.166-177
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• 1994

In this paper, an implemenation of on-line continuous recognizer for cursive Hangul handwriting is explained. For the Hangul recognition system, we propose a high speed string matching. The editing process in our proposed string matching is accomplished by single editing path. And the matching results are stored in a heap structure and we decide the user comfortibility of unceasing writing during recognition owing to the high speed matching. In the experimental result, a recongition rate of 86.36% at 1.75 second/character over 21,076 characters collected from 50 persons are abtained. And it is shown that the proposed recognition system is operated properly for the on-line recognition for cursive handwring between graphemes.

• Journal of the Korea Society of Computer and Information
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• v.15 no.10
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• pp.49-57
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• 2010

In this thesis, We studied on hand-written character recognition, that characters entered into a digital input device and remove noise and separating character elements using preprocessing. And processed character images has done thinning and 3-level wavelet transform for making normalized image and reducing image data. The structural method among the numerical Hangul recognition methods are suitable for recognition of printed or hand-written characters because it is usefull method deal with distortion. so that method are applied to separating elements and analysing texture. The results show that recognition by analysing texture is easily distinguished with respect to consonants. But hand-written characters are tend to decreasing successful recognition rate for the difficulty of extraction process of the starting point, of interconnection of each elements, of mis-recognition from vanishing at the thinning process, and complexity of character combinations. Some characters associated with the separation process is more complicated and sometime impossible to separating elements. However, analysis texture of the proposed character recognition with the exception of the complex handwritten is aware of the character.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.40 no.5
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• pp.266-279
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• 2003

In this paper, we propose machine printed character recognition methods which utilize the character type information and divide the character clusters. The characters are subdivided into a total of seven types, of which six types are for Hangul according to the grapheme combination fashions and one type for English characters, numerals, and symbols. According to the character type, we separate input character image into several recognition units and recognize them by using the direction angle feature. The recognition for each character type is completed by combining recognition units which are recognized by neural networks respectively For combining a total of seven character recognizers, we implemented seven methods such as switching method, integrating method, and their several variants. As experimental results, we obtained 98.2% recognition rate of simple switching method, 90.54% of integrating one, and between 97.35% and 98.65% of five variants.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.37 no.8
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• pp.579-587
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• 1988

Conventional methods of automatic recognition of Korean characters consist of the thinning processing, the segmentation of connected fundamental phonemes and the recognition of each fundamental character. These methods, however require the thinning processing which is complex and time consuming. Also several noise components make worse effects on the recognition of characters than in the case of no thinning. This paper describes the extraction method of the feature components of Korean fundamental characters of the Gothic Korean letter without the thinning. We regard line-components of the contour which describes the character's external boundary as the feature-components. The line-component includes the directional code, the length and the start point in the image. Each fundamental character is represented by the string of directional codes. Therefore the recognition process is only the string pattern matching. We use the Gothic-hangul in the experiment. The ecognition rate is 92%.

• The Transactions of the Korea Information Processing Society
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• v.4 no.8
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• pp.2017-2024
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• 1997

The main focus of this paper is the recognition of printed Hangul documents in terms of typeface, character size and character slope for IICS(Intelligent Image Communication System). The fixed-size blocks extracted from documents are analyzed in frequency domain for the typeface classification. The vertical pixel counts and projection profile of bounding box are used for the character size classification and the character slope classification, respectively. The MLP with variable hidden nodes and error back-propagation algorithm is used as typeface classifier, and Mahalanobis distance is used to classify the character size and slope. The experimental results demonstrated the usefulness of proposed system with the mean rate of 95.19% in typeface classification. 97.34% in character size classification, and 89.09% in character slope classification.

• 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.