• Cross-Cultural Studies
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• v.27
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• pp.255-289
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• 2012

In the course of completing a National Research Foundation project, I recently found that a handwritten Korean manuscript of The Tale of Mei Fei is kept in the Adan Collection, which is a significant scholarly discovery given that no relevant research is available. The editions of the Tale of Mei Fei available in Korea include ${\ll}$藝苑?華${\gg}$ edition, ${\ll}$說?${\gg}$ edition, and the handwritten manuscript in Korean collected in the Adan Collection. Being the only handwritten Korean translation of the work, the Tale of Mei Fei in the Adan Collection was appended by the translations of ${\ll}$한셩뎨됴비연합덕젼${\gg}$ and ${\ll}$당고종무후뎐${\gg}$. As for the practice of translation of the work, literal "word to word" translation was done for the most part of the text; some sentences were occasionally translated liberally. Also, as for the poems in the text, pronunciation of each Chinese character was provided along with the translated text.

• International Journal of Ocean System Engineering
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• v.2 no.1
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• pp.24-31
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• 2012

This paper introduce a technique for Word segmentation for the handwritten recognition of Urdu script. Word segmentation or word tokenization is a primary technique for understanding the sentences written in Urdu language. Several techniques are available for word segmentation in other languages but not much work has been done for word segmentation of Urdu Optical Character Recognition (OCR) System. A method is proposed for word segmentation in this paper. It finds the boundaries of words in a sequence of ligatures using probabilistic formulas, by utilizing the knowledge of collocation of ligatures and words in the corpus. The word identification rate using this technique is 97.10% with 66.63% unknown words identification rate.

• The Journal of Information Technology
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• v.9 no.3
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• pp.1-14
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• 2006

China has recently (28 August 2004) adopted a new act legalizing the electronic signature. This new act provides electronic signatures with the same legal status as handwritten signatures, and states that on-line certification providers will have to be created in order to ensure the security of on-line operations made using said signatures. This new act is intended to increase Chinese electronic business, and thus to raise the revenue China can expect from said business. And the law grants electronic signatures the same legal effect as handwritten signatures and seals in business transactions, and sets up the market access system for online certification providers to ensure the security of e-commerce. As Internet trade requires a reliable third party to identify the signers, the credibility of online certifying organizations is significant for the transaction security. So, considering the weakness of China's social credibility system, the law regulates that the online signatures certification providers should be approved and administered by governments.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.28B no.10
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• pp.747-754
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• 1991

In this paper, we studies the on-line recognition of handwritten character using WLD(weighted levenshtein distance) algorithm with parallelism. The Hangeul can be separated for unit of phonemes and the alphanumeric can be separated for unit of characters. And, we studies the parallelism and the concurrency of the WLD algorithm for realization of special-purpose processor. By the simulation result for 10, 000 characters in practical sentences, the recognition rate of strokes in obtained 96.57$\%$ and the separation rate for phonemes and characteristics is obtained 95.4$\%$.

• Journal of information and communication convergence engineering
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• v.21 no.2
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• pp.167-173
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• 2023

Hangul is unique compared to other Asian languages because of its simple letter forms that combine to create syllabic shapes. There are 24 basic letters that can be combined to form 27 additional complex letters. This produces 51 graphemes. Hangul optical character recognition has been a research topic for some time; however, handwritten Hangul recognition continues to be challenging owing to the various writing styles, slants, and cursive-like nature of the handwriting. In this study, a dataset containing thousands of samples of 51 Hangul graphemes was gathered from 110 freshmen university students to create a robust dataset with high variance for training an artificial neural network. The collected dataset included 2200 samples for each consonant grapheme and 1100 samples for each vowel grapheme. The dataset was normalized to the MNIST digits dataset, trained in three neural networks, and the obtained results were compared.

• Journal of Korea Multimedia Society
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• v.2 no.3
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• pp.297-307
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• 1999

A character recognition system, where a large amount of character images arrive continuously in real time, must preprocess character images very quickly. Moreover, information loss due to image trans-formations such as geometric normalization and thinning needs to be minimized especially when character images are small and noisy. Therefore, we suggest a prompt and effective feature extraction method without transforming original images. For this, boundary pixels are defined in terms of the degree in classification, and those boundary pixels are considered selectively in extracting features. The proposed method is tested by a handwritten character recognition and a car plate number recognition. The experiments show that the proposed method is effective in recognition compared to conventional methods. And an overall reduction of execution time is achieved by completing all the required processing by a single image scan.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.34C no.7
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• pp.61-69
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• 1997

With the vigorous researches in the character recognition, the need to recognize run-on multilingual handwritten characters is increasing to provide uses with more comfortable PUI(pen user interface) environments. In general, many intermediate word candidates word candidates are generated in run-on multilingual recognition because there is no information of ending position and linguistic kind of character. To remove unnecessary word candidates which are generated in run-on multilingual recognition, we classify them into two groups and select the best candidate among the word candidates in the group where the final characater is completed using 5 attributes. In this research, we propose a method in order to select the best one candidate. It is called WRM (Weighted ranking method). The weights are adaptively trained by LMS(Least mean square) learning rule. Results show that the abilities of decision makin gusing weights are much better than those not using weights.

• Journal of KIISE:Software and Applications
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• v.30 no.10
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• pp.904-911
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• 2003

In this paper, we propose an effective method for the distinction between machine-printed and handwritten Korean address images. It is important to know whether an input image is handwritten or machine-printed, because methods for handwritten image are quite different from those of machine-printed image in such applications as address reading, form processing, FAX routing, and so on. Our method consists of three blocks: valid connected components grouping, feature extraction, and classification. Features related to width and position of groups of valid connected components are used for the classification based on a neural network. The experiment done with live Korean address images has demonstrated the superiority of the proposed method. The correct classification rate for 3,147 testing images was about 98.85%.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.205-208
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• 2010

We introduce a novel feature extraction scheme for online handwritten digit based on utilizing Zernike moment and angulation feature. The time sequential signal from mouse movement on the writing pad is described as a sequence of consecutive points on the x-y plane. So, we can create data-set which are successive and time-sequential pixel position data by preprocessing. Data preprocessed is used for Zernike moment and angulation feature extraction. this feature is scale-, translation-, and rotation-invariant. The extracted specific feature is fed to a BP(backpropagation) neural network, which in turn classifies it as one of the nine digits. In this paper, proposed method not noly show high recognition rate but also need less learning data for 200 handwritten digit data.

• Journal of Industrial Technology
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• v.17
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• pp.331-338
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• 1997

In this paper, we propose a new neural pattern recognition from wavelet transform. We first analysis in BFT(Binary Field Transform) in character image. The proposed neural network and wavelet transform is able to improve learning time and scaling. The ability and effectiveness of identifying image using the proposed wavelet transform will be demonstrated by computer simulation.