• International Journal of Contents
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• v.8 no.1
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• pp.39-46
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• 2012

Character segmentation is a preprocessing step in many offline handwriting recognition systems. In this paper, Chinese characters are categorized into seven different structures. In each structure, the character size with the range of variations is estimated considering typical handwritten samples. The component removal and merge criteria are presented to remove punctuation symbols or to merge small components which are part of a character. Finally, the criteria for segmenting the adjacent characters concerning each other or overlapped are proposed.

• Journal of KIISE:Software and Applications
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• v.36 no.12
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• pp.1009-1015
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• 2009

Handwriting verification is a technique of distinguishing the same person's handwriting specimen from imitations with any two or more texts using one's handwriting individuality. This paper suggests an effective verification method for the handwritten signature or text on the off-line environment using pattern recognition technology. The core processes of the method which has been researched in this paper are extraction of letter area, extraction of features employing structural characteristics of handwritten text, feature analysis employing DTW(Dynamic Time Warping) algorithm and PCA(Principal Component Analysis). The experimental results show a superior performance of the suggested method.

• 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.

• Journal of KIISE:Software and Applications
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• v.27 no.6
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• pp.660-667
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• 2000

In this paper, a word segmentation method for handwritten Korean text line images is proposed. The method uses gap information to segment words in line images, where the gap is defined as a white run obtained after vertical projection of line images. Each gap is assigned to one of inter-word gap and inter-character gap based on gap distance. We take up three distance measures which have been proposed for the word segmentation of handwritten English text line images. Then we test three clustering techniques to detect the best combination of gap metrics and classification techniques for Korean text line images. The experiment has been done with 305 text line images extracted manually from live mail pieces. The experimental result demonstrates the superiority of BB(Bounding Box) distance measure and sequential clustering approach, in which the cumulative word segmentation accuracy up to the third hypothesis is 88.52%. Given a line image, the processing time is about 0.05 second.

• Journal of Information Processing Systems
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• v.11 no.3
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• pp.325-341
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• 2015

This paper describes the Tezpur University dataset of online handwritten Assamese characters. The online data acquisition process involves the capturing of data as the text is written on a digitizer with an electronic pen. A sensor picks up the pen-tip movements, as well as pen-up/pen-down switching. The dataset contains 8,235 isolated online handwritten Assamese characters. Preliminary results on the classification of online handwritten Assamese characters using the above dataset are presented in this paper. The use of the support vector machine classifier and the classification accuracy for three different feature vectors are explored in our research.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.36C no.7
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• pp.27-35
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• 1999

Researches on the recognition of handwritten script have been conducted under the assumption that the isolated recognition units are provided as inputs. However, in practical recognition system designs, providing the isolated recognition unit is an challenge due to various writing syles. This paper proposes an approach for segmenting words from lines of unconstrained handwritten text, without help of recognition. In contrast to the conventional approaches which are based on physical gaps between connected components, clues that reflect the author's writing style, in terms of spacing, are extracted and utilized for the segmentation using a simple neural network. The clues are from character segments and include normalized heights and intervals of the segments. Effectiveness of the proposed approach compared with the conventional connected component based approaches in terms of word segmentation performance was evaluated by experiments.

• Proceedings of the Korean Society for Cognitive Science Conference
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• 2000.01a
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• pp.63-67
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• 2000

• Annual Conference on Human and Language Technology
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• 2000.10d
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• pp.63-67
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• 2000

In order to develop a character recognition system, it is an essential preceding work that gathers an image data of the standard. On this purpose a data of the digitized images of a handwritten characters was collected. The types of a gathered image data are Korean character, Chiness character, Numeral, English character, Special character, and so on. This paper deals with a handwritten character image data base, and the image data base different from the general storage structure of a lame capacity multimedia was designed and builded.

• Journal of KIISE:Software and Applications
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• v.31 no.1
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• pp.8-19
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• 2004

In this paper, we propose an efficient method for locating destination address block on both of machine-Printed and handwritten Korean mail piece images. The proposed method extracts connected components from the binary mail piece image, generates text lines by merging them, and then groups the text fines into nine clusters. The destination address block is determined by selecting some clusters. Considering the geometric characteristics of address information on Korean mail piece, we split a mail piece image into nine areas with an equal size. The nine clusters are initialized with the center coordinate of each area. A modified Manhattan distance function is used to compute the distance between text lines and clusters. We modified the distance function on which the aspect ratio of mail piece could be reflected. The experiment done with live Korean mail piece images has demonstrated the superiority of the Proposed method. The success rate for 1, 988 testing images was about 93.56%.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.10
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• pp.4632-4641
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• 2011

The detailed production traceability information is a fundamental element in successful introduction and revitalization of traceability system. In this paper, we propose a production traceability information gathering system which is based on handwritten data digitalization technology in agro-livestock products. By the proposed system, we can effectively gather the detailed production traceability information with digital pen and the management ledger of paper document type by only writing the ledger. The server of the system generates the same digital image as the ledger and converts the handwritten data into digital text to insert the data into the database. Because the system is superior to data gathering system based on PC, PDA and touch screen in mobility, usability, data input speed, suitability in agro-livestock environment, it is possible to effectively gather traceability information of high quality by users even if they have low information ability and insufficient time to input data. We expect that the handwritten data digitalization technology is used to gather document based information in stage of manufacturing, distribution and marketing. In addition, this technology is applied to implementing advanced traceability system with RFID/USN based systems.