• 프린팅코리아
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• s.24
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• pp.116-121
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• 2004

현존 세계 최고의 금속활자본 직지심체요절이 유네스코의 '세계기록유산'으로 등재되면서 세계 각국의 '세계기록유산'은 어떤 것들이 있는지 관심이다. 2003년 8월 말 현재 33개국 68점이 세계기록유산에 올라 있는데 우리나라는 '직지'를 비롯 조선왕조실록, 승정원일기, 훈민정음 해례본이 등재되어 있다. 이에 세계 각국의 기록유산에 대해 청주 고인쇄박물관 이승철 학예연구사의 기고로 연재한다.

• Journal of the Korean Graphic Arts Communication Society
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• v.18 no.2
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• pp.103-111
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• 2000

We synthesized hexapyrrolylbenzene(HPB) an octapyrrolylenaphthalene(OPN) and measured photocurrent and darkcurrent of them. At the result, photocurrent of HBP/TiOPc and OPN/TiOPc systems were 1.81E-11 and 1.04E-10 at electric field 4.4$\times$10$^3$V/cm, and efficiency of them were 16 and 167 respectively.

• 프린팅코리아
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• s.25
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• pp.120-125
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• 2004

현존 세계 최고의 금속활자본 직지심체요절이 유네스코의 '세계기록유산'으로 등재되면서 세계 각국의 '세계기록유산'은 어떤 것들이 있는지 관심이다. 2003년 8월 말 현재 33개국 68점이 세계기록유산에 올라 있는데 우리나라는 '직지'를 비롯 조선왕조실록, 승정원일기, 훈민정음 해례본이 등재되어 있다. 이에 세계 각국의 기록유산에 대해 청주 고인쇄박물관 이승철 학예연구사의 기고로 연재한다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.18 no.6
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• pp.802-814
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• 1993

This paper propose an algorithm for preprocessing of character recognition, which classify characters into Hangeul and Hanja. In this study, we use the 9 structural chacteristics of Hanja which isn't affected by deformation of size and style of characters and rates based on character size to classify characters. Firstly, we process the blocking to segment each characters. Secondly, on this segmented characters, we apply algorithm proposed in this paper to classify Hangeul and Hanja. Finally, we classify characters into Hangeul and Hanja, respectively. An experiment with 2350 Hangeul and 4888 Hanja printed Gothic and Mincho style of KS-C 5601 are carried out. We experiment on typeface sample book, newspapers, academic society's papers, magazines, textbooks and documents written out word processor to obtain the classifying rates of 98.8%, 92%, 96%, 98% and 98%, respectively.

• Journal of the Korean Institute of Telematics and Electronics
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• v.21 no.3
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• pp.55-59
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• 1984

This paper describes a method of Hangout recognition using 2 - D digital filtering. The 170 patterns classified by the positions of the initial sound (consonant), middle sound (vowel) and terminal sound (consonant) of the 1,659 characters were established and models formed by using 2 - D digital filtering for each patterns were obtained. Based on these models we proposed an algorithm that can recognize KOREAN combinational characters by separating patterns from them with superpostion principles. As a result of simulation, 100% of recognition rate is obtained in the case of the print letter.

• Korean Journal of Cognitive Science
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• v.2 no.1
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• pp.33-50
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• 1990

Recently, neural networks have been proposed as computaional models for hard prlblems that the brain appears to solve easily. This paper proposes a hierarchical network which practically recognizes printed Hangul characters based on the various psychological stueies. This system is composed of a type classification netwotk and six recognition networks. The former clessifier input character images into one of the six thper by their overall sturcture, and the latter further classify them into character code. Extperiments with most frequently used 990 printed hangul characters conform the superiority of the propsed system. After all, neural nework approach turns out to be very reasonable through a comparison with statistical classifier and an analysis of mis-classification and generalization capability.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.18 no.9
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• pp.1269-1282
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• 1993

In this paper, we propose to method of recognizing printed chinese characters which combine the coventional deterministic methods and the neural networks. Firstly, we extract four directional vector of strokes from chinese characters. Secondly, we make the mesh of the center of gravity in the vector and then constitute the H x8 feature matrix using black pixel lenth from each meshs. This normalized feature matrix value offer as the input of neural network for classifying into the 14 character types. And this calssified character classify again into Busu group by the Busu recognizing neural network. Finally, we recognize each characters using the distance of similarity between input characters and reference characters. The usefulness of the proposed algorithm is evaluated by experimenting with recognizing the chinese characters.

• The Transactions of the Korea Information Processing Society
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• v.5 no.1
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• pp.119-127
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• 1998

In this paper, the design of a VLSI-based multilayer neural network is presented, which can be used as a dedicated hardware for character-type segmentation and character-element recogniti on consuming large processing time in conventional software-based Hangul printed-character recognition systems. Also the architecture and its design of a neural coprocessor interfacing the neural network with a host computcr and controlling thc neural network are presented. The architecture, behavior, and performance of the proposed neural coprocessor are justified using VHDL modeling and simulation. Experimental results show the successful rates of character-type segmentation and character-element recognition is competitive to those of software-based Hangul printed-character recognition systems with retaining high-speed.

• The Transactions of the Korea Information Processing Society
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• v.4 no.7
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• pp.1881-1892
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• 1997

This paper proposes the method for recognition of printed chinese characters by probabilistic VQ networks and multi-stage recognizer has hierarchical structure. We use modular neural networks, because it is difficult to construct a large-scale neural network. Problems in this procedure are replaced by probabilistic neural network model. And, Confused Characters which have significant ratio of miss-classification are reclassified using the entropy theory. The experimental object consists of 4,619 chinese characters within the KSC5601 code except the same shape but different code. We have 99.33% recognition rate to the training data, and 92.83% to the test data. And, the recognition speed of system is 4-5 characters per second. Then, these results demonstrate the usefulness of our work.

• Archives of design research
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• v.20 no.1 s.69
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• pp.219-228
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• 2007

Printing advertisement is aggregate of commercial information communication text consisted of image sign and language sign. This means that verbal tabor through visual stimulation and character is mixed and passes information through picture. Typography is process that visualize verbal appeal in printing advertisement. Therefore study about typography is very important for a visual expression element in printing advertisement. Typography expression of Korean printing advertisement accomplished fast qualitative growth after 2000 flowing the 1990s. This study makes that typography expression propensity of Korean printing advertisement after 2000 of changed of expression structure, changed of expression rule, changed of expression method etc. Accordingly, extracted each three analysis bases. And this study presented expansive direction of typography expression of printing advertising in case studies.