• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2002.12a
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• pp.361-364
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• 2002

본 논문에서는 일반적인 문서를 CCD 카메라로 입력 받은 후, 사용자가 원하는 영역을 손가락으로 선택하면, 손 인식 알고리즘을 적용하여 사용자의 손가락 움직임을 검출하고, 손가락으로 선택되어진 영역을 인식한 후, 선택되어진 영역으로 카메라를 이동시켜 획득된 영상을 문자 인식 가능한 크기로 확대/축소하며, 확대된 영상에 문자인식 알고리즘을 적용하여 문서로 변환하는 시스템을 구현하였다 최종적으로 사용자가 이 시스템의 존재를 인지하지 못할 만큼 자연스럽게 사용할 수 있는 시스템을 구현하고자 하였다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.05a
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• pp.77-79
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• 2012

The paper deals with the approximate analysis of printed antenna like superconductor antenna. Analysis of antenna with polarization current in dielectric layer using Moment method. This approximation is very useful for printed antenna on dielectric plane with low dielectric constant. In this paper, we compared numerical results of this method with measurement results.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.5 no.2
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• pp.123-127
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• 2004

A printed folded-monopole antenna for portable wireless applications is presented. The proposed design is based on the folded quarter-wave antennas, which have a conductor plate having two arms. A prototype antenna is fabricated according to the simulation result. The obtained antenna can perform in 2.4GHz band and be adopted for laptop applications. All the measurements are performed in the actual test fixture.

• 프린팅코리아
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• s.33
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• pp.124-125
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• 2005

올해는 유네스코 세계기록유산인 (백운화상초록불조직지심체요절)이 프랑스에서 공개된 지 35년이 되는 해이다. 또한 (직지)를 간행한 청주 흥덕사 터를 발굴한 지 20주년이 되는 해이기도 하다.

• The Magazine of the IEIE
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• v.17 no.6
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• pp.53-60
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• 1990

본 글은 완성된 circuit를 thick-film hybrid IC화 하기 위하여 고려하여야 할 사항인 설계의 기본개념, 기판 재질의 소개 및 특성, 도체, 저항, 유전체 paste를 소개하고 제조 기술 분야에서는 기본공정인 인쇄, 소성, 트리밍, packaging에 대하여 기술하였다.

• The KIPS Transactions:PartB
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• v.10B no.7
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• pp.777-784
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• 2003

In this Paper. we propose a recognition method of machine printed characters based on the combination of recognition units using multiple neural networks. In our recognition method, the input character is classified into one of 7 character types among which the first 6 types are for Hangul character and the last type is for non-Hangul characters. Hangul characters are recognized by several MLP (multilayer perceptron) neural networks through two stages. In the first stage, we divide Hangul character image into two or three recognition units (HRU : Hangul recognition unit) according to the combination fashion of graphemes. Each recognition unit composed of one or two graphemes is recognized by an MLP neural network with an input feature vector of pixel direction angles. In the second stage, the recognition aspect features of the HRU MLP recognizers in the first stage are extracted and forwarded to a subsequent MLP by which final recognition result is obtained. For the recognition of non-Hangul characters, a single MLP is employed. The recognition experiments had been performed on the character image database collected from 50,000 real letter envelope images. The experimental results have demonstrated the superiority of the proposed method.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.1
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• pp.1-5
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• 2003

In this paper, we realized a system that converts the character images of the printed Korean alphabet (Hangul) to the editable text documents by using the black and white CCD camera, We were able to abstract the contours information of the character which is based on the structural character by using the boundary tracing technique that is strong to the noise on the character recognition. By using the contours information, we recognized the horizontal vowels and vertical vowels of the character image and classify the character into the six patterns. After that, the character is divided to the unit of the consonant and vowel. The vowels are recognized by using the maximum length projection. The separated consonants are recognized by comparing the inputted pattern with the standard pattern that has the phase information of the boundary line change. We realized a system that the recognized characters are inputted to the word editor with the editable KS Hangul completion type code.

• 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 Journal of the Korea Contents Association
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• v.8 no.11
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• pp.33-40
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• 2008

The application of OCR moves from traditional formatted documents to the web document and natural scene images. It is usual that the new applications use not only standard fonts of Myungjo and Godic but also various fonts. The conventional databases which have mainly been constructed with standard fonts have limitations in applying to the new applications. In this paper, we generate 243 image samples for each of 2350 Hangul character classes which differs in font size, quality, and resolution. Additionally each sample was varied according to binarization threshold and rotational transformation. Through this process 2187 samples were generated for each character class. Totally 5,139,450 samples constitutes the printed Hangul character database called the PHD08. In addition, we present the characteristics and recognition performance by an commercial OCR software.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.12
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• pp.2364-2375
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• 1994

For the efficient recognition of printed Korean characters, a multiplexed minimum average correlation energy(MMACE) filter is proposed. Proposed method solved the disadvantages of the tree structure algorithm which recognition system is very huge and recognition method is sophisticated. Using only one consonant MMACE filter and one vowel one, we recognized the full Korean character. Each MMACE filter is multiplexed by 4 K-tuple MACE filters which are synthesized by 24 consonants and vowels. Hence the proposed MMACE filter and the correlation distribution plane are divided by 4 subregion. We obtained the binary codes for the Korean character recognition from each correlation distribution subplane. And the obtained codes are compared with the truth table for consonants and vowels in computer. We can recognize the full Korean characters when substitute the corresponded consonant or vowel font of the consistent code to the correlation peak place in the output correlation plane. The computer simulation and optical experiment results show that the proposed compact Korean character recognition system using the MMACE filters has high discrimination capability.