• Title/Summary/Keyword: printed font

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Bubyeogru-junsugi and the books printed with the same type font -Anti-Chwijinja font- (부벽루중수기와 같은 활자 인본들 -반'취진자'론-)

  • Yoon Byeong-tae
    • Journal of the Korean Society for Library and Information Science
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    • v.3
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    • pp.47-82
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    • 1973
  • In this study, I have tried to examine the movable type font called 'Chwijinja' (聚珍字) as hitherto and the book printed in Chwijinia for the first time. In order to illustrate the orgin of it more clearly, I introduced Bubyeogru-jungsugi(浮碧樓重修記.) which has been believed the first printed edition of this book and also some other books printed in the same movable type font. By the way, I introduced some views of other bibliographers on Chwijinja. I refuted the views that Chwijinja is metal type and then I substantiated it is wooden type. I also presented three hypotheses on the formation of Chwijinja. I described the reason why we had better change the name of that printing type into 'Bang-Chwijin-pansig Pilseoche Wooden Type'(倣聚珍版式筆書木活字) on the basis of that its name is common noun. I also explained about 'Yeonmu Wooden Type'(燕貿木(唐)字, Wooden Type font imported from China) which is relevant to my description.

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A Study of the Books Printed with a Newly Found Font, Tentatively Named "Muin-ja" (세조조(世祖朝) 신주(新鑄)의 '무인자(戊寅字)'와 그 간본(刊本) -주(主)로 그 주자(鑄字)의 고증(考證)을 중심(中心)으로-)

  • Chon, Hye-Bong
    • Journal of the Korean BIBLIA Society for library and Information Science
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    • v.2 no.1
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    • pp.102-131
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    • 1974
  • The author's thesis is that the types used for the large-sized characters seen in the two metal type-printed books "Kyosik chubopop karyong"(交食推步法假令) and "Yok-hak kemong yohae"(易學啓蒙要解) both printed in 1458 belong to a new metal font hitherto unnamed. The former book was compiled by Yi Sun-ji(李純之) and Kim Sok-je(金石梯) in January of 1458 in accordance to King Sejo's order. A new font was created to be used for the large-sized characters of the book. Several. months after completion of the compilation, the book was printed with mixed use of the new font and the Kabin-ja(甲寅字) for medium- and small-sized characters. The latter book had been written by King Sejo before his accession to the throne. Ascending the throne the king had his scholar-subjects examine the writing to correct it where necessary. The examination was completed in July of 1458 and printing was immediately done with the two fonts the above-mentioned, new font for the large-sized letters and the Kabin-ja for the medium- and small-sized ones. The books were granted to the scholar-subjects and the students of the Sung Kyun Kwan Academy as a royal gift. The matrix seems to have been modeled after the calligraphy of King Sejo. Because the new font was created to print the large-sized letters of the two books in 1458, it may be proper to name it "Muin-ja" using the "kanji"(干支) of the year. The author is happy to identify and include another font in the list of Korean movable types as a result of the present study.

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Machine Printed and Handwritten Text Discrimination in Korean Document Images

  • Trieu, Son Tung;Lee, Guee Sang
    • Smart Media Journal
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    • v.5 no.3
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    • pp.30-34
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    • 2016
  • Nowadays, there are a lot of Korean documents, which often need to be identified in one of printed or handwritten text. Early methods for the identification use structural features, which can be simple and easy to apply to text of a specific font, but its performance depends on the font type and characteristics of the text. Recently, the bag-of-words model has been used for the identification, which can be invariant to changes in font size, distortions or modifications to the text. The method based on bag-of-words model includes three steps: word segmentation using connected component grouping, feature extraction, and finally classification using SVM(Support Vector Machine). In this paper, bag-of-words model based method is proposed using SURF(Speeded Up Robust Feature) for the identification of machine printed and handwritten text in Korean documents. The experiment shows that the proposed method outperforms methods based on structural features.

Machine-Printed Character Segmentation according to Font Style (문자 스타일에 따른 문자 분할)

  • Jung Minchul
    • Proceedings of the KAIS Fall Conference
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    • 2004.11a
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    • pp.163-165
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    • 2004
  • An identification of a font allows that an OCR system can perform font-specific processes, which consist of various mono-font segmentation tools and recognizers According to the font styles, character segmentation method should be applied differently. Touching characters in slant style cannot be segmented vertically but segmented on a slant. This paper proposes that touching characters in italic style can be segmented vertically after slant normalization.

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Study on the Interfaces Phenomenon in the Lithography (평판인쇄에 있어서 계면현상에 관한 연구)

  • 김성빈;이상남
    • Journal of the Korean Graphic Arts Communication Society
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    • v.3 no.1
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    • pp.43-50
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    • 1985
  • This paper describes an algorithm recognizing multi-font printed numeric characters. In order to extract feature selection of printed numeric characters. this paper describes an algorithm using stoke density function. Printed numeric characters are recognized by using the set of stroke-density feature vectors.

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A Recognition of the Printed Alphabet by Using Nonogram Puzzle (노노그램 퍼즐을 이용한 인쇄체 영문자 인식)

  • Sohn, Young-Sun;Kim, Bo-Sung
    • Journal of the Korean Institute of Intelligent Systems
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    • v.18 no.4
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    • pp.451-455
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    • 2008
  • In this paper we embody a system that recognizes the printed alphabet of two font types (Batang, Dodum) inputted by a black-and-white CCD camera and converts it into an editable text form. The image of the inputted printed sentences is binarized, then the rows of each sentence are separated through the vertical projection using the Histogram method, and the height of the characters are normalized to 48 pixels. With the reverse application of the basic principle of the Nonogram puzzle to the individual normalized character, the character is covered with the pixel-based squares, representing the characteristics of the character as the numerical information of the Nonogram puzzle in order to recognize the character through the comparison with the standard pattern information. The test of 2609 characters of font type Batang and 1475 characters of font type Dodum yielded a 100% recognition rate.

Preference and Readability of Hangul Fonts in the Presbyopic Age (노안 연령에서 한글서체의 선호도와 가독성 평가)

  • Jeung, Shinhae;Son, Jeong-Sik;Hwang, Hae-Young;Kim, Seong Kun;Yu, Dong-Sik
    • Journal of Korean Ophthalmic Optics Society
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    • v.18 no.2
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    • pp.149-156
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    • 2013
  • Purpose: The aim of this study was to determine a suitable type and size of Hangul fonts for printed materials in the presbyopic age. Methods: Based on the most common Hangul fonts used today, three types of fonts were used Hamchrombatang, Sinmoonmyungjo and Sinmyungjo at small font sizes in the range 9-11 point (pt). Subjects were 101 volunteers aged 41 through 85 years. Near visual acuity (VA) was corrected to read VA 0.5 at 40 cm after distance correction. The subjects were asked to read words containing 88 characters in 10 pt after a question about preference. Readability was assessed by reading rate that was calculated as the number of words read correctly in one minute (words per minute, wpm). Results: The most preferred font type was Simmyungjo at small font sizes. Although preferred font sizes were different in each font type, Sinmyungjo was generally preferred at 10 pt more than other fonts. Hamchrombatang and Sinmyungjo were read significantly faster than Sinmoonmyungjo. There was a weak negative relationship between readability and age in Sinmyungjo. In comparing between the top 10% and the bottom 10% group sorted by reading rate, the top group showed lower average age and addition than the bottom group, however there were no significant differences in reading rate among the fonts. Conclusions: Although increasing age tends to be low in readability for Sinmyungjo, in the light of preferred font and readability, it is recommended to use a 10 pt Sinmyungjo font in printed materials for the presbyopic age.

Font Classification of English Printed Character using Non-negative Matrix Factorization (NMF를 이용한 영문자 활자체 폰트 분류)

  • Lee, Chang-Woo;Kang, Hyun;Jung, Kee-Chul;Kim, Hang-Joon
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.41 no.2
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    • pp.65-76
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    • 2004
  • Today, most documents are electronically produced and their paleography is digitalized by imaging, resulting in a tremendous number of electronic documents in the shape of images. Therefore, to process these document images, many methods of document structure analysis and recognition have already been proposed, including font classification. Accordingly, the current paper proposes a font classification method for document images that uses non-negative matrix factorization (NMF), which is able to learn part-based representations of objects. In the proposed method, spatially total features of font images are automatically extracted using NMF, then the appropriateness of the features specifying each font is investigated. The proposed method is expected to improve the performance of optical character recognition (OCR), document indexing, and retrieval systems, when such systems adopt a font classifier as a preprocessor.

A Study on the Hangul Recognition Using Hough Transform and Subgraph Pattern (Hough Transform과 부분 그래프 패턴을 이용한 한글 인식에 관한 연구)

  • 구하성;박길철
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.3 no.1
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    • pp.185-196
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    • 1999
  • In this dissertation, a new off-line recognition system is proposed using a subgraph pattern, neural network. After thinning is applied to input characters, balance having a noise elimination function on location is performed. Then as the first step for recognition procedure, circular elements are extracted and recognized. From the subblock HT, space feature points such as endpoint, flex point, bridge point are extracted and a subgraph pattern is formed observing the relations among them. A region where vowel can exist is allocated and a candidate point of the vowel is extracted. Then, using the subgraph pattern dictionary, a vowel is recognized. A same method is applied to extract horizontal vowels and the vowel is recognized through a simple structural analysis. For verification of recognition subgraph in this paper, experiments are done with the most frequently used Myngjo font, Gothic font for printed characters and handwritten characters. In case of Gothic font, character recognition rate was 98.9%. For Myngjo font characters, the recognition rate was 98.2%. For handwritten characters, the recognition rate was 92.5%. The total recognition rate was 94.8% with mixed handwriting and printing characters for multi-font recognition.

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