• Journal of Digital Contents Society
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• v.10 no.4
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• pp.493-499
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• 2009

Three methods frequently used for Hangul display in computer systems are Standard Johab Code in which each of Hangul consonants and vowels is given a 5-bit code and each syllable created by combining them forms a 2-byte code, Standard Wansung Code in which each of all the syllables generally used for Hangul presentation forms a 2-byte code, and Unicode in which each syllable in most of the world's language systems is given a unique code so that it allows computers to consistently represent and manipulate them in a unified manner. An embedded system in general has a lower processing power and a limited amount of storage space, compared to a personal compute(PC) system. According to its usage, however, the former may have a processing power equal to that of the latter. Hence, when Hangul display needs to be adopted, an embedded system must choose a display method suitable for its own resource environment. This paper introduces a TFT LCD initialization method and pixel display functions of an LN2440SBC embedded board on which an LP35, a 3.5" TFT LCD kit, is attached. Using the initialization and pixel display functions, in addition, we compare three aforementioned Hangul display methods, in terms of their processing speeds and amounts of memory space required. According to experiments, Standard Johab Code requires less amount of memory space but more processing time than Standard Wansung Code, and Unicode requires the largest amount of memory space but the least processing time.

• The Transactions of the Korea Information Processing Society
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• v.4 no.8
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• pp.2017-2024
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• 1997

The main focus of this paper is the recognition of printed Hangul documents in terms of typeface, character size and character slope for IICS(Intelligent Image Communication System). The fixed-size blocks extracted from documents are analyzed in frequency domain for the typeface classification. The vertical pixel counts and projection profile of bounding box are used for the character size classification and the character slope classification, respectively. The MLP with variable hidden nodes and error back-propagation algorithm is used as typeface classifier, and Mahalanobis distance is used to classify the character size and slope. The experimental results demonstrated the usefulness of proposed system with the mean rate of 95.19% in typeface classification. 97.34% in character size classification, and 89.09% in character slope classification.

• Korean Journal of Cognitive Science
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• v.27 no.2
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• pp.325-353
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• 2016

The visual span refers to the number of letters that can be accurately recognized without moving one's eyes. The size of the visual span is affected by sensory factors such as perimetric complexity, crowding, and mislocation of letters. Korean Hangul utilizes rather unique alphabetic-syllabary writing system, quite different from English and Chinese writing systems. Due to this combinatorial nature of the script, the visual span for Hangul characters can also be affected by the letter type (e.g., CV vs CVCC). The present study examined the effect of syllable complexity on the visual span for Hangul by comparing letter recognition accuracy across four letter type conditions (C only, CV, CVC, and CVCC). We also aimed to determine the meaningful letter type(s) that is associated with differences in reading abilities in Korean. Using a trigram presentation method, we found that overall recognition accuracy declined as syllable complexity increased. However, the visual span for CVC type was greater than that for CV type, suggesting that the effect is not necessarily linear, and that there might be other factors affecting the visual span for these types of letters. C and CV type showed fairly strong positive correlations with reading comprehension, suggesting that these might be the meaningful units for measuring visual span in relating to reading abilities.

• The Journal of Information Technology
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• v.4 no.1
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• pp.71-79
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• 2001

This paper presents an adaptive back propagation algorithm that update the learning parameter by the generated error, adaptively and configuration of the range for the initial connecting weight according to the different maximum target value from minimum target value. This algorithm is expected to escaping from the local minimum and make the best environment for the convergence. On the simulation tested this algorithm on three learning pattern. The first was 3-parity problem learning, the second was $7{\times}5$ dot alphabetic font learning and the third was handwritten primitive strokes learning. In three examples, the probability of becoming trapped in local minimum was reduce. Furthermore, in the alphabetic font and handwritten primitive strokes learning, the neural network enhanced to loaming efficient about 27%~57.2% for the standard back propagation(SBP).

• Journal of KIISE:Computer Systems and Theory
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• v.33 no.12
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• pp.894-906
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• 2006

There are many difficulties to develop a mobile contents due to many constraints on mobile environments. It is difficult to make a good mobile contents with only visual reduction of existing contents on wire Internet. Therefore, it is essential to devise the data representation and to develop the authoring tool to meet the needs of the mobile contents market. We suggest the compact mobile contents to learn Chinese characters and developed its authoring tool. The animation which our system produces is realistic as if someone writes letters with pen or brush. Moreover, our authoring tool makes a user generate a Chinese character animation easily and rapidly although she or he has not many knowledge in computer graphics, mobile programming or Chinese characters. The method to generate the stroke animation is following: We take basic character shape information represented with several contours from TTF(TrueType Font) and get the information for the stroke segmentation and stroke ordering from simple user input. And then, we decompose whole character shape into some strokes by using polygonal approximation technique. Next, the stroke animation for each stroke is automatically generated by the scan line algorithm ordered by the stroke direction. Finally, the ordered scan lines are compressed into some integers by reducing coordinate redundancy As a result, the stroke animation of our system is even smaller than GIF animation. Our method can be extended to rendering and animation of Hangul or general 2D shape based on vector graphics. We have the plan to find the method to automate the stroke segmentation and ordering without user input.

• Journal of the Korean Society of Safety
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• v.24 no.5
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• pp.92-100
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• 2009

This study evaluated the effects of the syllable number(one, two), font type(gothic, myung), color contrast (black on white, white on black), display type(paper, LCD), age(20s, 60s) and character size(2~80pt) on the Korean characters' legibility. Total twenty subjects from two age groups (20s: n=10, 60s: n=10, five male and five female in each group) participated in the legibility test. A target panel was presented in the distance of 50 cm, and subjects conducted a reading tests for, in total, 16 treatment conditions (full combination of syllable number, font type, color contrast and display type). Results showed that two-syllable words revealed better legibility than one-syllable character. The main effects of the age, display type, font type, color contrast, and character size were statistically significant(p<0.01). Paper showed better legibility than LCD, particularly in the 20s and in the character sizes of less than 9pt. Gothic revealed more correct answers than Myung, particularly in the 60s, paper, and white on black conditions. It is expected that these results can provide basic data for the determination of the Korean characters' minimum legible size standards. For example, the minimum legible size for the Gothic and black on white characters presented in the paper should be 5pt for 20s and 1lpt for 60s if the 75% correct reading(3 correct answers in this study) was applied for the legibility criterion.

• Journal of the Korean Data and Information Science Society
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• v.21 no.4
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• pp.689-697
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• 2010

In this study, we propose a new procedure for improving the character recognition of text area extracted from video images. The recognition of strings extracted from video, which are mixed with Hangul, English, numbers and special characters, etc., is more difficult than general character recognition because of various fonts and size, graphic forms of letters tilted image, disconnection, miscellaneous videos, tangency, characters of low definition, etc. We improved the recognition rate by taking commonly used letters and leaving out the barely used ones instead of recognizing all of the letters, and then using SVM and RDA character recognition methods. Our numerical results indicate that combining SVM and RDA performs better than other methods.