• Journal of applied mathematics & informatics
• /
• v.3 no.2
• /
• pp.157-168
• /
• 1996

This paper describes an efficient coding method for Ko-rean characters (alphabet) using a three-state transition graph. Par-allel hangul Dynamic Coding Method (PHDCM) compresses about 3.5 bits per Korean character compared with other coding techinques. When we ran the method on a MasPar machine it achieved a 49.314-fold speedup with 64 processors having 10 million orean characters

• Proceedings of the KIEE Conference
• /
• 1987.07b
• /
• pp.1445-1448
• /
• 1987

The phase-only filter (POF) to the classical matched filter is compared for the criteria of discrimination, correlation peak, and optical efficiency in Korean alphabet. In addition, logarithmically scaled POF is presented to improve the recognition efficiency and this shows the superior performances in English alpanumeric characters to Korean.

• Cross-Cultural Studies
• /
• v.30
• /
• pp.223-244
• /
• 2013

Sino-Korean words make almost 70% of Korean words. Chinese Characters are very different from Hangul (Korean alphabet system) in form and they are semantic symbols. Therefore Korean and foreign students are very likely to have difficulty in mastering the Sino-Korean characters. This paper aims at reviewing the problems of teaching Chinese characters to Koreans and foreigners in Korea, and proposing how to teach them effectively. For this purpose, we first look into the realities of the national system of Chinese characters' education, and then suggest more effective instructions in teaching Chinese characters.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.18 no.4
• /
• pp.451-455
• /
• 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.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2009.01a
• /
• pp.547-550
• /
• 2009

The object recognition mechanism of human being is not well understood yet. On research of animal experiment using an ape, however, neurons that respond to simple shape (e.g. circle, triangle, square and so on) were found. And Hypothesis has been set up as human being may recognize object as combination of such simple shapes. That mechanism is called Figure Alphabet Hypothesis, and those simple shapes are called Figure Alphabet. As one way to research object recognition algorithm, we focused attention to this Figure Alphabet Hypothesis. Getting idea from it, we proposed the feature extraction algorithm for object recognition. In this paper, we described recognition of binarized images of multifont alphabet characters by the recognition model which combined three-layered neural network in the feature extraction algorithm. First of all, we calculated the difference between the learning image data set and the template by the feature extraction algorithm. The computed finite difference is a feature quantity of the feature extraction algorithm. We had it input the feature quantity to the neural network model and learn by backpropagation (BP method). We had the recognition model recognize the unknown image data set and found the correct answer rate. To estimate the performance of the contriving recognition model, we had the unknown image data set recognized by a conventional neural network. As a result, the contriving recognition model showed a higher correct answer rate than a conventional neural network model. Therefore the validity of the contriving recognition model could be proved. We'll plan the research a recognition of natural image by the contriving recognition model in the future.

• The KIPS Transactions:PartA
• /
• v.10A no.5
• /
• pp.463-468
• /
• 2003

The Internet, especially the mobile Internet influences enormously in many areas in human societym espeially in terms of the exchanging speed of knowledge and information. This new society of knowledge and information will introduce many new types of services based on valuable knowlwdge and information. Among many new services in this mobile computing environment, the real-time worldwide korean information networking service using the Korean characters invented by the mobile computing environment, the real-time worldwide Korean information networking service using the Koean characters invented by the King Sejong is possible ubiquitously with wired and mobile Internet. We studied the user interface with Korean characters in the mobile computing environment, and introduce the useful results with new metrics of performance analysis after real implementation for real-time Korean information networking using Korean domain names.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.8 no.3
• /
• pp.225-230
• /
• 2008

In this paper we embody a system that recognizes printed alphabet, numeral figures and symbols written on the keyboard for the recognition of English sentences. The image of the printed sentences is inputted and binarized, and the characters are separated by using histogram method that is the same as the existing character recognition method. During the abstraction of the individual characters, we classify one group that has not numerical information by the projection of the vertical center of the character. In case of another group that has the longer width than the height, we assort them by normalizing the width. The other group normalizes the height of the images. With the reverse application of the basic principle of the Japanese Puzzle to a normalized character image, the proposed system classifies and recognizes the printed numeral figures, symbols and characters, consequently we meet with good result.

• Communications of Mathematical Education
• /
• v.27 no.4
• /
• pp.391-406
• /
• 2013

Most of mathematical terms in Korean are Sino-Korean words. It is necessary to find the efficient ways to teach Sino-Korean mathematical terms to mathematics teachers and students who dot not know Chinese characters well and use only Korean alphabet in mathematics. Especially, we have to avoid the inappropriate Sino-Korean words which can cause misconceptions and can distinguish homophones by Korean alphabet. We may use native Korean terms to do that and the national curriculum can play an important role. In this paper, we investigate the way of improving mathematics terms in Korea with concrete examples.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2021.10a
• /
• pp.624-626
• /
• 2021

Yumentingzheng, which records the contents of the Qing dynasty's discussions with his subjects, is an important document like the Annals of Joseon in Korea. This paper describes the method and steps for big data analysis of Yumentingzheng written in Manchu alphabet. In big data analysis of documents written in Manchu characters, there are many problems that need to be solved in advance, and research on these should be preceded. In this paper, a method of big data analysis using the R language was proposed in the stage where the text written in Manchurian characters was transliterated into Latin characters through a preliminary study to be conducted in the future. In the proposed method, Apkai method was adopted for the transliteration of Wumentingzheng, and the results of big data analysis were presented using the text of Weiwenqiju.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2001.04a
• /
• pp.125-130
• /
• 2001

Skilled typists can type characters or words without looking at keyboard, relying on the finger's relative position. If the relative positions of the fingers can be identified, a virtual keyboard may be accomplished by applying the concept of "DataGlove" or "FingerRing". The virtual keyboard may be efficient as a new mobile input device supporting QWERTY keyboard layout. For the purpose of investigating skilled typing pattern, in this paper the touch-positions of the fingers are measured with a touchscreen while five skilled typists type a long sentence. From these measurements it can be observed that the groups of touch-positions are classified into alphabet characters. Though there are some overlapped groups we can find constant distances capable of being discriminated among the groups from investigation of the change of touch-position for touch-time. Based on the analysis, the prediction algorithm of the constant distance is proposed and evaluated, which is useful for realization of a portable virtual keyboard.le virtual keyboard.