• Proceedings of the Korea Society of Design Studies Conference
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• 2001.10a
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• pp.32.2-32
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• 2001

• MALSORI
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• no.39
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• pp.43-51
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• 2000

The aim of this paper is to present a phonetically oriented keyboard array for the International Korean Phonetic Alphabet (IKPA). IKPA is a phonetic alphabet devised on the basis of Hangout (Korean alphabet) (Lee, 1999). Every computer has a keyboard as its input device and the English keyboard array is hewn as 'QWERTY' system, which represents the first six letters of the second line of the keyboard. This array is a traditional one devised to protect the congestion of the keys of the mechanical typewriter. To improve the anay of the keyboard, another system named 'Dvorak' has been devised. Likewise, a serious attempt has been made by the authors to work out an efficient keyboard for IKPA representing the manner of vowel and consonant classification. In the phonetic keyboard, the consonant symbols are arranged in the left hand side according to the Place and mauler of the articulation and the vowel symbols in the right hand side according to the vowel quadrilateral.

• Journal of Korea Game Society
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• v.9 no.4
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• pp.67-80
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• 2009

In this paper, we described the development of a Korean Manual Alphabet (KMA) learning game with avatar. KMA letters correspond to the vocabulary of Korean Sign Language (KSL) when spelling a word. Each KMA letter corresponds to a letter of the Korean Alphabet (KA) and KA is represented as hand shapes by sign language user. We developed a KMA learning game for a beginner to learn KMA letters from sign language avatar and practice KMA presentation easily. The system composed of sign language teacher avatar GUI popup window based on OpenGL, KMA letter recognition module, KA letter raining game module and USB camera. A user learns a KMA letter with expressing KA syllabic from avatar and inputs a KMA letter to the system using USB camera. We evaluated the efficiency of the developed system through the verification of users.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1996.10a
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• pp.333-336
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• 1996

The sign language is a method of communication for deaf person. For sign communication, sign language and manual alphabet are used continuously. In this paper is proposed a system which recognize Korean sign language(KSL) and Korean manual alphabet(KMA) continuously. For recognizing KSL and KMA, basic elements for sign language, namely, the 14 hand directions, 23 hand postures, and 14 hand orientations are used. At first, this system recognize current motion state using speed and change of speed in motion by state automata. Using state, basic element classifiers using Fuzzy Min-Max Neural Network and Fuzzy Rule are executed. Meaning of signed gesture is selected by using basic elements which was recognized.

• Korean Journal of Cognitive Science
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• v.5 no.2
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• pp.5-23
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• 1994

The present research measured interkey times in typewriting according to the mumber of consonants and vowels within words of the Korean alphabet. And another purpose of this study was to investigate whether the perception of syllable and final consonant, and one hand repetition can influence the interkey times in typewriting or not. The procedure of experiment was that subjects typed works according to the conditions. And we analyzed interkey times of each words. The results has shown that the perception of syllable and final consonant, and one hand repetition influenced the interkey times in typewriting.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.35C no.6
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• pp.76-87
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• 1998

This paper deals with a system which recognizes dynmic hand gestures, Korean Sign Language(KSL), mixed with static hand gesture, Korean Manual Alphabet(KMA), continuously. Recognition of continuous hand gestures is very difficult for lack of explicit tokens indicating beginning and ending of signs and for complexity of each gesture. In this paper, state automata is used for segmenting sequential signs into individual ones, and basic elements of KSL and KMA, which consist of 14 hand directions, 23 hand postures and 14 hand orientations are used for recognition of complex gestures under consideration of expandability. Using a pair of CyberGlove and Polhemus sensor, this system recognizes 131 Korean signs and 31 KMA's in real-time with recognition rate 94.3% for KSL excluding no recognition case and 96.7% for KMA.

• Journal of IKEEE
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• v.18 no.2
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• pp.291-297
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• 2014

Since hand gesture recognition was realized thanks to improved image processing algorithms, sign language translation has been a critical issue for the hearing-impaired. In this paper, we extract human hand figures from a real time image stream and detect gestures in order to figure out which kind of hand language it means. We used depth-color calibrated image from the Kinect to extract human hands and made a decision tree in order to recognize the hand gesture. The decision tree contains information such as number of fingers, contours, and the hand's position inside a uniform sized image. We succeeded in recognizing 'Hangul', the Korean alphabet, with a recognizing rate of 98.16%. The average execution time per letter of the system was about 76.5msec, a reasonable speed considering hand language translation is based on almost still images. We expect that this research will help communication between the hearing-impaired and other people who don't know hand language.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.6
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• pp.805-814
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• 2013

This paper proposes a robust hand segmentation method using view-invariant characteristic of a wrist-mounted camera, and deals with a hand shape recognition system based on segmented hand information. We actively utilize the advantage of the proposed camera device that provides view-invariant images physically, and segment hand region using a Bayesian rule based on adaptive histograms. We construct HSV histograms from RGB histograms, and update HSV histograms using hand region information from a current image. We also propose a user adaptation method by which hand models gradually approach user-dependent models from user-independent models as the user uses the system. The proposed method was evaluated using 16 Korean manual alphabet, and we obtained increases of 27.91% in recognition success rate.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2007.11a
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• pp.300-303
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• 2007

지문자는 청각장애인이 사용하는 수화로 표현하지 못하는 한글 문자를 알파벳으로 표시하기위한 손 제스처이다. 본 논문에서는 추출된 손 영역의 무게 중심과 퍼지 논리를 이용하여 지문자를 인식하는 알고리즘을 제안하고, 한글 문자를 표현하는 시스템을 개발한다. USB 카메라로부터 얻어진 영상에서 히스토그램을 이용하여 손의 피부색 영역을 추출하고, 영상 마스크를 이용하여 피부색이 아닌 배경 영역을 제거한다. 문턱 값을 사용하여 얻어진 이진화된 영상에서 손의 영역을 검출하고, 무게 중심을 이용하여 손 중심과 손가락 끝의 거리를 측정한다. 얻어진 거리 정보에 퍼지 기법을 적용하여 손가락의 굽힘 정도를 판단하고, 손 모양 데이터베이스에서 손가락 굽힘 정도와 가장 근사한 한글 문자를 선택한다.

• Journal of the Korean Society of Food Culture
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• v.31 no.4
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• pp.269-285
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• 2016

This study aimed to compare and analyze two respective versions of Jusikbangmun: Nogajae's and National Library of Korea. Types and composition of recipes, archives, classification of names and contents, techniques, tools, and measurement were analyzed. Nogajae's, owned by the Yuwagong family, has established sources while the writer and its publication year are unknown. The other version from the National Library of Korea, on the other hand, has a clear publication year (February, Year Jeongmi) while writer is unclear. In terms of its archive, Nogajae's is twice the size as that of the National Library of Korea, which is the same percentage (85.42%) as that from Nogajae's. However, six types of liquor have been written in its 2 books, respectively, and no overlaps occurred. Considering the Korean alphabet, Nogajae's was published earlier. Nogajae's and the one from the National Library of Korea have 104 kinds of foods (118 times) and 50 kinds of foods (51 times), respectively.