• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2005.11a
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• pp.199-202
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• 2005

TV OSD(On Screen Display) 메뉴 자동검증 시스템에서 다국적 언어의 문자 인식은 표준패턴의 구조적 분석이 쉽지 않을 뿐만 아니라 학습패턴 집합의 규모와 특징의 수가 증가함으로 인하여 특징추출 및 인식 과정에서 방대한 계산량이 요구된다. 이에 본 연구에서는 학습 데이터에 포함되는 다량의 특징 집합으로부터 인식에 필요한 효과적인 특징을 선별함으로써 패턴 분류기의 효율성을 개선하기 위한 방법론을 고찰한다. 이를 위하여 수정된 형태의 Adaboost 기법을 제안하고 이를 적용한 실험 결과로부터 그 유용성을 고찰한다. 제안된 알고리즘은 초기의 특징 집합을 취약한 성능을 갖는 다수의 분류기(classifier)로서 고려하며, 이로부터 반복학습을 통하여 개선된 분류기를 점진적으로 선별해 나가게 된다. 학습의 원리는 주어진 학습패턴 집합에 기초하여 일종의 교사학습(supervised learning) 방식으로 이루어진다. 각 패턴에 할당된 가중치 값은 각 단계에서 산출되는 분류결과에 따라 적응적으로 수정되어 반복학습이 진행됨에 따라 점차 보완적 성능을 갖는 분류기를 선택할 수 있게 한다. 즉, 주어진 각 학습패턴에 대하여 초기에 균등한 가중치가 부여되며, 반복학습의 각 단계에서 적용되는 분류기의 출력을 분석하여 오분류된 패턴의 가중치 분포를 증가시켜 나간다. 본 연구에서는 실제 응용으로서 OSD 메뉴검증 시스템을 대상으로 제안된 이론을 적용하고 그 타당성을 평가한다.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.135-139
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• 2009

In this paper we present INCUI, a user interface based on natural view of physical user interface of target devices and services in pervasive computing environment. We present a concept of Intuitively Natural and Consistent User Interface (INCUI) consisted of an image of physical user interface and a description XML file. Then we elaborate how INCUI template can be used to consistently map user interface components structurally and visually. We describe the process of INCUI mapping and a novel mapping method selection architecture based on domain size, types of source and target INCUI. Especially we developed and applied an extended LCS-based algorithm using prefix/postfix/synonym for similarity calculation.

• The Journal of the Acoustical Society of Korea
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• v.10 no.1
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• pp.82-91
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• 1991

The history of automatic speech recognition research, and current and future speech products at Fujitsu are introduced here. The speech recognition research at Fujitsu started in 1970. Our research efforts have results in the production of a speaker dependent 12,000 word discrete / connected word recognizer(F2360), and a speaker independent 17 word discrete word recognizer(F2355L/S). Currently, we are working on a larger vocabulary speech recognizer, in which an input utterance will be matched with networks representing possible phonemic variations. Its application to text input is also discussed.

• Proceedings of the Korean Information Science Society Conference
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• 2001.10b
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• pp.325-327
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• 2001

본 논문은 온라인 문자 인식을 연속 밀도 HMM의 구조의 최적화 문제를 다룬다. 최적이란 최소한의 모델 파라미터를 사용하여 최소한의 오류를 허용하는 것이라고 정의할 수 있다. 본 연구에서는 HMM 구조의 최적화를 위해 Bayesian 모델 선택 방법론을 사용한다. 먼저 잘 알려진 BIC(Bayesian Information Criterion)을 적용해보고, 그것을 HMM의 복잡한 구조에 적합하도록 본 논문에서 제안한 HBIC(HMM-Oriented BIC)와 비교해본다. BIC는 모델의 사전 확률 분포를 추정하지 않고 다변량 정규분포라고 가정하는데 비해 HBIC는 모델의 각 파라미터로부터 사전 확률을 추정한 후 그것들을 사용함으로써 더 좋은 결과를 얻도록 한다. 실험 결과 BIC와 HBIC 둘 다 기존 방법보다 모델의 파라미터 수를 현저히 감소시킴을 확인했고, HBIC가 BIC에 비해 더 적은 수의 파라미터를 사용해도 비슷한 인식률을 얻을 수 있었다.

• Korean Journal of Cognitive Science
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• v.3 no.1
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• pp.61-78
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• 1991

This paper descibes the study of application of a modified Neocognitron model with backward path for the recognition of Hangul(Korean) syllabic characters. In this original report, Fukushima demonstrated that Neocognitron can recognize hand written numerical characters of $19{\times}19$ size. This version accepts $61{\times}61$ images of handwritten Hangul syllabic characters or a part thereof with a mouse or with a scanner. It consists of an input layer and 3 pairs of Uc layers. The last Uc layer of this version, recognition layer, consists of 24 planes of $5{\times}5$ cells which tell us the identity of a grapheme receiving attention at one time and its relative position in the input layer respectively. It has been trained 10 simple vowel graphemes and 14 simple consonant graphemes and their spatial features. Some patterns which are not easily trained have been trained more extrensively. The trained nerwork which can classify indivisual graphemes with possible deformation, noise, size variance, transformation or retation wre then used to recongnize Korean syllabic characters using its selective attention mechanism for image segmentation task within a syllabic characters. On initial sample tests on input characters our model could recognize correctly up to 79%of the various test patterns of handwritten Korean syllabic charactes. The results of this study indeed show Neocognitron as a powerful model to reconginze deformed handwritten charavters with big size characters set via segmenting its input images as recognizable parts. The same approach may be applied to the recogition of chinese characters, which are much complex both in its structures and its graphemes. But processing time appears to be the bottleneck before it can be implemented. Special hardware such as neural chip appear to be an essestial prerquisite for the practical use of the model. Further work is required before enabling the model to recognize Korean syllabic characters consisting of complex vowels and complex consonants. Correct recognition of the neighboring area between two simple graphemes would become more critical for this task.

• The Journal of Bigdata
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• v.5 no.1
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• pp.29-39
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• 2020

Purpose The atmosphere of respect for individual tastes that have spread throughout society has changed the consumption trend. As a result, the travel industry is also seeing customized travel as a new trend that reflects consumers' personal tastes. In particular, there is a growing interest in 'film-induced tourism', one of the areas of travel industry. We hope to satisfy the individual's motivation for traveling while watching movies with customized travel proposals, which we expect to be a catalyst for the continued development of the 'film-induced tourism industry'. Design/methodology/approach In this study, we implemented a methodology through 'OCR' of extracting and suggesting film location information that viewers want to visit. First, we extract a scene from a movie selected by a user by using 'OpenCV', a real-time image processing library. In addition, we detected the location of characters in the scene image by using 'EAST model', a deep learning-based text area detection model. The detected images are preprocessed by using 'OpenCV built-in function' to increase recognition accuracy. Finally, after converting characters in images into recognizable text using 'Tesseract', an optical character recognition engine, the 'Google Map API' returns actual location information. Significance This research is significant in that it provides personalized tourism content using fourth industrial technology, in addition to existing film tourism. This could be used in the development of film-induced tourism packages with travel agencies in the future. It also implies the possibility of being used for inflow from abroad as well as to abroad.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.10 no.1
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• pp.63-68
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• 2010

Recently, to accelerate the Ubiquitous generation, the input interface of the mobile machinery and tools are actively being researched. In addition with the existing interfaces such as the keyboard and curser (mouse), other subdivisions including the handwriting, voice, vision, and touch are under research for new interfaces. Especially in the case of small-sized mobile machinery and tools, there is a increasing need for an efficient input interface despite the small screens. This is because, additional installment of other devices are strictly limited due to its size. Previous studies on handwriting recognition have generally been based on either two-dimensional images or algorithms which identify handwritten data inserted through vectors. Futhermore, previous studies have only focused on how to enhance the accuracy of the handwriting recognition algorithms. However, a problem arisen is that when an actual handwriting is inserted, the user must select the classification of their characters (e.g Upper or lower case English, Hangul - Korean alphabet, numbers). To solve the given problem, the current study presents a system which distinguishes different languages by analyzing the form/shape of inserted handwritten characters. The proposed technique has treated the handwritten data as sets of vector units. By analyzing the correlation and directivity of each vector units, a more efficient language distinguishing system has been made possible.

• 한국HCI학회:학술대회논문집
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• 2006.02a
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• pp.1379-1386
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• 2006

전자우편이나 문자 메세지를 이용할 때 겪는 불편함 중 하나는 상대방이나 기계에 정서 정보를 전달하기 어렵다는 점이다. 정서 정보를 메시지에 싣기 위해서는 컴퓨터나 디지털 기기가 정서를 인식하거나 사용자가 정서를 입력해야 한다. 기존의 정서 인식 방법은 생리적, 신체적 측정치를 이용하는 것인데, 이 경우 측정을 위한 별도의 장비가 필요하고 현재 자신의 정서 상태와 다른 정서를 표현할 수 없다는 단점이 있다. 특히 소형 모바일 기기를 이용할 때 다른 측정 장치를 사용하는 것은 더욱 어렵다. 이런 문제를 해결하기 위해 모바일 기기를 사용하는 환경에서 사용자가 원하는 정서를 기계에 입력하기 위해 동작을 이용하려는 연구가 진행되었다(Fargerberg, Stahl, & Hook, 2003). 본 연구에서는 Laban Movement Analysis에서 동작을 구성하는 다섯 요소 중 노력(effort)과 모양(shape) 요소를 재구성하여, 방향성 차원, 무게감 차원, 시간감 차원으로 동작을 구분하고 총 20개의 동작을 선정하였다. 또한 한덕웅과 강혜자(2000)가 수집한 834개 정서 어휘를 평정하여 동작을 통해 표현하고 전달되기 쉬운 정서 어휘 50개를 선택하였다. 최종 실험에서 참가자들은 20개의 동작에 대해 50개의 정서 어휘를 평정하고 데이터는 범주형 주성분분석을 이용하여 분석하였다. 분석 결과 Russell(1980)의 이차원 정서 구조 모형에서 각성 수준 차원은 동작의 무게감과 시간감 차원과 관련이 있는 것으로 나타났다. 강하고 빠른 동작일수록 각성 수준이 높은 정서가 나타났다. 또한 동작의 방향성 차원은 정서의 종류와 관련이 있는 것으로 드러났다. 직선 움직임은 높은 각성 수준의 부정적 정서와, 흔듦 움직임은 불안 및 초조와, 원형 움직임은 즐거운 정서와 관련이 있는 것으로 나타났다. 이는 동작을 통하여 정서 정보를 효과적으로 전달할 수 있음을 보여주었고, 동작과 정서를 연관 짓기 위해 방향성 차원과 무게감 차원 그리고 시간감 차원을 고려할 필요가 있음을 시사한다.

• Journal of the Korea Society of Computer and Information
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• v.25 no.6
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• pp.49-56
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• 2020

The virtual Korean keyboard system is a method of inputting characters by touching a fixed position. This system is very inconvenient for people who have difficulty moving their fingers. To alleviate this problem, this paper proposes an efficient framework that enables keyboard input and handwriting through video and user motion obtained through the RGB camera of the mobile device. To develop this system, we use face recognition to calculate control coordinates from the input video, and develop an interface that can input and combine Hangul using this coordinate value. The control position calculated based on face recognition acts as a pointer to select and transfer the letters on the keyboard, and finally combines the transmitted letters to integrate them to perform the Hangul keyboard function. The result of this paper is an efficient writing system that utilizes face recognition technology, and using this system is expected to improve the communication and special education environment for people with physical disabilities as well as the general public.

• Journal of the Korean Society of Marine Environment & Safety
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• v.21 no.4
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• pp.403-408
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• 2015

A text-based communication system has been developed with a communication function on AIS and display and input function on ECDIS as a way to complement voice communication. It features no linguistic error and is not affected by VHF restrictions on use and noise. The text communication system is designed to use messages for clear intentions and further improves convenience of users by using various UI through software. It works without additional hardware installation and modification and can transmit a sentence by selecting only via Message Banner Interface without keyboard input and furthermore has a advantage to enhance processing speed through its own message coding and decoding. It is determined as the most useful alternative to reduce language limitations and recognition errors of the user and solve the problem of various voice communications on VHF. In addition, it will help to prevent collisions between ships with decrease in VHF use, accurate communication and request of cooperation based on text at heavy traffic areas.