• 한국안전학회지
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• 제13권4호
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• pp.256-263
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• 1998

In this paper, we propose a volume holographic fingerprint recognition system based on optical correlator for personal identification. Optical correlator has high speed and parallel processing characteristics of optics. Matched filters are recorded into a volume hologram that can store data with high density, transfer them with high speed, and select a randomly chosen data element. The multiple reference images of database are prerecorded in a photorefractive crystal in the form of Fourier transform images, simply by passing the image displayed in a spatial light modulator through a Fourier transform lens. The angular multiplexing method for multiple holograms of database can be achieved by rotating the crystal by use of a step motor. Experimental results show that the proposed system can be used for the security verification system.

• Journal of Multimedia Information System
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• 제7권1호
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• pp.41-44
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• 2020

In autonomous driving, object recognition based on machine learning is one of the core software technologies. In particular, the object recognition using deep learning becomes an essential element for autonomous driving software to operate. In this paper, we introduce a drivable area detection method based on Region-based CNN model to support autonomous driving. To effectively detect the drivable area, we used the BDD dataset for model training and demonstrated its effectiveness. As a result, our R-CNN model using BDD datasets showed interesting results in training and testing for detection of drivable areas.

• 융합신호처리학회 학술대회논문집
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• 한국신호처리시스템학회 2001년도 하계 학술대회 논문집(KISPS SUMMER CONFERENCE 2001
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• pp.273-276
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• 2001

본 논문에서는 산업용으로 주로 사용되고 있는 바코드(code 73)글 비전시스템을 이용하여 자동으로 인식할 수 있는 알고리즘을 제안하였다. 제안된 알고리즘은 입력된 바코드 영상에 대해 회전에 관계없이 각도를 자동 추출하여, 모듈 (module)을 구성하는 화소들을 추출한다. 각 모듈에 대해 적응적인 방법으로 바(bar)와 스페이스(space)를 구성하는 엘리먼트(element) 값을 구하고, 심벌 문자들의 엘리먼트 값을 9개의 그룹으로 나누어 바코드 값을 인식한다. 여러 종류의 바코드 영상을 대상으로 모의실험을 수행하여, 제안한 알고리즘의 성능을 검증하였다.

• 전자공학회논문지B
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• 제31B권6호
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• pp.91-103
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• 1994

As CAD systems are introduced in the filed of engineering design, the necessities for automatic drawing input are increased . In this paper, we propose a method for realizing automatic drawing input by separation of text regions and graphic regions, extraction of line vectors from graphic regions, and recognition of circular arcs and circles from line vectors. Sizes of isolated regions, on a drawing are used for separating text regions and graphic regions. Thinning and maximum allowable error method are used to extract line vectors. And geometric structures of line vectors are analyzed to recognize circular arcs and circles. By processing text regions and graphic regions separately, 30~40% of vector information can be reduced. Recognition of circular arcs and circles can increase the utilization of automatic drawing input function.

• International Journal of Railway
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• 제7권4호
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• pp.94-99
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• 2014

Urban railway systems are located under populated areas and are mostly constructed for underground structures which demand high standards of structural safety. However, the damage progression of underground structures is hard to evaluate and damaged underground structures may not effectively stand against successive earthquakes. This study attempts to examine initial damage-stage and to access structural damage condition of the ground structures using Earthquake Damage Monitoring (EDM) system. For actual underground structure, vulnerable damaged member of Ulchiro-3ga station is chosen by finite element analysis using applied artificial earthquake load, and then damage pattern and history of damaged members is obtained from measured acceleration data introduced unsupervised learning recognition. The result showed damage index obtained by damage scenario establishment using acceleration response of selected vulnerable members is useful. Initial damage state is detected for selected vulnerable member according to established damage scenario. Stiffness degrading ratio is increasing whereas the value of reliability interval is decreasing.

• 음성과학
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• 제10권4호
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• pp.167-177
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• 2003

This paper presents a method of building an exceptional pronunciation dictionary for Korean automatic pronunciation generator. An automatic pronunciation generator is an essential element of speech recognition system and a TTS (Text-To-Speech) system. It is composed of a part of regular rules and an exceptional pronunciation dictionary. The exceptional pronunciation dictionary is created by extracting the words which have exceptional pronunciations from text corpus based on the characteristics of the words of exceptional pronunciation through phonological research and text analysis. Thus, the method contributes to improve performance of Korean automatic pronunciation generator as well as the performance of speech recognition system and TTS system.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2018년도 추계학술대회
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• pp.441-443
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• 2018

본 논문은 RGB 영상 이용하여 하지 움직임에 대한 분석을 다룬다. 딥러닝 접근방법인 객체 인식 Segmentation 알고리즘과 자세 검출 알고리즘을 융합한 방법과 BMC(Background Model Challenge)을 활용하여 RGB 영상을 보행 분석 요소로 사용하였다. 본 연구에서 제시한 영상 보행 분석은 보행패턴 인식과 비정상적인 보행 등의 분류를 위한 변수로서 활용할 수 있을 것으로 판단된다.

• 음성과학
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• 제7권4호
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• pp.11-26
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• 2000

In this paper, we propose the HMM with the MIN module. Because initial and re-estimated variance vectors are important elements for performance in HMM recognition systems, we propose a method which compensates for the mismatched statistical feature of training and test data. The MIN module function is a differentiable function similar to the sigmoid function. Unlike a continuous density function, it does not include variance vectors of the data set. The proposed hybrid HMM/MIN module is a unified network in which the observation probability in the HMM is replaced by the MIN module neural network. The parameters in the unified network are re-estimated by the gradient descent method for the Maximum Likelihood (ML) criterion. In estimating parameters, the variance vector is not estimated because there is no variance element in the MIN module function. The experiment was performed to compare the performance of the proposed HMM and the conventional HMM. The experiment measured an isolated number for speaker independent recognition.

• Journal of Information Processing Systems
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• 제14권3호
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• pp.790-800
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• 2018

The simplified neutrosophic set (SNS) is a generalization of fuzzy set that is designed for some practical situations in which each element has truth membership function, indeterminacy membership function and falsity membership function. In this paper, we propose a new method to construct similarity measures of single valued neutrosophic sets (SVNSs) and interval valued neutrosophic sets (IVNSs), respectively. Then we prove that the proposed formulas satisfy the axiomatic definition of the similarity measure. At last, we apply them to pattern recognition under the single valued neutrosophic environment and multi-criteria decision-making problems under the interval valued neutrosophic environment. The results show that our methods are effective and reasonable.

• 한국지능시스템학회논문지
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• 제12권6호
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• pp.517-523
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• 2002

본 논문에서는 자연언어를 이용하는 인간의 학습방법에 기초한 LIBL방법의 실용화를 위하여 음성지시기반학습(VIBL : Voice Instruction Based Learing)을 선박의 조타 시스템, 주기원격제어시스템(MERCS), 윈치기기에 적용하여 항해사의 조타명령과 같은 언어적 지시가 조타수를 경유하여 수행되는 과정을 대체하는 VIBL법을 이용한 조타기, 주기 원격 조종장치, 윈치 기기를 제어하는 시스템을 제안하고자 한다. 구체적인 연구방법으로는 조타수의 적절한 조타조작모델을 퍼지추론 규칙을 이용하여 구현하고, 적절한 의미소 및 평가규칙을 제시한 언어지시 기반 학습방법을 선박의 조타시스템에 적용하여 지시자의 음성언어지시에 보다 효율적으로 응답하는 지능형 조타기 제어 시스템을 구현하고, 지시자의 음성지시를 인식하여 주기 원격 조종 장치와 윈치 기기를 제어하는 시스템을 구현한다. 음성언어지시를 인식하여 텍스트로 변환하기 위한 기법과 퍼지추론을 이용하여 조타수의 경험을 바탕으로 한 조타 조작 모델을 구축하였고, 지능형 조타 시스템을 위한 타각, 방위도달시간, 정상상태의 의미소를 제안하여, 조타수 조작 모델 규칙을 수정하기 위한 평가규칙을 제시하였다. 또한, 구현된 음성인식 선박조종 시뮬레이터에 적용하여 그 유효성을 확인하였다.