• 한국통신학회논문지
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• 제15권7호
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• pp.618-627
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• 1990

본 논문은 한글문자 인식을 위하여 새로운 접촉소자의 분리 및 자획연결 특징추출 알고리즘을 제안하였다. 자소 접촉특징을 분석하여 자소접촉 형태별로 분류하고 자획연결특징 추출, 접촉자소의 분리, 문자형식 분류를 시행한다. 분리된 자소로부터 설정된 표준패턴으로 정규화하고 자소별 굴곡특징의 상대위치값으로 부터의 특징을 입력패턴으로 신경망을 이용하여 인식 실험을 하였다. 여기에서의 학습은 BEP 알고리즘을 이용하였다. 접촉자소의 분리, 형식분리, 자획연결특징 추출 및 인식 실험에서 제안된 알고리즘이 좋은 결과를 나타내었다.

• 방사선산업학회지
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• 제17권1호
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• pp.11-17
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• 2023

Waste generated during the dismantling of nuclear power plants is not only diverse in types such as metal, concrete, soil, but also in a large amount, requiring systematic and efficient management. It is very important to quickly and accurately measure radioactive contamination of wastes generated simultaneously at the decommissioning site, classify them by level, and make decisions so that they can be disposed of in accordance with related laws and regulations. In this paper, for the technical and economic aspects of recycling of radioactive metal waste generated during the dismantling of nuclear power plants, we propose a management system that can measure the radioactive contamination by shape of metal waste at the decommissioning site and automatically classify it according to the presence or absence of contamination. Accordingly, a system for collecting information on metal samples such as weight measurement and shape acquisition of metal waste, measurement of radioactive contamination and identification of nuclides, and an automatic classification system according to radioactivity measurement results were described.

• 한국항행학회논문지
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• 제16권1호
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• pp.151-157
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• 2012

최근 영상처리기술과 컴퓨터과학의 발달로 연령변화에 따른 얼굴형상 분류 방법은 일반적인 주제가 되었다. 사람의 연령별 얼굴분류는 생물학적 유전자와 오랜 생활의 식습관으로 인하여 얼굴 형상이 변하기 때문에 통계적 형상만으로 예측하기란 쉽지 않다. 본 논문에서는 Gobor 특징과 fuzzy SVM 기법을 이용하여 연령대별 얼굴분류 기법을 제안하였다. Gabor 웨이블릿 함수는 얼굴의 특징벡터를 구하기 위하여 사용되고 연령대별 얼굴형상 구분이 애매모호한 문제를 해결하기 위해 fuzzy SVM 기법을 이용하여 연령별 소속 함수를 정의하였다. 제안한 방법으로 연령별 소속함수에 따른 얼굴 분류 실험을 수행하였고 제안한 방법의 타당성을 확인하였다.

• 디지털융복합연구
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• 제14권2호
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• pp.519-527
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• 2016

이 연구는 BMI 분류기준과 9점-신체상평정척도 분류기준의 일치도를 조사하여 현장적용의 유용성을 확인하고, 여대생들이 체형에 대해 실제로 인식하고 정도를 파악하여 체형인식의 왜곡에 대한 올바른 정보와 비만의 기준에 대한 정보 제공에 목적이 있다. BMI 분류기준과 신체상평정척도 분류기준의 일치도, 그리고 여대생의 BMI에 따른 신체상 인식 정도를 알아보기 위하여 교차분석, Spearman의 등위차상관계수 및 카파통계량을 산출하였다. 분석결과 일반 여자대학생이 판정한 신체상 평정척도 분류기준과 BMI 분류기준은 통계적으로 ${\rho}=.719$(p<.001)로 높은 상관과 ${\kappa}=.506$(p<.001)로 보통 수준의 일치도를 나타냈다. 이러한 결과를 바탕으로 차후 신체상과 관련하여 인종의 특성에 따른 크기와 형태를 조정할 필요가 있으며 인구통계학적 특성이 다르거나 비만도가 높은 대상자를 선별하여 그들의 체형인식과 심리적인 측면에 관한 추가적인 연구가 필요하다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 Proceedings of the Korea Automatic Control Conference, 11th (KACC); Pohang, Korea; 24-26 Oct. 1996
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• pp.430-433
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• 1996

The shape of an object plays a very important role in pattern analysis and classification. Roughly, the researches on this topic can be classified into three fields, i.e. (i) edge detection, (ii) dominant points extraction, and (iii) shape recognition and classification. Many works have been done in these three fields. However, it is very seldom to see the research that discusses the connection relationship of objects. This problem is very important in robot assembly systems. Therefore, here we focus on this problem and discuss how to recover the connection relationship of planar objects. Our method is based on the partial curve identification algorithm. The experiment results show the efficiency and validity of this method.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2003년도 춘계학술대회
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• pp.304-309
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• 2003

In this study, natural flaws in welding parts are classified using the signal pattern classification method. The storage digital oscilloscope including FFT function and enveloped waveform generator is used and the signal pattern recognition procedure is made up the digital signal processing, feature extraction, feature selection and classifier design. It is composed with and discussed using the distance classifier that is based on euclidean distance the empirical Bayesian classifier. Feature extraction is performed using the class-mean scatter criteria. The signal pattern classification method is applied to the signal pattern recognition of natural flaws.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송공학회 2015년도 하계학술대회
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• pp.516-517
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• 2015

The automatic traffic sign detection and recognition has been one of the highly researched and an important component of advanced driver assistance systems (ADAS). They are designed especially to warn the drivers of imminent dangers such as sharp curves, under construction zone, etc. This paper presents a traffic sign recognition (TSR) system using morphological operations and multiple descriptors. The TSR system is realized in three stages: segmentation, shape classification and recognition stage. The system is designed to attain maximum accuracy at the segmentation stage with the inclusion of morphological operations and boost the computation time at the shape classification stage using MB-LBP descriptor. The proposed system is tested on the German traffic sign recognition benchmark (GTSRB) and on Korean traffic sign dataset.

• 대한의용생체공학회:학술대회논문집
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• 대한의용생체공학회 1998년도 추계학술대회
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• pp.263-264
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• 1998

In this paper, we present the result of feature points recognition and classification of radial pulse by the shape of pulse wave. And we analyze radial pulse in frequency domain. The recognition algorithm use the method which runs in parallel with both the data of ECG and differential pulse simultaneously to recognize the feature points. Also fie specified 3-time elements of pulse wave as main parameters for diagnosis and measured them by execution of algorithm, then we classify the shape of radial pulse by existence and position of feature points. lastly we execute frequency analysis on the feature points and get the power spectrum of radial pulse.

• 제어로봇시스템학회논문지
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• 제20권6호
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• pp.593-598
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• 2014

Hand gesture recognition based on vision is a challenging task in human-robot interaction. The sign language of finger spelling alphabets has been tested as a kind of hand gesture. In this paper, we test hand gesture recognition by detecting the contour shape and orientation of hand with visual image. The method has three stages, the first stage of finding hand component separated from the background image, the second stage of extracting the contour feature over the hand component and the last stage of comparing the feature with the reference features in the database. Here, finger spelling alphabets are used to verify the performance of our system and our method shows good performance to discriminate finger alphabets.

• 한국CDE학회논문집
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• 제8권2호
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• pp.122-132
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• 2003

STEP AP218 has a standard schema to represent the structural model of a midship section. While it helps to exchange ship structural models among heterogeneous automation systems, most shipyards and classification societies still exchange information using 2D paper drawings. We propose a feature parameter input method to generate a 3D STEP model of a ship structure from 2D drawings. We have analyzed the ship structure information contained in 2D drawings and have defined a data model to express the contents of the drawing. We also developed a QUI for the feature parameter input. To translate 2D information extracted from the drawing into a STEP AP2l8 model, we have developed a shape generation library, and generated the 3D ship model through this library. The generated 3D STEP model of a ship structure can be used to exchange information between design departments in a shipyard as well as between classification societies and shipyards.