• International Journal of Contents
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• 제3권2호
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• pp.1-5
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• 2007

This paper proposes a technique for principal component analysis (PCA) to raise the recognition rate of a front face in a low dimension by hierarchical image and parallel processing structure. The conventional PCA shows a recognition rate of less than 50% in a low dimension (dimensions 1 to 6) when used for facial recognition. In this paper, a face is formed as images of 3 fixed-size levels: the 1st being a region around the nose, the 2nd level a region including the eyes, nose, and mouth, and the 3rd level image is the whole face. PCA of the 3-level images is treated by parallel processing structure, and finally their similarities are combined for high recognition rate in a low dimension. The proposed method under went experimental feasibility study with ORL face database for evaluation of the face recognition function. The experimental demonstration has been done by PCA and the proposed method according to each level. The proposed method showed high recognition of over 50% from dimensions 1 to 6.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권11호
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• pp.5605-5623
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• 2016

We propose a face recognition method that utilizes the LCP face descriptor. The proposed method applies a LoG mask to extract a face contour response, and employs the LCP algorithm to produce a binary pattern representation that ensures high recognition performance even under the changes in illumination, noise, and aging. The proposed LCP algorithm produces excellent noise reduction and efficiency in removing unnecessary information from the face by extracting a face contour response using the LoG mask, whose behavior is similar to the human eye. Majority of reported algorithms search for face contour response information. On the other hand, our proposed LCP algorithm produces results expressing major facial information by applying the threshold to the search area with only 8 bits. However, the LCP algorithm produces results that express major facial information with only 8-bits by applying a threshold value to the search area. Therefore, compared to previous approaches, the LCP algorithm maintains a consistent accuracy under varying circumstances, and produces a high face recognition rate with a relatively small feature vector. The test results indicate that the LCP algorithm produces a higher facial recognition rate than the rate of human visual's recognition capability, and outperforms the existing methods.

• 전자공학회논문지CI
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• 제41권5호
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• pp.33-40
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• 2004

본 논문에서는 웨이블릿 압축을 이용하여 얼굴 데이터베이스를 구축하고, 주성분 분석(Principal Component Analysis : PCA) 알고리듬을 이용하여 얼굴 인식률을 비교한다. 일반적인 얼굴인식 방법은 정규화된 크기를 이용하여 데이터베이스를 구축하고, 얼굴 인식을 한다. 제안된 방법은 정규화된 크기(92×112)의 영상을 웨이블릿 압축으로 1단계, 2단계, 3단계로 변환하고 데이터베이스를 구축한다. 입력 영상도 웨이블릿으로 압축하고 PCA 알고리듬으로 얼굴인식 실험을 하였다 실험을 통하여 제안된 방법은 기존 얼굴영상의 정보를 축소할 뿐만 아니라 처리속도도 향상되었다. 또한 제안된 방법은 원본 영상이 99.05%, 1단계 99.05%, 2단계 98.93%, 3단계 98.54% 정도의 인식률을 보였으며, 대량의 얼굴 데이터베이스를 구축하여 얼굴인식을 하는데 가능함을 보였다.

• 한국콘텐츠학회논문지
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• 제13권9호
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• pp.10-19
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• 2013

본 논문에서는 그래프 패턴 인식을 신속히 처리하기 위한 새로운 자성 센서의 개발과 인식 시스템을 제안하고자 하였다. 그래픽을 입력받아 세션화와 균형화를 수행하는데 있어서 특징점의 사전 처리를 선결 수행함으로써 인식 속도를 증강하고 선처리된 특징점을 이용하여 끝점, 굴곡점, 분기점의 특징점을 별도로 추출하지 않는 방법으로 조사하여 모음이나 자음의 부분패턴의 그래프 사전을 비교하는 간단한 구조해석과 인식을 도모하였다. 본 논문의 성능 비교를 위하여 사용자의 필기체를 사전에 등록 인식하고 입력 필기체를 비교 인식하여 Unicode로 변환시켜 비교한 결과 70%의 초기 인식률에서 누적 인공학습 지능 처리 결과 95%의 이상의 인식률을 보여주고 있다.

• The Journal of the Acoustical Society of Korea
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• 제17권2E호
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• pp.26-30
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• 1998

In this paper, we compose neural network predictive HMM(NNPHMM) to provide the dynamic feature of the speech pattern for the HMM. The NNPHMM is the hybrid network of neura network and the HMM. The NNPHMM trained to predict the future vector, varies each time. It is used instead of the mean vector in the HMM. In the experiment, we compared the recognition abilities of the one hundred Korean syllables according to the variation of hidden layer, state number and prediction orders of the NNPHMM. The hidden layer of NNPHMM increased from 10 dimensions to 30 dimensions, the state number increased from 4 to 6 and the prediction orders increased from 10 dimensions to 30 dimension, the state number increased from 4 to 6 and the prediction orders increased from the second oder to the fourth order. The NNPHMM in the experiment is composed of multi-layer perceptron with one hidden layer and CMHMM. As a result of the experiment, the case of prediction order is the second, the average recognition rate increased 3.5% when the state number is changed from 4 to 5. The case of prediction order is the third, the recognition rate increased 4.0%, and the case of prediction order is fourth, the recognition rate increased 3.2%. But the recognition rate decreased when the state number is changed from 5 to 6.

• 한국임상약학회지
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• 제21권2호
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• pp.66-73
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• 2011

The objective of this study was to evaluate the recognition and performance rates about the safety rules on hazardous drugs among the selected pharmacists. The 160 pharmacists working in 4 general hospitals and in the other 4 institutions specialized in the oncology division were surveyed through mail. Among the 137 respondents to the survey (response rate 85.6%), 111 pharmacists (81%) had recognized the terms of 'hazardous drugs'. In categories of vaccines and hormones, the degrees of the recognition rate were much lower than the cytotoxic medications. It was surveyed that the degree of recognition and performance of safety rules on injectable drugs were higher than the disposal and noninjectable medications. The higher recognition rate of the safety rules made the higher degree of performance. These results were expected to provide the incentive for guidelines on handling hazardous drugs based on Korean healthcare system.

• 한국엔터테인먼트산업학회논문지
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• 제14권8호
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• pp.345-352
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• 2020

본 연구는 요양의료기관 종사자의 감정노동과 진료비 삭감 인식도가 삭감율에 미치는 영향을 알아보기 위해 대한민국의 의료기관 종사자 414명을 대상으로 설문조사를 실시하여 다음과 같은 결과를 도출하였다. 첫째, 인구사회학적 특성에 따른 삭감률 차이를 살펴본 결과 입원 삭감률과 외래 삭감률은 근무형태, 현 병원 근무경력과 허가 병상 수에서 유의한 차이를 보였다. 둘째, 감정노동, 진료비 삭감 인식도와 삭감률의 상관관계를 분석한 결과 감정노동과 외래 삭감률은 정적 상관, 진료비 삭감 인식도과 입원 삭감률은 부적 상관, 진료비 삭감인식도과 외래 삭감률은 부적 상관에 유의한 것으로 나타났다. 셋째, 감정노동은 입원 삭감률에 유의한 정적 영향 미치며, 진료비삭감인식도는 입원 삭감률에 유의한 부적 영향 미치는 것으로 나타났다. 감정노동은 외래 삭감률에 유의한 정적 영향을 미치며, 진료비 삭감인식도는 외래삭감률에 유의한 부적 영향을 미치는 것으로 나타났다.

• The Journal of the Acoustical Society of Korea
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• 제16권2E호
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• pp.55-61
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• 1997

This paper proposes a MSHMM(Multi-Section Hidden Markov Model) recognition method based on Fuzzy Concept, as a method on the speech recognition of speaker-independent. In this recognition method, training data are divided into several section and multi-observation sequences given proper probabilities by fuzzy rule according to order of short distance from MSVQ codebook per each section are obtained. Thereafter, the HMM per each section using this multi-observation sequences is generated, and in case of recognition, a word that has the most highest probability is selected as a recognized word. In this paper, other experiments to compare with the results of these experiments are implemented by the various conventional recognition methods(DP, MSVQ, DMS, general HMM) under the same data. Through results of all-round experiment, it is proved that the proposed MSHMM based on fuzzy concept is superior to DP method, MSVQ method, DMS model and general HMM model in recognition rate and computational time, and does not decreases recognition rate as 92.91% in spite of increment of speaker number.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 추계종합학술대회 논문집(3)
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• pp.121-124
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• 2000

In this paper, we propose a pen gesture recognition system for user interface in multimedia terminal which requires fast processing time and high recognition rate. It is realtime and interaction system between graphic and text module. Text editing in recognition system is performed by pen gesture in graphic module or direct editing in text module, and has all 14 editing functions. The pen gesture recognition is performed by searching classification features that extracted from input strokes at pen gesture model. The pen gesture model has been constructed by classification features, ie, cross number, direction change, direction code number, position relation, distance ratio information about defined 15 types. The proposed recognition system has obtained 98% correct recognition rate and 30msec average processing time in a recognition experiment.

• 음성과학
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• 제13권4호
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• pp.177-186
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• 2006

In an effort to enhance the quality of feature vector classification and thereby reduce the recognition error rate of the speaker-independent speech recognition, we employ the Mahalanobis distance in the calculation of the similarity measure between feature vectors. It is assumed that the metric matrix of the Mahalanobis distance be diagonal for the sake of cost reduction in memory and time of calculation. We propose that the diagonal elements be given in terms of the variations of the feature vector components. Geometrically, this prescription tends to redistribute the set of data in the shape of a hypersphere in the feature vector space. The idea is applied to the speech recognition by hidden Markov model with fuzzy vector quantization. The result shows that the recognition is improved by an appropriate choice of the relevant adjustable parameter. The Viterbi score difference of the two winners in the recognition test shows that the general behavior is in accord with that of the recognition error rate.