• Title/Summary/Keyword: 분류계수

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People Counting Method using Moving and Static Points of Interest (동적 및 정적 관심점을 이용하는 사람 계수 기법)

  • Gil, Jong In;Mahmoudpour, Saeed;Whang, Whan-Kyu;Kim, Manbae
    • Journal of Broadcast Engineering
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    • v.22 no.1
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    • pp.70-77
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    • 2017
  • Among available people counting methods, map-based approaches based on moving interest points have shown good performance. However, the stationary people counting is challenging in such methods since all static points of interest are considered as background. To include stationary people in counting, it is needed to discriminate between the static points of stationary people and the background region. In this paper, we propose a people counting method based on using both moving and static points. The proposed method separates the moving and static points by motion information. Then, the static points of the stationary people are classified using foreground mask processing and point pattern analysis. The experimental results reveal that the proposed method provides more accurate count estimation by including stationary people. Also, the background updating is enabled to solve the static point misclassification problem due to background changes.

A study on the lubrication characteristics of Liquid Crystals (액정의 윤활특성에 관한 연구)

  • 민지홍;임윤철
    • Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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    • 1992.06a
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    • pp.60-65
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    • 1992
  • 액정은 합성에 의해서 만들어지는 고분자 화합물로서 액체와 고체결정의 중간적인 특성을 갖는 물질이다. 따라서 액체와 같이 점도를 갖고 유동하며 고체와 같이 외부하중에 대하여는 탄성변형을 하므로 일반 윤활유보다 월등한 윤활특성이 기대된다. 액정은 분자배열에 따라 smectics, cholesterics, Nematics의 세종류로 나뉘어지며 Smectics는 다시 Smectic A, Smectic C등으로 분류되며 관심대상은 Smectic A이다. 본 연구에서는 평판 슬라이더 베어링의 간극에 액정층이 형성되어있을때 액정의 탄성계수, 침투계수 및 벌어짐계수가 베어링부하, 액정층의 유동현상등에 미치는 영향을 비선형 유한 요소법을 사용하여 해석하고 레이놀즈 이론해와 비교하였다.

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Speech Recognition for Vowel Detection using by Cepstrum Coefficients (켑스트럼 계수에 의한 모음검출을 위한 음성인식)

  • Choi, Jae-Seung
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2011.10a
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    • pp.613-615
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    • 2011
  • 본 논문에서는 켑스트럼 계수를 이용하여 음성인식을 하는 알고리즘을 제안한다. 본 논문에서 제안하는 방법은 사람이 발성한 음성을 두 영역의 켑스트럼 계수로 분리한 후에, 신경회로망을 사용하여 음성인식을 하는 방법이다. 본 논문에서 제안하는 신경회로망은 오차가 거의 없어지는 일정 기간 동안 네트워크를 학습시킨 후에 신경회로망의 학습 데이터와는 다른 새로운 음성이 신경회로망에 입력된 경우에 대하여 각 음성 구간에서 분류가 가능한 모음검출을 위한 음성인식 시스템을 제안한다.

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Classification of ECG arrhythmia using Discrete Cosine Transform, Discrete Wavelet Transform and Neural Network (DCT, DWT와 신경망을 이용한 심전도 부정맥 분류)

  • Yoon, Seok-Joo;Kim, Gwang-Jun;Jang, Chang-Soo
    • The Journal of the Korea institute of electronic communication sciences
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    • v.7 no.4
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    • pp.727-732
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    • 2012
  • This paper presents an approach to classify normal and arrhythmia from the MIT-BIH Arrhythmia Database using Discrete Cosine Transform(DCT), Discrete Wavelet Transform(DWT) and neural network. In the first step, Discrete Cosine Transform is used to obtain the representative 15 coefficients for input features of neural network. In the second step, Discrete Wavelet Transform are used to extract maximum value, minimum value, mean value, variance, and standard deviation of detail coefficients. Neural network classifies normal and arrhythmia beats using 55 numbers of input features, and then the accuracy rate is 98.8%.

Analysis of Co-relationship between Rock Mass Grade by RMR and Estimation Method of Rock Deformation Modulus by Suggested Formulas (RMR 분류에 의한 암반등급과 제안식에 의한 암반 변형계수 추정기법의 상관관계 분석)

  • Do, Jongnam;Lee, Jinkyu;Chun, Byungsik
    • Journal of the Korean GEO-environmental Society
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    • v.13 no.4
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    • pp.13-26
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    • 2012
  • The deformation modulus of rock masses is a very important design factor for the computation of stability of tunnels and their support systems. Several empirical formulas to estimate the deformation modulus using simple rock classification methods such as RQD or RMR are widely used because field tests to evaluate the deformation modulus are very expensive and time consuming work. However, these formulas can be depended on experiences from the characteristics of local sites in each country. So it is possible that there might be limitations to estimate appropriate deformation modulus in South Korea using the empirical formulas. Therefore, in this study, the applicability of empirical formulas was analyzed by comparing estimated value with the measured value from eight sites in South Korea. The results show that the estimated value based on the empirical formulas partially have tendency to overestimate. Especially, in case of sedimentary rocks, it was too difficult to apply to the empirical formulas because there was no relation ship between estimated value and measured value. For these reasons, additional data from many tests and accurate analyses are necessary to evaluate the estimation method for the deformation modulus considering the local characteristics of rock masses.

Domain Searching method using DCT-coefficient for Fractal Image Compression (Fractal 압축방법을 위한 DCT 계수를 사용한 도메인 탐색 방법)

  • Suh, Ki-Bum;Chong, Jong-Wha
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.37 no.2
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    • pp.28-38
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    • 2000
  • This paper proposes a fractal compression method using the domain classification and local searching, which utilize DCT coefficient characteristic Generally, the fractal Image encoding method has a time consuming process to search a domain to be matched with range block In order to reduce computation complexity, the domain and range regions are respectively classified into 4 category by using the characteristics of DCT coefficients and each range region is encoded by a method suitable for the property of its category Since the bit amount of the compressed image depends on the number of range blocks, the matching of domain block and range block is induced on the large range block by using local search, so that compression ratio is increased by reducing the number of range block In the local search, the searching complexity is reduced by determining the direction and distance of searching using the characteristics of DCT coefficients The experimental results shows that the proposed algorithm have 1 dB higher PSNR and 0 806 higher compression ratio than previous algorithm.

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Learning-Based People Counting System Using an IR-UWB Radar Sensor (IR-UWB 레이다 센서를 이용한 학습 기반 인원 계수 추정 시스템)

  • Choi, Jae-Ho;Kim, Ji-Eun;Kim, Kyung-Tae
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.30 no.1
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    • pp.28-37
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    • 2019
  • In this paper, we propose a real-time system for counting people. The proposed system uses an impulse radio ultra-wideband(IR-UWB) radar to estimate the number of people in a given location. The proposed system uses learning-based classification methods to count people more accurately. In other words, a feature vector database is constructed by exploiting the pattern of reflected signals, which depends on the number of people. Subsequently, a classifier is trained using this database. When a newly received signal data is acquired, the system automatically counts people using the pre-trained classifier. We validated the effectiveness of the proposed algorithm by presenting the results of real-time estimation of the number of people changing from 0 to 10 in an indoor environment.

Classification of the PVC Using The Fuzzy-ART Network Based on Wavelet Coefficient (웨이브렛 계수에 근거한 Fuzzy-ART 네트워크를 이용한 PVC 분류)

  • Park, K. L;Lee, K. J.;lee, Y. S.;Yoon, H. R.
    • Journal of Biomedical Engineering Research
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    • v.20 no.4
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    • pp.435-442
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    • 1999
  • A fuzzy-ART(adaptive resonance theory) network for the PVC(premature ventricular contraction) classification using wavelet coefficient is designed. This network consists of the feature extraction and learning of the fuzzy-ART network. In the first step, we have detected the QRS from the ECG signal in order to set the threshold range for feature extraction and the detected QRS was divided into several frequency bands by wavelet transformation using Haar wavelet. Among the low-frequency bands, only the 6th coefficient(D6) are selected as the input feature. After that, the fuzzy-ART network for classification of the PVC is learned by using input feature which comprises of binary data converted by applying threshold to D6. The MIT/BIH database including the PVC is used for the evaluation. The designed fuzzy-ART network showed the PVC classification ratio of 96.52%.

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Analysis of Acquaintance Relations Between Parameters of RMR and Q Rock Mass Classification System (RMR 및 Q 암반분류법의 평가 요소간 친숙도 관계 분석)

  • Synn, Joong-Ho;Park, Chul-Whan;SunWoo, Choon
    • Tunnel and Underground Space
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    • v.18 no.6
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    • pp.408-417
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    • 2008
  • Rock mass classification methods such as RMR and Q system have different characteristics each other in parameters considered and applications, and so it is very important to prescribe the relationship between parameters for the analysis of correlativity of these methods. With the Held data of RMR and Q estimation in road construction sites, the acquaintance relations between RMR and Q of rock mass classifications are analyzed. The correlation equations between parameters of RMR and Q, matrix of correlation coefficients and the generalized form of acquaintance relation matrix are derived. This acquaintance relation matrix can be further extended to the form of generalized acquaintance relation network, and could be used to analyze the correlativity and to enhance the utility of common rock mass classification methods.