• Title/Summary/Keyword: 변곡점추출

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Optimum Design of Natural Observation Filter for Detection of Inflection Point of Time Series Data (시계열 데이터의 변곡점 검출을 위한 자연관측필터의 최적 설계)

  • Kim, Tae-Soo;Chun, Joong-Chang
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • v.9 no.1
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    • pp.635-638
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    • 2005
  • The curve shape of the time fluctuation extracted from the electromagnetic signals is very complex. Thus it is important to decide exactly the signal property such as the inflection point for the observed signal. Usually filters elaborately designed are used to detect the signal characteristics. When the noise is added to the signal, the inflection point can be detected using the observation filter. In this paper we propose the design method for a natural observation filter with optimal filter order to extract a definite inflection point for the case of signals with the mixed noise.

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Algorithm of the Detection of the Feature points using distributed feature points of the Second Derivative of Photoplethysmogram waveform (이차 미분 맥파의 변곡점 분포를 이용한 특징점 추출 알고리즘)

  • Kim, Pan-Ki;Ahn, Chang-Beom
    • Proceedings of the KIEE Conference
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    • 2009.07a
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    • pp.1988_1989
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    • 2009
  • 본 논문은 이차 미분 맥파(SDPTG, Second Derivation of Photoplethysmogram)를 측정하여 이차 미분 맥파의 5개의 특징점을 검출하는 방법에 대한 내용을 기술한다. 본 논문에서는 측정된 신호의 신호대 잡음비(SNR)을 높이는 방법과 기존의 미분을 이용한 변곡점 추출의 한계적인 부분, 그리고 본 논문에서 제안하는 이차 미분 맥파의 특징점의 분포를 이용한 특징점 추출 알고리즘에 대해서 설명한다.

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Detection of Inflection Point of Waveform by Wavelet Threshold Denoising (웨이브릿 임계치 잡음제거에 의한 파형의 변곡점 검출)

  • Kim, Tae-Soo
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.13 no.10
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    • pp.2205-2210
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    • 2009
  • In this paper, the proposed method is a denoising technology by tangent curve interpolation of zero points. The problem of the hard threshold method is improved by the proposed method. The quantity of time fluctuation of the electromagnetic signal as the quantity of electric fluctuation of the natural world or the curve of motion waveform of the fast movement of human extracted using virtual reality is, in fact, complex. Therefore it is important to decide exactly the signal properties as the inflection point for observation signal. In particular, it is necessary to extract the properties after denoising, since the measurement signal of the natural world include some noises. It shows that the noise of the inflection point signal with noise II, noise factor 5, is eliminated by the proposed method, and the result of SNR for the signal is improved 3.4dB than that by the conventional hard threshold.

Detection of Inflection Point of Waveform Using Wavelet Thresholding and Natural Observation Filter (웨이브릿 임계치와 자연관측필터를 이용한 파형의 변곡점 검출)

  • Kim, Tae-Soo
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.42 no.4 s.304
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    • pp.127-132
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    • 2005
  • The curve of motion indicated to waveform of the fast movement of human extracted using virtual reality or the quantity of time fluctuation of the electromagnetic signal as the quantity of electric fluctuation of the atmosphere is complex. It is important to decide exactly the signal property as the inflection point for the observation signal. When the signal is mixed by noise signal, the traditional method is difficult to detect the inflection point. In this paper the noisy signal is eliminated by wavelet thresholding method and the filter using natural observation theorem is applied. It shows that the inflection point of the signal waveform can be detected exactly.

Three-Dimensional Direction Code Patterns for Hand Gesture Recognition (손동작인식을 위한 3차원 방향 코드 패턴)

  • Park, Jung-Hoo;Kim, Young-Ju
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2013.07a
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    • pp.21-22
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    • 2013
  • 논문에서는 제스처 인식을 하기 위해 필요한 특징 값을 3차원 방향 코드로 구현한 특징 패턴을 검출하는 방법을 제안한다. 검출된 데이터 좌표끼리 직선을 만들고 직선들의 사이각의 합 연산을 이용해서 특징 변곡점을 추출한다. 추출된 변곡점끼리 직선을 생성한 후, 8방향 코드와 깊이 값을 병합시킨 24방향 코드를 맵핑 시켜준다. 맵핑된 방향 코드들을 한 패턴으로 생성한다. 생성된 패턴에서 인식에 불필요한 방향 노이즈를 제거하기 위해 특정 규칙을 적용한 필터링을 적용하여 필터링된 패턴을 추출하게 된다. '배너코드를 이용한 8방향 패턴'과 비교해서 더 효과적인 패턴이 추출됨을 확인하였다.

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Fundamental Frequency Estimation of Voiced Speech Signals Based on the Inflection Point Detection (변곡점 검출에 기반한 음성의 기본 주파수 추정)

  • Byeonggwan Iem
    • Journal of IKEEE
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    • v.27 no.4
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    • pp.472-476
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    • 2023
  • Fundamental frequency/pitch period are major characteristics of speech signals. They are used in many speech applications like speech coding, speech recognition, speaker identification, and so on. In this paper, some of inflection points are used to estimate the pitch which is the inverse of the fundamental frequency. The inflection points are defined as points where local maxima, local minima or the slope changes occur. The speech signal is preprocessed to remove unnecessary inflection points due to the high frequency components using a low pass filter. Only the inflection points from local maxima are used to get the pitch period. While the existing pitch estimation methods process speech signals in blockwise, the proposed method detects the inflection points in sample and produces the pitch period/fundamental frequency estimates along the time. Computer simulation shows the usefulness of the proposed method as a fundamental frequency estimator.

Online Signature Verification using Extreme Points and Writer-dependent Features (변곡점과 필자고유특징을 이용한 온라인 서명 인증)

  • Son, Ki-Hyoung;Park, Jae-Hyun;Cha, Eui-Young
    • Journal of Korea Multimedia Society
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    • v.10 no.9
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    • pp.1220-1228
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    • 2007
  • This paper presents a new system for online signature verification, approaching for finding gaps between a point-to-point matching and a segment-to-segment matching. Each matching algorithm has been separately used in previous studies. Various features with respect to each matching algorithm have been extracted for solving two-class classification problem. We combined advantages of the two algorithms to implement an efficient system for online signature verification. In the proposed method, extreme feints are used to extract writer-dependent features. In addition, using the writer-dependent features proves to be more adaptive than using writer-independent features in terms of efficiency of classification and verification in this paper.

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Instantaneous Frequency Estimation of AM-FM Signals using the Inflection Point Detection (변곡점 검출을 이용한 AM-FM 신호의 순간주파수 추정)

  • Iem, Byeong-Gwan
    • Journal of IKEEE
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    • v.24 no.4
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    • pp.1081-1085
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    • 2020
  • Instantaneous frequencies (IF) of the AM-FM signal is estimated based on the inflection point detection (IPD) method. Local maxima/minima are detected using the IPD, and they are exploited to find the IF of AM and FM components, respectively. The envelope of the maxima/minima is obtained to estimate the IF of the AM part. And the distance between neighboring maxima (or minima) is used to estimate the IF of the FM component. Computer simulation shows that the proposed method properly estimates the IF of the AM and FM when the signal has fixed frequencies for both parts. In the case of the time-varying IF of the FM part, the estimated IF shows some deviation from the true IF due to the rough sampling effect of the maximum/minimum points. Thus, the post-processing such as the lowpass filtering of the estimated IF is required to refine the resulting IF estimation.

A Study on the salient points detection and object representation for object matching (물체 정합을 위한 특징점 추출 및 물체 표현에 관한 연구)

  • Park, Jeong-Min;Sohn, Kwang-Hoon;Huh, Young
    • Journal of the Korean Institute of Telematics and Electronics S
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    • v.35S no.6
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    • pp.101-108
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    • 1998
  • An efficient approach to recognize occluded objects is to detect a number of essential features on the boundary of the unknown shape. The salient points including corner points, tangential points and inflection points are detected by the relation of neighboring pixels of each pixel on the boundaries. Corner points are usually detected in the curvature function and tangential points and inflection points are detected by median filtering the curvature function to avoid the effect of quantization noise as corner points is not sufficient to represent an object with lines and arcs. Then, these salient points are used as features for object matching. Discrete Hopfield Neural Network is used for object matching. Experimental results show that the matching result using salient points is better than those of using corner points only when an object consists of lines and arcs.

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A Variable Data Rate Speech Coding Technique Based on the Inflection Point Detection of Speech (음성의 변곡점 추출 및 전송에 기반한 가변 데이터율 음성 부호화 기법)

  • Iem, Byeong-Gwan
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.62 no.4
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    • pp.562-565
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    • 2013
  • A new variable rate speech coding technique is proposed. The method is based on the observation that the speech signal approximately looks linear for a very short period of time. The information transmitted is the location and data value of inflection points. If the distance between the inflection points is large, the mid point location and its data value are also delivered. Thus, the encoder transmits both the location and the data value for the inflection samples, but the location only for the non-inflection points. The location information is expressed using one bit for each sample, 0 for non-inflection and 1 for inflection point. At the receiver, using the interpolation, the decoder estimates the untransmitted sample values for non-inflection locations from the received sample values for the inflection samples. With 50 % of computational cost of the existing CVSD delta modulation, the proposed method is expected to achieve the data rate of 36 to 38 kbps and the SNR of 10 to 13 dB.