• Title/Summary/Keyword: Peak 임계값

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Accuracy Improvement Methode of Step Count Detection Using Variable Amplitude Threshold (가변 진폭 임계값을 이용한 걸음수 검출 정확도 향상 기법)

  • Ryu, Uk Jae;Kim, En Tae;An, Kyung Ho;Chang, Yun Seok
    • KIPS Transactions on Computer and Communication Systems
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    • v.2 no.6
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    • pp.257-264
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    • 2013
  • In this study, we have designed the variable amplitude threshold algorithm that can enhance the accuracy of step count using variable amplitude. This algorithm converts the x, y, z sensor values into a single energy value($E_t$) by using SVM(Signal Vector Magnitude) algorithm and can pick step count out over 99% of accuracy through the peak data detection algorithm and fixed peak threshold. To prove the results, We made the noise filtering with the fixed amplitude threshold from the amplitude of energy value that found out the detection error was increasing, and it's the key idea of the variable amplitude threshold that can be adapted on the continuous data evaluation. The experiment results shows that the variable amplitude threshold algorithm can improve the average step count accuracy up to 98.9% at 10 Hz sampling rate and 99.6% at 20Hz sampling rate.

Noise-robust electrocardiogram R-peak detection with adaptive filter and variable threshold (적응형 필터와 가변 임계값을 적용하여 잡음에 강인한 심전도 R-피크 검출)

  • Rahman, MD Saifur;Choi, Chul-Hyung;Kim, Si-Kyung;Park, In-Deok;Kim, Young-Pil
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.18 no.12
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    • pp.126-134
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    • 2017
  • There have been numerous studies on extracting the R-peak from electrocardiogram (ECG) signals. However, most of the detection methods are complicated to implement in a real-time portable electrocardiograph device and have the disadvantage of requiring a large amount of calculations. R-peak detection requires pre-processing and post-processing related to baseline drift and the removal of noise from the commercial power supply for ECG data. An adaptive filter technique is widely used for R-peak detection, but the R-peak value cannot be detected when the input is lower than a threshold value. Moreover, there is a problem in detecting the P-peak and T-peak values due to the derivation of an erroneous threshold value as a result of noise. We propose a robust R-peak detection algorithm with low complexity and simple computation to solve these problems. The proposed scheme removes the baseline drift in ECG signals using an adaptive filter to solve the problems involved in threshold extraction. We also propose a technique to extract the appropriate threshold value automatically using the minimum and maximum values of the filtered ECG signal. To detect the R-peak from the ECG signal, we propose a threshold neighborhood search technique. Through experiments, we confirmed the improvement of the R-peak detection accuracy of the proposed method and achieved a detection speed that is suitable for a mobile system by reducing the amount of calculation. The experimental results show that the heart rate detection accuracy and sensitivity were very high (about 100%).

Multi-thresholds Selection Based on Plane Curves (평면 곡선에 기반한 다중 임계값 결정)

  • Duan, Na;Seo, Suk-T.;Park, Hye-G.;Kwon, Soon-H.
    • Journal of the Korean Institute of Intelligent Systems
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    • v.20 no.2
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    • pp.279-284
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    • 2010
  • The plane curve approach which was proposed by Boukharouba et. al. is a multi-threshold selection method through searching peak-valley based on histogram cumulative distribution function. However the method is required to select parameters to compose plane curve, and the shape of plane curve is affected according to parameters. Therefore detection of peak-valley is effected by parameters. In this paper, we propose an entropy maximizing-based method to select optimal plane curve parameters, and propose a multi-thresholding method based on the selected parameters. The effectiveness of the proposed method is demonstrated by multi-thresholding experiments on various images and comparison with other conventional thresholding methods based on histogram.

An Enhanced Step Detection Algorithm with Threshold Function under Low Sampling Rate (낮은 샘플링 주파수에서 임계 함수를 사용한 개선된 걸음 검출 알고리즘)

  • Kim, Boyeon;Chang, Yunseok
    • KIPS Transactions on Computer and Communication Systems
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    • v.4 no.2
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    • pp.57-64
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    • 2015
  • At the case of peak threshold algorithm, 3-axes data should sample step data over 20 Hz to get sufficient accuracy. But most of the digital sensors like 3-axes accelerometer have very low sampling rate caused by low data communication speed on limited SPI or $I^2C$ bandwidth of the low-cost MPU for ubiquitous devices. If the data transfer rate of the 3-axes accelerometer is getting slow, the sampling rate also slows down and it finally degrades the data accuracy. In this study, we proved there is a distinct functional relation between the sampling rate and threshold on the peak threshold step detection algorithm under the 20Hz frequency, and made a threshold function through the experiments. As a result of experiments, when we apply threshold value from the threshold function instead of fixed threshold value, the step detection error rate can be lessen about 1.2% or under. Therefore, we can suggest a peak threshold based new step detection algorithm with threshold function and it can enhance the accuracy of step detection and step count. This algorithm not only can be applied on a digital step counter design, but also can be adopted any other low-cost ubiquitous sensor devices subjected on low sampling rate.

A Selection of Threshold for the Generalized Hough Transform: A Probabilistic Approach (일반화된 허프변환의 임계값 선택을 위한 확률적 접근방식)

  • Chang, Ji Y.
    • Journal of the Institute of Electronics and Information Engineers
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    • v.51 no.1
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    • pp.161-171
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    • 2014
  • When the Hough transform is applied to identify an instance of a given model, the output is typically a histogram of votes cast by a set of image features into a parameter space. The next step is to threshold the histogram of counts to hypothesize a given match. The question is "What is a reasonable choice of the threshold?" In a standard implementation of the Hough transform, the threshold is selected heuristically, e.g., some fraction of the highest cell count. Setting the threshold too low can give rise to a false alarm of a given shape(Type I error). On the other hand, setting the threshold too high can result in mis-detection of a given shape(Type II error). In this paper, we derive two conditional probability functions of cell counts in the accumulator array of the generalized Hough transform(GHough), that can be used to select a scientific threshold at the peak detection stage of the Ghough.

A Study on the Critical Duration of Design Rainfall in Midsize Catchment (중규모 하천유역에서 설계강우의 임계지속기간에 관한 연구)

  • Park, Jong-Young;Shin, Chang-Dong;Lee, Jung-Sik
    • Journal of Korea Water Resources Association
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    • v.37 no.9
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    • pp.695-706
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    • 2004
  • This study is to propose the temporal pattern of design rainfall which causes maximum peak discharge, and to analyze the relation of catchment characteristics and critical durations for gauged midsize catchment. Hydrologic analysis has done over the 44 midsize catchments with 50-5,000$\textrm{km}^2$. The type of temporal pattern of design rainfall which causes maximum peak discharge has resulted in Huff's 4 quartile distribution method for effective rainfall(AMC III) The peak discharges of 24hr rainfall duration are similar to those of critical duration for 50-600$\textrm{km}^2$, and the peak discharges of 48hr rainfall duration are similar to those of critical duration for 600-5,000$\textrm{km}^2$. Therefore, if the proper rainfall intensity formula is selected, 24hr or 48hr rainfall duration may be regarded as the critical duration of midsize catchment. A simple regression equation is derived by using a catchment area and critical duration with high correlation for the case of effective rainfall(AMC III). Therefore, it can be used to determine the critical duration of ungauged catchment with 50-5,000$\textrm{km}^2$. Also, dimensionless regression equation is derived by using characteristic values of unit hydrograph.

Speckle Noise Reduction in SAR Images using Wavelet Transform (SAR 영상에서 웨이블렛 변환을 이용한 스펙클 잡음제거 방법)

  • Lim, Dong-Hoon
    • Journal of the Korea Society of Computer and Information
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    • v.12 no.3
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    • pp.123-130
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    • 2007
  • It is difficult to analyse images because of multiplicative characteristics of speckle noises in SAR images. In this paper. wavelet transform is proposed for restoring SAR images corrupted by speckle noise. The multiplicative noise is transformed into a form of additive noise and then the additive noise is denoised using wavelet thresholding selections such as VisuShrink, SureShrink, BayesShrink and modified BayesShrink. Experimental results on several test images show that the modified BayesShrink yields significantly superior image quality and better Peak Signal to Noise Ratio(PSNR).

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Automatic Defect Detection and Classification Using PCA and QDA in Aircraft Composite Materials (주성분 분석과 이차 판별 분석 기법을 이용한 항공기 복합재료에서의 자동 결함 검출 및 분류)

  • Kim, Young-Bum;Shin, Duk-Ha;Hwang, Seung-Jun;Baek, Joong-Hwan
    • Journal of Advanced Navigation Technology
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    • v.18 no.4
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    • pp.304-311
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    • 2014
  • In this paper, we propose a ultra sound inspection technique for automatic defect detection and classification in aircraft composite materials. Using local maximum values of ultra sound wave, we choose peak values for defect detection. Distance data among peak values are used to construct histogram and to determine surface and back-wall echo from the floor of composite materials. C-scan image is then composed through this method. A threshold value is determined by average and variance of the peak values, and defects are detected by the values. PCA(principal component analysis) and QDA(quadratic discriminant analysis) are carried out to classify the types of defects. In PCA, 512 dimensional data are converted into 30 PCs(Principal Components), which is 99% of total variances. Computational cost and misclassification rate are reduced by limiting the number of PCs. A decision boundary equation is obtained by QDA, and defects are classified by the equation. Experimental result shows that our proposed method is able to detect and classify the defects automatically.

Implementation of a Respiration Measurement System Based on a Nonrestraint Approach (무구속 방식의 호흡 측정 시스템 구현)

  • Cho, Seok-Hyang;Cho, Seung-Ho
    • Journal of the Korea Society of Computer and Information
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    • v.19 no.11
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    • pp.33-41
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    • 2014
  • In this paper, we implemented a system to measure respiration rate with nonrestraint sensors comfortable for people to do their everyday life. The proposed system consists of a pad covered with a Piezoelectric sensor, a respiration measuring device able to send the signal data after amplifying and filtering the source signals to the viewer, a viewer providing sensor data visualization and implementing the respiration measuring algorithm. The algorithm is based on a breathing cycle with the local peak points extracted from threshold on sensor data. Respiration measurements on 3 subjects were performed by changing moving averages and thresholds. The proposed system showed less than 5% error rate when proper moving averages are N=50~60 and a range of thresholds is 800~1300. The system will contribute to preventing suffocation during sleep for infants and the elderly living alone.

Study on threshold values of a intensity-of-congestion measure for operations evaluation at signalized intersections based on traffic flow information (교통소통 정보기반 신호교차로 운영평가를 위한 혼잡강도 지표 임계값 연구)

  • Kim, Jin-Tae;Cho, Yongbin
    • International Journal of Highway Engineering
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    • v.20 no.3
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    • pp.85-92
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    • 2018
  • PURPOSES : In this study, analyze the characteristics of IOC indicator 'threshold' which is needed when evaluating the traffic signal operation status with ESPRESSO in various grade road traffic environment of Seoul metropolitan city and derive suggested value to use in field practice. METHODS : Using the computerized database program (Postgresql), we extracted data with regional characteristics (Arterial, Collector road) and temporal characteristics (peak hour, non-peak hour). Analysis of variance and Duncan's validation were performed using statistical analysis program (SPSS) to confirm whether the extracted data contains statistical significance. RESULTS : The analysis period of the main and secondary arterial roads was confirmed to be suitable from 14 days to 60 days. For the arterial, it is suggested to use 20 km/h as the critical speed for PM peak hour and weekly non peak hour. It is suggested to use 25 km/h as the critical speed for AM peak hour and night non peak hour. As for the collector road, it is suggested to use 20 km/h as the critical speed for PM peak hour and weekly non peak hour. It is suggested to use 30 km/h as the critical speed for AM peak hour and night non peak hour. CONCLUSIONS : It is meaningful from a methodological point of view that it is possible to make a reasonable comparative analysis on the signal intersection pre-post analysis when the signal operation DB is renewed by breaking the existing traffic signal operation evaluation method.