• 제목/요약/키워드: threshold algorithm

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저전력 특징추출 알고리즘의 구현을 위한 블록 유형 분류 기반 낮은 복잡도를 갖는 영상 이진화 (Low Complexity Image Thresholding Based on Block Type Classification for Implementation of the Low Power Feature Extraction Algorithm)

  • 이주성;안호명;김병철
    • 한국정보전자통신기술학회논문지
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    • 제12권3호
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    • pp.179-185
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    • 2019
  • 본 논문은 저전력 특징추출 알고리즘의 구현을 위한 블록 유형 분류 기반 영상 이진화 방법을 제안한다. 제안하는 방법은 영상 내에서 $64{\times}64$ macro block 크기로 영상을 나누고 각 블록 유형별 threshold 값을 한 번만 연산한 후 그 값을 re-use 하는 기법으로 구현될 수 있다. 알고리즘은 threshold 값이 같은 영상/블록 유형 내에서 최대 9%의 변화율만 발생하는 것을 정량적인 결과를 기반으로 검증했다. 기존 알고리즘은 $512{\times}512$ 이미지 기준으로 macro block을 $64{\times}64$로 나누었을 때 64개의 블록을 위해 threshold 값을 연산해야 하지만 제안하는 방법은 모두 같은 블록 유형이 출력되는 best case의 경우 threshold 연산을 한번만 수행하고, 나머지 63개의 블록에 대해서는 블록 유형 구분 과정만 수행하면 adaptive threshold calculation 연산을 98% 생략할 수 있다. 모든 블록 유형이 발생하는 worst case일 때 threshold calculation 연산은 다섯 번 수행되고, 나머지 59개의 블록에 대해서는 블록 유형 구분 과정만 수행할 수 있으므로 93%의 adaptive threshold calculation 연산을 생략할 수 있다.

저궤도 위성 Receiver의 Threshold측정 시험 결과에 대한 분석 (Analysis about Threshold Measurement Test Result of LEO Satellite Receiver)

  • 조승원;권재욱;최종연;최석원
    • 항공우주기술
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    • 제5권2호
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    • pp.77-84
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    • 2006
  • 저궤도 위성의 시스템 시험에서는 위성의 5 대역 Receiver의 적정 수신 RF 전력 영역을 확인하기 위하여 저궤도 위성의 Receiver Tracking Threshold와 Command Threshold를 측정한다. 본 논문에서는 두 Threshold 측정의 알고리듬을 살펴보고 통합 시스템 시험 (Integrated System Test)에서 수행하였던 결과를 보여준다. 그 후에 Receiver의 성능 이외 에 Threshold 측정결과에 영향을 미칠 수 있는 요소를 알아보고 그에 따른 왜곡된 값을 분석하여 보정을 수행하였다.

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블록 영상의 통계적 특성을 이용한 적응적 상황 검출 알고리즘 (An Adaptive Event Detection Algorithm Based on Statistics of Subblock Images)

  • 하영욱;김희태
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 1998년도 추계종합학술대회 논문집
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    • pp.875-878
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    • 1998
  • In this paper, an adaptive event detection algorithm is proposed, for which we use the statistics of subblock image and adaptive threshold levels. The adaptive threshold level for a parameter binarization is taken by averaging the corresponding paramerter obtained from several input images. As simulation results, it is shown that the proposed algorithm is much more adaptive to the input images and effective in event detection rate than the conventional difference based algorithms.

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임계값 학습에 의한 Hopfield망의 기억 효율 개선 (An Improvement of Memory Efficiency by Iearning Threshold on the Hopfield Network)

  • 김재훈;김한우;최병욱
    • 대한전기학회논문지
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    • 제40권7호
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    • pp.718-724
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    • 1991
  • In this paper, we proposed an algorithm to improve the memory efficiency by means of learning thresholds in spite of correlations among input patterns to be memorized. The proposed algorithm does not need preprocess correlations among input patterns but processes them with a threshold on a neural network. When memory contents are destroyed by correlation, nearly all patterns can be properly recovered with past learning. Through experiments we show how out algorithm can improve the memory efficiency.

Generalized SCAN Bit-Flipping Decoding Algorithm for Polar Code

  • Lou Chen;Guo Rui
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제17권4호
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    • pp.1296-1309
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    • 2023
  • In this paper, based on the soft cancellation (SCAN) bit-flipping (SCAN-BF) algorithm, a generalized SCAN bit-flipping (GSCAN-BF-Ω) decoding algorithm is carried out, where Ω represents the number of bits flipped or corrected at the same time. GSCAN-BF-Ω algorithm corrects the prior information of the code bits and flips the prior information of the unreliable information bits simultaneously to improve the block error rate (BLER) performance. Then, a joint threshold scheme for the GSCAN-BF-2 decoding algorithm is proposed to reduce the average decoding complexity by considering both the bit channel quality and the reliability of the coded bits. Simulation results show that the GSCAN-BF-Ω decoding algorithm reduces the average decoding latency while getting performance gains compared to the common multiple SCAN bit-flipping decoding algorithm. And the GSCAN-BF-2 decoding algorithm with the joint threshold reduces the average decoding latency further by approximately 50% with only a slight performance loss compared to the GSCAN-BF-2 decoding algorithm.

파라메트릭 배열을 이용한 해저지층 탐사 알고리즘 (Sub-bottom Profiling Algorithm using Parametric Array)

  • 이종현;이재일;배진호
    • 한국해양공학회지
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    • 제28권1호
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    • pp.55-63
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    • 2014
  • In this paper, we propose an threshold-based Schur algorithm for estimating the media characteristics of sub-bottom multi-layers by using the signal generated by a parametric array transducer. We use the KZK model to generate a parametric array signal, and use the proposed threshold-based Schur algorithm for estimating the reflection coefficients of multiple sea bottom layers. Using computer simulation, we verify that the difference frequency component generated by the KZK model prevails over the signals of primary frequencies at long range. For the simulation, we use the transmit signal generated by the KZK and the reflected signal obtained from a lattice filter model for the seawater and sub-bottom of multi-level non-homogeneous layers. Through the simulation, we verify that the proposed threshold-based Schur algorithm can give much more accurate and efficient estimates of the reflection coefficients than methods using received signal, matched filter output signal, and normal Schur algorithm output.

차영상에서의 히스토그램을 이용한 적응적 임계값 결정 (Decision of Adaptive Threshold Value Using Histogram in Differential Image)

  • 오명관;김태익;최동진;전병민
    • 한국콘텐츠학회논문지
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    • 제4권3호
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    • pp.91-97
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    • 2004
  • 이동 객체 추적 시스템을 위한 한 연구 분야로 차영상을 이용하여 움직임을 추정하는 기법이 있다. 움직임 추정을 위해 차영상을 이용하는 경우 임계값을 적용하여 배경 영역과 이동 객체 영역을 구분할 수 있도록 이진화를 수행하는 과정이 필수적이다. 본 논문에서는 차영상에서 배경과 객체의 특성 변화에 적응적인 임계값 결정 기법을 제안하였다. 제안 기법은 차영상의 히스토그램 모양을 분석하여 적절한 임계값을 결정하도록 하였다. 그레이 스케일 영상의 이진화에 사용되는 일반적인 임계값 기법들과 성능을 비교 평가하였다. 60개의 실험 영상에 대해 평가한 결과 제안 기법이 수작업으로 확인한 최적의 임계값과 평균 오차 2.8로 성능의 우수성을 확인하였다.

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A Simple and Robustness Algorithm for ECG R- peak Detection

  • Rahman, Md Saifur;Choi, Chulhyung;Kim, Young-pil;Kim, Sikyung
    • Journal of Electrical Engineering and Technology
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    • 제13권5호
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    • pp.2080-2085
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    • 2018
  • There have been numerous studies that extract the R-peak from electrocardiogram (ECG) signals. All of these studies can extract R-peak from ECG. However, these methods are complicated and difficult to implement in a real-time portable ECG device. After filtration choosing a threshold value for R-peak detection is a big challenge. Fixed threshold scheme is sometimes unable to detect low R-peak value and adaptive threshold sometime detect wrong R-peak for more adaptation. In this paper, a simple and robustness algorithm is proposed to detect R-peak with less complexity. This method also solves the problem of threshold value selection. Using the adaptive filter, the baseline drift can be removed from ECG signal. After filtration, an appropriate threshold value is automatically chosen by using the minimum and maximum value of an ECG signals. Then the neighborhood searching scheme is applied under threshold value to detect R-peak from ECG signals. Proposed method improves the detection and accuracy rate of R-peak detection. After R-peak detection, we calculate heart rate to know the heart condition.

NOAA/AVHRR 주간 자료로부터 지면 자료 추출을 위한 구름 탐지 알고리즘 개발 (Development of Cloud Detection Algorithm for Extracting the Cloud-free Land Surface from Daytime NOAA/AVHRR Data)

  • 서명석;이동규
    • 대한원격탐사학회지
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    • 제15권3호
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    • pp.239-251
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    • 1999
  • The elimination process of cloud-contaminated pixels is one of important steps before obtaining the accurate parameters of land and ocean surface from AVHRR imagery. We developed a 6step threshold method to detect the cloud-contaminated pixels from NOAA-14/AVHRR datime imagery over land using different combination of channels. This algorithm has two phases : the first is to make a cloud-free characteristic data of land surface using compositing techniques from channel 1 and 5 imagery and a dynamic threshold of brightness temperature, and the second is to identify the each pixel as a cloud-free or cloudy one through 4-step threshold tests. The merits of this method are its simplicity in input data and automation in determining threshold values. The threshold of infrared data is calculated through the combination of brightness temperature of land surface obtained from AVHRR imagery, spatial variance of them and temporal variance of observed land surface temperature. The method detected the could-comtaminated pixels successfully embedded inthe NOAA-14/AVHRR daytime imagery for the August 1 to November 30, 1996 and March 1 to July 30, 1997. This method was evaluated through the comparison with ground-based cloud observations and with the enhanced visible and infrared imagery.

플립 칩 BGA 최종 검사를 위한 최대퍼지엔트로피 기반의 다중임계값 선정 알고리즘 (A Multiple Threshold Selection Algorithm Based on Maximum Fuzzy Entropy for the Final Inspection of Flip Chip BGA)

  • 김경범
    • 한국정밀공학회지
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    • 제21권4호
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    • pp.202-209
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    • 2004
  • Quality control is essential to the final product in BGA-type PCB fabrication. So, many automatic vision systems have been developed to achieve speedy, low cost and high quality inspection. A multiple threshold selection algorithm is a very important technique for machine vision based inspection. In this paper, an inspected image is modeled by using fuzzy sets and then the parameters of specified membership functions are estimated to be in maximum fuzzy entropy with the probability of the fuzzy sets, using the exhausted search method. Fuzzy c-partitions with the estimated parameters are automatically generated, and then multiple thresholds are selected as the crossover points of the fuzzy sets that form the estimated fuzzy partitions. Several experiments related to flip chip BGA images show that the proposed algorithm outperforms previous ones using both entropy and variance, and also can be successfully applied to AVI systems.