• Title/Summary/Keyword: threshold algorithm

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A SM2 Elliptic Curve Threshold Signature Scheme without a Trusted Center

  • Jie, Yan;Yu, Lu;Li-yun, Chen;Wei, Nie
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.10 no.2
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    • pp.897-913
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    • 2016
  • Threshold signature is very important in identity authentication and some other applications. In December 2010, Chinese Encryption Administration released the SM2 elliptic curve digital signature algorithm as the first standard of the digital signature algorithm in China. At present, the papers on the threshold signature scheme based on this algorithm are few. A SM2 elliptic curve threshold signature scheme without a trusted center is proposed according to the Joint-Shamir-RSS algorithm, the Joint-Shamir-ZSS algorithm, the sum or diff-SS algorithm, the Mul-SS algorithm, the Inv-SS algorithm and the PM-SS algorithm. The proposed scheme is analyzed from correctness, security and efficiency. The correctness analysis shows that the proposed scheme can realize the effective threshold signature. The security analysis shows that the proposed scheme can resist some kinds of common attacks. The efficiency analysis shows that if the same secret sharing algorithms are used to design the threshold signature schemes, the SM2 elliptic curve threshold signature scheme will be more efficient than the threshold signature scheme based on ECDSA.

A Computational Improvement of Otsu's Algorithm by Estimating Approximate Threshold (근사 임계값 추정을 통한 Otsu 알고리즘의 연산량 개선)

  • Lee, Youngwoo;Kim, Jin Heon
    • Journal of Korea Multimedia Society
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    • v.20 no.2
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    • pp.163-169
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    • 2017
  • There are various algorithms evaluating a threshold for image segmentation. Among them, Otsu's algorithm sets a threshold based on the histogram. It finds the between-class variance for all over gray levels and then sets the largest one as Otsu's optimal threshold, so we can see that Otsu's algorithm requires a lot of the computation. In this paper, we improved the amount of computational needs by using estimated Otsu's threshold rather than computing for all the threshold candidates. The proposed algorithm is compared with the original one in computation amount and accuracy. we confirm that the proposed algorithm is about 29 times faster than conventional method on single processor and about 4 times faster than on parallel processing architecture machine.

Stagewise Weak Orthogonal Matching Pursuit Algorithm Based on Adaptive Weak Threshold and Arithmetic Mean

  • Zhao, Liquan;Ma, Ke
    • Journal of Information Processing Systems
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    • v.16 no.6
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    • pp.1343-1358
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    • 2020
  • In the stagewise arithmetic orthogonal matching pursuit algorithm, the weak threshold used in sparsity estimation is determined via maximum iterations. Different maximum iterations correspond to different thresholds and affect the performance of the algorithm. To solve this problem, we propose an improved variable weak threshold based on the stagewise arithmetic orthogonal matching pursuit algorithm. Our proposed algorithm uses the residual error value to control the weak threshold. When the residual value decreases, the threshold value continuously increases, so that the atoms contained in the atomic set are closer to the real sparsity value, making it possible to improve the reconstruction accuracy. In addition, we improved the generalized Jaccard coefficient in order to replace the inner product method that is used in the stagewise arithmetic orthogonal matching pursuit algorithm. Our proposed algorithm uses the covariance to replace the joint expectation for two variables based on the generalized Jaccard coefficient. The improved generalized Jaccard coefficient can be used to generate a more accurate calculation of the correlation between the measurement matrixes. In addition, the residual is more accurate, which can reduce the possibility of selecting the wrong atoms. We demonstrate using simulations that the proposed algorithm produces a better reconstruction result in the reconstruction of a one-dimensional signal and two-dimensional image signal.

A Study on the Dynamic Priority Scheduling for Multiple Class Traffic in ATM Network (ATM망에서 다중등급 통화유량 처리를 위한 동적 우선순위 스케쥴링에 관한 연구)

  • 정상국;진용옥
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.18 no.2
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    • pp.279-287
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    • 1993
  • In this paper, double laxity threshold MLT(Minimum Laxity Threshold) algorithm and double queue threshold QLT(Queue Length Threshold) algorithm are proposed as DPS(Dynamic Priority Scheduling) techniques for advanced processing of multiple class traffics. Also, the performance of the proposed algorithms is analyzed by a computer simulation. According to the simulation results, it can be shown that the proposed double laxity threshold ML T algorithm advances the processing performance versus ML T algorithm for 2 or more classes delay sensitive traffics, and that double queue length threshold QL T algorithm provides more efficient performance than QL T for 2 or more classes of non real time traffics.

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Buffer Management Mechanism Using DT-DFBA Algorithm for GFR Service (GFR 서비스를 위한 DT-DFBA 버퍼관리 메커니즘)

  • 안상규;최승권;신승수;조용환
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.27 no.5C
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    • pp.474-485
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    • 2002
  • To keep simplicity that needs for GFR service and improve fairness of FIFO based buffer management algorithm, we propose a new LBO threshold decision mechanism. Proposed mechanism uses dynamic threshold that are adjusted according to the sum of active VC's weight. We reformed DT-DFBA(Differential Threshold-Differential Fair Buffer Allocation) algorithm using proposed LBO threshold decision mechanism with existing DFBA algorithm.

The Improved Watershed Algorithm using Adaptive Local Threshold (적응적 지역 임계치를 이용한 개선된 워터쉐드 알고리즘)

  • Lee Seok-Hee;Kwon Dong-Jin;Kwak Nae-Joung;Ahn Jae-Hyeong
    • Annual Conference of KIPS
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    • 2004.11a
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    • pp.891-894
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    • 2004
  • This paper proposes an improved image segmentation algorithm by the watershed algorithm based on the local adaptive threshold on local minima search and the fixing threshold on label allocation. The previous watershed algorithm generates the problem of over-segmentation. The over-segmentation makes the boundary in the inaccuracy region by occurring around the object. In order to solve those problems we quantize the input color image by the vector quantization, remove noise and find the gradient image. We sorted local minima applying the local adaptive threshold on local minima search of the input color image. The simulation results show that the proposed algorithm controls over-segmentation and makes the fine boundary around segmented region applying the fixing threshold based on sorted local minima on label allocation.

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An Improved Acquisition of the Noncoherent DS/SS-CSK (비동기식 DS/SS-CSK 통신의 개선된 초기동기)

  • 김종헌;이한섭;홍대식;강창언
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.18 no.12
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    • pp.1797-1805
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    • 1993
  • An algorithm for the threshold decision from the maximum mismatching correlation value in a direct-sequence spread-spectrum system is presented. This algorithm is named the TDMMC(Threshold Decision from the Maximum Mismatching Correlation value). The purpose of the algorithm is to set the decision threshold in the system which will provide large probability of signal detection. Using this algorithm, the proper setting of the threshold for various SNRs is possible. An additional block called the Threshold Block is used to improve the system performance. The result from the computer simmulation has shown that appling the TDMMC to the noncoherent DS/SS-CSK system can achieve performance improvement.

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Fish Injured Rate Measurement Using Color Image Segmentation Method Based on K-Means Clustering Algorithm and Otsu's Threshold Algorithm

  • Sheng, Dong-Bo;Kim, Sang-Bong;Nguyen, Trong-Hai;Kim, Dae-Hwan;Gao, Tian-Shui;Kim, Hak-Kyeong
    • Journal of Power System Engineering
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    • v.20 no.4
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    • pp.32-37
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    • 2016
  • This paper proposes two measurement methods for injured rate of fish surface using color image segmentation method based on K-means clustering algorithm and Otsu's threshold algorithm. To do this task, the following steps are done. Firstly, an RGB color image of the fish is obtained by the CCD color camera and then converted from RGB to HSI. Secondly, the S channel is extracted from HSI color space. Thirdly, by applying the K-means clustering algorithm to the HSI color space and applying the Otsu's threshold algorithm to the S channel of HSI color space, the binary images are obtained. Fourthly, morphological processes such as dilation and erosion, etc. are applied to the binary image. Fifthly, to count the number of pixels, the connected-component labeling is adopted and the defined injured rate is gotten by calculating the pixels on the labeled images. Finally, to compare the performances of the proposed two measurement methods based on the K-means clustering algorithm and the Otsu's threshold algorithm, the edge detection of the final binary image after morphological processing is done and matched with the gray image of the original RGB image obtained by CCD camera. The results show that the detected edge of injured part by the K-means clustering algorithm is more close to real injured edge than that by the Otsu' threshold algorithm.

The Development of Automatic Correction Algorithm for the Knocking Threshold in Spark Ignition Engine (스파크 점화기관에서의 노킹판단 기준값의 자동수정 알고리즘 개발)

  • 강성현;장광수;서정인;전광민
    • Transactions of the Korean Society of Automotive Engineers
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    • v.7 no.7
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    • pp.32-41
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    • 1999
  • In this study, a new knocking control algorithm was developed using the knock threshold value auto-correction algorithm. This algorithm uses the Fast Fourier Transform9FFT) method by measuring cylinder block vibration signals of a 1498 cc four-cylinder spark ignition engine. The experimental results show the proposed knock control algorithm provides improved performance compared to existing methods. The results also show that the proposed FFT algorithm provides real-time adjustment of the knock threshold value.

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Automatic Thresholding Selection for Image Segmentation Based on Genetic Algorithm (유전자알고리즘을 이용한 영상분할 문턱값의 자동선정에 관한 연구)

  • Lee, Byung-Ryong;Truong, Quoc Bao;Pham, Van Huy;Kim, Hyoung-Seok
    • Journal of Institute of Control, Robotics and Systems
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    • v.17 no.6
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    • pp.587-595
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    • 2011
  • In this paper, we focus on the issue of automatic selection for multi-level threshold, and we greatly improve the efficiency of Otsu's method for image segmentation based on genetic algorithm. We have investigated and evaluated the performance of the Otsu and Valley-emphasis threshold methods. Based on this observation we propose a method for automatic threshold method that segments an image into more than two regions with high performance and processing in real-time. Our paper introduced new peak detection, combines with evolution algorithm using MAGA (Modified Adaptive Genetic Algorithm) and HCA (Hill Climbing Algorithm), to find the best threshold automatically, accurately, and quickly. The experimental results show that the proposed evolutionary algorithm achieves a satisfactory segmentation effect and that the processing time can be greatly reduced when the number of thresholds increases.