• Title/Summary/Keyword: Lloyd Algorithm

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A Robust Vector Quantization Method against Distortion Outlier and Source Mismatch (이상 신호왜곡과 소스 불일치에 강인한 벡터 양자화 방법)

  • Noh, Myung-Hoon;Kim, Moo-Young
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.49 no.3
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    • pp.74-80
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    • 2012
  • In resolution-constrained quantization, the size of Voronoi cell varies depending on probability density function of the input data, which causes large amount of distortion outliers. We propose a vector quantization method that reduces distortion outliers by combining the generalized Lloyd algorithm (GLA) and the cell-size constrained vector quantization (CCVQ) scheme. The training data are divided into the inside and outside regions according to the size of Voronoi cell, and consequently CCVQ and GLA are applied to each region, respectively. As CCVQ is applied to the densely populated region of the source instead of GLA, the number of centroids for the outside region can be increased such that distortion outliers can be decreased. In real-world environment, source mismatch between training and test data is inevitable. For the source mismatch case, the proposed algorithm improves performance in terms of average distortion and distortion outliers.

Weighted Distance-Based Quantization for Distributed Estimation

  • Kim, Yoon Hak
    • Journal of information and communication convergence engineering
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    • v.12 no.4
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    • pp.215-220
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    • 2014
  • We consider quantization optimized for distributed estimation, where a set of sensors at different sites collect measurements on the parameter of interest, quantize them, and transmit the quantized data to a fusion node, which then estimates the parameter. Here, we propose an iterative quantizer design algorithm with a weighted distance rule that allows us to reduce a system-wide metric such as the estimation error by constructing quantization partitions with their optimal weights. We show that the search for the weights, the most expensive computational step in the algorithm, can be conducted in a sequential manner without deviating from convergence, leading to a significant reduction in design complexity. Our experments demonstrate that the proposed algorithm achieves improved performance over traditional quantizer designs. The benefit of the proposed technique is further illustrated by the experiments providing similar estimation performance with much lower complexity as compared to the recently published novel algorithms.

Fast Algorithms to Generate the Codebook for Vector Quantization in Image Coding (화상 벡터 양자화의 코드북 구성을 위한 고속 알고리즘)

  • 이주희;정해묵;이충웅
    • Journal of the Korean Institute of Telematics and Electronics
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    • v.27 no.1
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    • pp.105-111
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    • 1990
  • In this paper, fast algorithms to generate the codebook of vector quantization in image coding, are proposed. And an efficient algorithm to guess a initial codebook, namely, binary splitting method, is proposed. We generated the initial codebook by binary splitting method and then reduced the searching time using Iterative Optimization algorithm as an alternate to the generalized Lloyd algorithm and several information from binary splitting method. And the searching time and performance can be traded off by varying the searching range. With this proposed algorithm, the computation time can be reduced by a factor of 60 Without any degradation of image quality.

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The Cooperate Navigation for Swarm Robot Using Centroidal Voronoi Tessellation (무게중심 보로노이 테셀레이션을 이용한 군집로봇의 협조탐색)

  • Bang, Mun-Seop;Joo, Young-Hoon
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.61 no.1
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    • pp.130-134
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    • 2012
  • In this paper, we propose a space partitioning technique for swarm robots by using the Centroidal Voronoi Tessellation. The proposed method consists of two parts such as space partition and collision avoidance. The space partition for searching a given space is carried out by a density function which is generated by some accidents. The collision avoidance is implemented by the potential field method. Finally, the numerical experiments show the effectiveness and feasibility of the proposed method.

Maximum Likelihood (ML)-Based Quantizer Design for Distributed Systems

  • Kim, Yoon Hak
    • Journal of information and communication convergence engineering
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    • v.13 no.3
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    • pp.152-158
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    • 2015
  • We consider the problem of designing independently operating local quantizers at nodes in distributed estimation systems, where many spatially distributed sensor nodes measure a parameter of interest, quantize these measurements, and send the quantized data to a fusion node, which conducts the parameter estimation. Motivated by the discussion that the estimation accuracy can be improved by using the quantized data with a high probability of occurrence, we propose an iterative algorithm with a simple design rule that produces quantizers by searching boundary values with an increased likelihood. We prove that this design rule generates a considerably reduced interval for finding the next boundary values, yielding a low design complexity. We demonstrate through extensive simulations that the proposed algorithm achieves a significant performance gain with respect to traditional quantizer designs. A comparison with the recently published novel algorithms further illustrates the benefit of the proposed technique in terms of performance and design complexity.

Low-Complexity Design of Quantizers for Distributed Systems

  • Kim, Yoon Hak
    • Journal of information and communication convergence engineering
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    • v.16 no.3
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    • pp.142-147
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    • 2018
  • We present a practical design algorithm for quantizers at nodes in distributed systems in which each local measurement is quantized without communication between nodes and transmitted to a fusion node that conducts estimation of the parameter of interest. The benefits of vector quantization (VQ) motivate us to incorporate the VQ strategy into our design and we propose a low-complexity design technique that seeks to assign vector codewords into sets such that each codeword in the sets should be closest to its associated local codeword. In doing so, we introduce new distance metrics to measure the distance between vector codewords and local ones and construct the sets of vector codewords at each node to minimize the average distance, resulting in an efficient and independent encoding of the vector codewords. Through extensive experiments, we show that the proposed algorithm can maintain comparable performance with a substantially reduced design complexity.

Spectral-Reflectance Estimation Using Adaptive Principle Component Analysis in Similar Color Region (유사 색상 영역의 적응적인 주성분 분석을 이용한 표면분광반사율 추정)

  • 권오설;이철희;이호근;하영호
    • Proceedings of the IEEK Conference
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    • 2003.07e
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    • pp.1767-1770
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    • 2003
  • This paper proposes an algorithm that can reduce the estimation error of surface spectral-reflectance(SR) when using a conventional 3-band RGB camera. In the proposed method, the estimation error is reduced by using adaptive principle components (PCs) for each color region. To build an adaptive set of PCs, n SR populations are organized for n PC sets using the Lloyd quantizer design algorithm. The Macbeth Color Checker is utilized for the initial representative SR values for 1485 Munsell color chips as the total color population, then the Munsell chips arc divided into subsets with a set of corresponding adaptive PCs organized for each subset.

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Fast hierarchical image segmentation based on mathematical morphology (수리형태론에 기반한 고속 계층적 영상분할)

  • 김해룡;홍원학;김남철
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.33B no.10
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    • pp.38-49
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    • 1996
  • In this paper, we propose a fast hierarchical image segmentation using mathematical morphology. The proposed segmentation method is composed of five basic steps; multi-thresholding, open-close by reconstructing, mode operation, marker extraction, and region decision. In the multi-thresholding, an input image is simplified by Lloyd clustering algorithm. The multi-thresholded image then is more simplified by open-close by reconstruction and mode operating. In the region decision, to which region each uncertainty pixel belongs finally is decided by a watershed algorithm. Experimental results show that the quality of the segmentation results by the proposed method is not inferior to that by the conventional method and the average times elapsed by the proposed method can be reduced by one tghird of those elapsed by the conventional method.

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Optimum Design of the Power Yacht Based on Micro-Genetic Algorithm

  • Park, Joo-Shin;Kim, Yun-Young
    • Journal of Navigation and Port Research
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    • v.33 no.9
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    • pp.635-644
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    • 2009
  • The optimum design of power yacht belongs to the nonlinear constrained optimization problems. The determination of scantlings for the bow structure is a very important issue with in the whole structural design process. The derived design results are obtained by the use of real-coded micro-genetic algorithm including evaluation from Lloyd's Register small craft guideline, so that the nominal limiting stress requirement can be satisfied. In this study, the minimum volume design of bow structure on the power yacht was carried out based on the finite element analysis. The target model for optimum design and local structural analysis is the bow structure of a power yacht. The volume of bow structure and the main dimensions of structural members are chosen as an objective function and design variable, respectively. During optimization procedure, finite element analysis was performed to determine the constraint parameters at each iteration step of the optimization loop. optimization results were compared with a pre-existing design and it was possible to reduce approximately 19 percents of the total steel volume of bow structure from the previous design for the power yacht.

Sample-Adaptive Product Quantization and Design Algorithm (표본 적응 프러덕트 양자화와 설계 알고리즘)

  • 김동식;박섭형
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.24 no.12B
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    • pp.2391-2400
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    • 1999
  • Vector quantizer (VQ) is an efficient data compression technique for low bit rate applications. However, the major disadvantage of VQ is its encoding complexity which increases dramatically as the vector dimension and bit rate increase. Even though one can use a modified VQ to reduce the encoding complexity, it is nearly impossible to implement such a VQ at a high bit rate or for a large vector dimension because of the enormously large memory requirement for the codebook and the very large training sequence (TS) size. To overcome this difficulty, in this paper we propose a novel structurally constrained VQ for the high bit rate and the large vector dimension cases in order to obtain VQ-level performance. Furthermore, this VQ can be extended to the low bit rate applications. The proposed quantization scheme has a form of feed-forward adaptive quantizer with a short adaptation period. Hence, we call this quantization scheme sample-adaptive product quantizer (SAPQ). SAPQ can provide a 2 ~3dB improvement over the Lloyd-Max scalar quantizers.

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