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Sensors 2016, 16(11), 1963; doi:10.3390/s16111963

Accelerating Families of Fuzzy K-Means Algorithms for Vector Quantization Codebook Design

1
Center of Science and Technology, Catholic University of Pernambuco (UNICAP), Recife 50050-900, Brazil
2
Centro de Informática, Universidade Federal de Pernambuco (UFPE), Recife 50740-560, Brazil
3
Department of Electrical Engineering, Center of Alternative and Renewable Energy, Federal University of Paraíba (UFPB), João Pessoa 58038-130, Brazil
*
Author to whom correspondence should be addressed.
Academic Editor: Vittorio M. N. Passaro
Received: 24 August 2016 / Revised: 11 November 2016 / Accepted: 15 November 2016 / Published: 23 November 2016
(This article belongs to the Section Physical Sensors)
View Full-Text   |   Download PDF [2632 KB, uploaded 23 November 2016]   |  

Abstract

The performance of signal processing systems based on vector quantization depends on codebook design. In the image compression scenario, the quality of the reconstructed images depends on the codebooks used. In this paper, alternatives are proposed for accelerating families of fuzzy K-means algorithms for codebook design. The acceleration is obtained by reducing the number of iterations of the algorithms and applying efficient nearest neighbor search techniques. Simulation results concerning image vector quantization have shown that the acceleration obtained so far does not decrease the quality of the reconstructed images. Codebook design time savings up to about 40% are obtained by the accelerated versions with respect to the original versions of the algorithms. View Full-Text
Keywords: fuzzy K-means; vector quantization; computational complexity fuzzy K-means; vector quantization; computational complexity
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Mata, E.; Bandeira, S.; de Mattos Neto, P.; Lopes, W.; Madeiro, F. Accelerating Families of Fuzzy K-Means Algorithms for Vector Quantization Codebook Design. Sensors 2016, 16, 1963.

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