The enhanced LBG algorithm

Clustering applications cover several fields such as audio and video data compression, pattern recognition, computer vision, medical image recognition, etc. In this paper, we present a new clustering algorithm called Enhanced LBG (ELBG). It belongs to the hard and K-means vector quantization groups and derives directly from the simpler LBG. The basic idea we have developed is the concept of utility of a codeword, a powerful instrument to overcome one of the main drawbacks of clustering algorithms: generally, the results achieved are not good in the case of a bad choice of the initial codebook. We will present our experimental results showing the ELBG is able to find better codebooks than previous clustering techniques and the computational complexity is virtually the same as the simpler LBG.

[1]  Robert M. Gray,et al.  An Algorithm for Vector Quantizer Design , 1980, IEEE Trans. Commun..

[2]  Daeryong Lee,et al.  Modified K-means algorithm for vector quantizer design , 1997, IEEE Signal Processing Letters.

[3]  D. Munson.  A note on Lena , 1996 .

[4]  James C. Bezdek,et al.  Generalized clustering networks and Kohonen's self-organizing scheme , 1993, IEEE Trans. Neural Networks.

[5]  Pamela C. Cosman,et al.  Vector quantization of image subbands: a survey , 1996, IEEE Trans. Image Process..

[6]  Allen Gersho,et al.  Asymptotically optimal block quantization , 1979, IEEE Trans. Inf. Theory.

[7]  Jean-Michel Jolion,et al.  Robust Clustering with Applications in Computer Vision , 1991, IEEE Trans. Pattern Anal. Mach. Intell..

[8]  C.-C. Jay Kuo,et al.  A new initialization technique for generalized Lloyd iteration , 1994, IEEE Signal Processing Letters.

[9]  Patrick Bosc,et al.  SQLf: a relational database language for fuzzy querying , 1995, IEEE Trans. Fuzzy Syst..

[10]  Mohammed Ghanbari,et al.  A successive approximation vector quantizer for wavelet transform image coding , 1996, IEEE Trans. Image Process..

[11]  Carlo H. Séquin,et al.  Optimal adaptive k-means algorithm with dynamic adjustment of learning rate , 1995, IEEE Trans. Neural Networks.

[12]  Robert M. Gray,et al.  Bayes risk weighted vector quantization with posterior estimation for image compression and classification , 1996, IEEE Trans. Image Process..

[13]  Teuvo Kohonen,et al.  Self-Organization and Associative Memory , 1988 .

[14]  Carlo S. Regazzoni,et al.  Application to locally optimum detection of a new noise model , 1996, 1996 IEEE International Conference on Acoustics, Speech, and Signal Processing Conference Proceedings.

[15]  James C. Bezdek,et al.  Two soft relatives of learning vector quantization , 1995, Neural Networks.

[16]  Joachim M. Buhmann,et al.  Pairwise Data Clustering by Deterministic Annealing , 1997, IEEE Trans. Pattern Anal. Mach. Intell..

[17]  Nicolaos B. Karayiannis,et al.  Fuzzy algorithms for learning vector quantization , 1996, IEEE Trans. Neural Networks.

[18]  Michael R. Anderberg,et al.  Cluster Analysis for Applications , 1973 .

[19]  Manuel Graña,et al.  An analysis of the GLVQ algorithm , 1995, IEEE Trans. Neural Networks.

[20]  James C. Bezdek,et al.  Repairs to GLVQ: a new family of competitive learning schemes , 1996, IEEE Trans. Neural Networks.

[21]  Kohji Fukunaga,et al.  Introduction to Statistical Pattern Recognition-Second Edition , 1990 .

[22]  J.E. Mazo,et al.  Digital communications , 1985, Proceedings of the IEEE.

[23]  Kuldip K. Paliwal,et al.  Efficient vector quantization of LPC parameters at 24 bits/frame , 1993, IEEE Trans. Speech Audio Process..

[24]  Nicolaos B. Karayiannis,et al.  A methodology for constructing fuzzy algorithms for learning vector quantization , 1997, IEEE Trans. Neural Networks.

[25]  S. P. Lloyd,et al.  Least squares quantization in PCM , 1982, IEEE Trans. Inf. Theory.

[26]  John G. Proakis,et al.  Digital Communications , 1983 .

[27]  Philip A. Chou,et al.  Variable rate vector quantization for speech, image, and video compression , 1993, IEEE Trans. Commun..

[28]  Allen Gersho,et al.  Vector quantization and signal compression , 1991, The Kluwer international series in engineering and computer science.