Details

Autor(en) / Beteiligte

• Rajagopalan, A.N.
• Yeasin, M.
• Chauldhuri, S.

Titel

Data clustering using higher order statistics

Ist Teil von

• TENCON '97 Brisbane - Australia. Proceedings of IEEE TENCON '97. IEEE Region 10 Annual Conference. Speech and Image Technologies for Computing and Telecommunications (Cat. No.97CH36162), 1997, Vol.2, p.803-806 vol.2

Ort / Verlag

IEEE

Erscheinungsjahr

1997

Quelle

IEEE Xplore

Beschreibungen/Notizen

• Traditional k-means algorithms for data clustering are based on the assumption that the underlying distribution of the data is Gaussian. In this paper, we propose a new clustering algorithm that makes use of higher order statistics for improved data clustering when the distribution of the data is non-Gaussian. The algorithm uses an HOS-based decision measure which is derived from a series expansion of the multivariate probability density function in terms of the multivariate Gaussian and the Hermite polynomials. Experimental results are presented on the performance of the proposed algorithm using color images segmentation.