Fast Estimation of the Number of Texture Segments Using Co-occurrence Statistics Conference Paper

abstract

• Estimation of the number of clusters is an essential processing step for various applications. Existing approaches search for an optimal solution by computing and comparing a validity measure for all feasible configurations, and tend to under-estimate the number of clusters incorrectly. In this paper, we propose a fast and robust method to estimate the number of clusters without adopting the exhaustive search. Our scheme first extracts the relationship of neighboring features, and then uses this information to partition the clusters. The superb performance of the method is verified by the simulation results in determining the number of texture segments in the textured images.

name of conference

• 2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03).

authors

• Liu, Jyh

published proceedings

• 2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03).

author list (cited authors)

• Pok, G., Liu, J., & Ryu, K. H.

citation count

• 0

complete list of authors

• Pok, Gou-Chol||Liu, Jyh-Charn||Ryu, Keun Ho

publication date

• January 2003

publisher

• Institute of Electrical and Electronics Engineers (IEEE)  Publisher

published in

• Proceedings of the ... IEEE International Conference on Acoustics, Speech, and Signal Processing / sponsored by the Institute of Electrical and Electronics Engineers Signal Processing Society. ICASSP (Conference)  Journal

Digital Object Identifier (DOI)

• 10.1109/icassp.2003.1199479

start page

• i-341-i-344

end page

• 344

volume

• 3

URL

• http%3A%2F%2Fdx.doi.org%2F10.1109%2Ficassp.2003.1199479