Wavelet packets and co-occurrence matrices for texture-based image segmentation

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IEEE Conference on Advanced Video and Signal Based Surveillance, 2005.

Como

September 16-September 16

ISBN: 0-7803-9385-6

	ASCII Text	x
	M. Bartels, null Hong Wei, D.C. MAson, "Wavelet packets and co-occurrence matrices for texture-based image segmentation," Advanced Video and Signal Based Surveillance, IEEE Conference on, pp. 428-433, IEEE Conference on Advanced Video and Signal Based Surveillance, 2005., 2005.

	BibTex	x
	@article{ 10.1109/AVSS.2005.1577307, author = {M. Bartels and null Hong Wei and D.C. MAson}, title = {Wavelet packets and co-occurrence matrices for texture-based image segmentation}, journal ={Advanced Video and Signal Based Surveillance, IEEE Conference on}, volume = {0}, year = {2005}, isbn = {0-7803-9385-6}, pages = {428-433}, doi = {http://doi.ieeecomputersociety.org/10.1109/AVSS.2005.1577307}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - Advanced Video and Signal Based Surveillance, IEEE Conference on TI - Wavelet packets and co-occurrence matrices for texture-based image segmentation SN - 0-7803-9385-6 SP428 EP433 A1 - M. Bartels, A1 - null Hong Wei, A1 - D.C. MAson, PY - 2005 KW - light detection and ranging KW - co-occurrence matrices KW - texture-based segmentation approach KW - normalised modified histogram thresholding KW - wavelet packet decomposition VL - 0 JA - Advanced Video and Signal Based Surveillance, IEEE Conference on ER -

M. Bartels, Dept. of Comput. Sci., Reading Univ., UK

null Hong Wei, Dept. of Comput. Sci., Reading Univ., UK

D.C. MAson

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/AVSS.2005.1577307

In this paper, a texture-based segmentation approach using wavelet packets, co-occurrence matrices and normalised modified histogram thresholding is discussed and developed. Background and objects in remotely sensed light detection and ranging (LIDAR) data are successfully partitioned into rivers, fields and residential areas using the developed algorithms. The issue of wavelet packet decomposition level is addressed by analysing the sub-images' energy and entropy. The standard deviation of the modified histogram, which is derived from the main diagonal of the sub-image's co-occurrence matrix, is used as a measure to evaluate the sub-images in terms of thresholdability. Finally, the segmentation results are presented.

Index Terms:

light detection and ranging, co-occurrence matrices, texture-based segmentation approach, normalised modified histogram thresholding, wavelet packet decomposition

Citation:

M. Bartels, null Hong Wei, D.C. MAson, "Wavelet packets and co-occurrence matrices for texture-based image segmentation," avss, pp.428-433, IEEE Conference on Advanced Video and Signal Based Surveillance, 2005., 2005

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