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IEEE Conference on Advanced Video and Signal Based Surveillance, 2005.
Wavelet packets and co-occurrence matrices for texture-based image segmentation
Como
September 16-September 16
ISBN: 0-7803-9385-6
ASCII Text
x 
 
M. Bartels, 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 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 - 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
Hong Wei, Dept. of Comput. Sci., Reading Univ., UK
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, 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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