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Proceedings Paper

Research on the adaptive probabilistic approach of texture analysis and its application in texture classification
Author(s): De Cai; Wen Hong; Yirong Wu
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Paper Abstract

Within a Bayesian framework, Brady proposed the adaptive texture approach for more accurate description and applied this model in texture segmentation with a neighbourhood-based algorithm. In this paper, the efficiency of the texture model in Brady's segmentation method is investigated. In the segmentation experiments of Brodatz texture mosaics and a remote sensing image, the results show that the good segmentation performance mainly owes to the neighbourhood-based algorithm, but not Brady's texture description model. Moreover, this probabilistic model is applied in texture classification with a MAP method. To improve the correct classification rate of the image bank, a method combining the best adaptive texture description of each class is proposed and obviously improves the rate from 91% to 95%.

Paper Details

Date Published: 5 March 2008
PDF: 9 pages
Proc. SPIE 6623, International Symposium on Photoelectronic Detection and Imaging 2007: Image Processing, 662312 (5 March 2008); doi: 10.1117/12.791429
Show Author Affiliations
De Cai, Institute of Electronics (China)
Wen Hong, Institute of Electronics (China)
Yirong Wu, Institute of Electronics (China)

Published in SPIE Proceedings Vol. 6623:
International Symposium on Photoelectronic Detection and Imaging 2007: Image Processing
Liwei Zhou, Editor(s)

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