Color and texture feature fusion using kernel PCA with application to object-based vegetation species classification
Li, Zhengrong, Liu, Yuee, Hayward, Ross F., & Walker, Rodney A. (2010) Color and texture feature fusion using kernel PCA with application to object-based vegetation species classification. In Proceedings of 2010 IEEE 17th International Conference on Image Processing, IEEE, Hong Kong.
A good object representation or object descriptor is one of the key issues in object based image analysis. To effectively fuse color and texture as a unified descriptor at object level, this paper presents a novel method for feature fusion. Color histogram and the uniform local binary patterns are extracted from arbitrary-shaped image-objects, and kernel principal component analysis (kernel PCA) is employed to find nonlinear relationships of the extracted color and texture features. The maximum likelihood approach is used to estimate the intrinsic dimensionality, which is then used as a criterion for automatic selection of optimal feature set from the fused feature. The proposed method is evaluated using SVM as the benchmark classifier and is applied to object-based vegetation species classification using high spatial resolution aerial imagery. Experimental results demonstrate that great improvement can be achieved by using proposed feature fusion method.
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|Item Type:||Conference Paper|
|Keywords:||color-texture feature fusion, geographic object-based image analysis (GEOBIA), kernel principal component analysis, local binary patters, vegetation classification|
|Subjects:||Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100)|
|Divisions:||Current > Research Centres > Australian Research Centre for Aerospace Automation
Past > Schools > Computer Science
Past > QUT Faculties & Divisions > Faculty of Built Environment and Engineering
Past > QUT Faculties & Divisions > Faculty of Science and Technology
Past > Schools > School of Engineering Systems
|Copyright Owner:||Copyright 2010 IEEE|
|Deposited On:||20 Dec 2010 03:28|
|Last Modified:||21 Jun 2011 15:02|
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