TY - JOUR
T1 - Hybrid IMM/SVM approach for wavelet-domain probabilistic model based texture classification
AU - Chen, L.
AU - Man, H.
PY - 2005/12
Y1 - 2005/12
N2 - The Fisher kernel method was recently proposed to incorporate probabilistic (generative) models and discriminative methods for pattern recognition. This method uses parameter derivatives of log-likelihood calculated from probabilistic model(s), Fisher scores, to generate statistical feature vectors. It is followed by discriminative classifiers such as support vector machine (SVM) for classification. In this work the authors study the potential of the Fisher kernel method on texture classification. A hybrid system of independent mixture model (IMM) and SVM is introduced to extract and classify statistical texture features in wavelet-domain. Compared to existing methods that apply Bayesian classification based on wavelet domain energy signatures and stand along IMM, the new hybrid IMM/SVM method is able to achieve superior performance. Experimental results are presented to demonstrate the effectiveness of this proposed method.
AB - The Fisher kernel method was recently proposed to incorporate probabilistic (generative) models and discriminative methods for pattern recognition. This method uses parameter derivatives of log-likelihood calculated from probabilistic model(s), Fisher scores, to generate statistical feature vectors. It is followed by discriminative classifiers such as support vector machine (SVM) for classification. In this work the authors study the potential of the Fisher kernel method on texture classification. A hybrid system of independent mixture model (IMM) and SVM is introduced to extract and classify statistical texture features in wavelet-domain. Compared to existing methods that apply Bayesian classification based on wavelet domain energy signatures and stand along IMM, the new hybrid IMM/SVM method is able to achieve superior performance. Experimental results are presented to demonstrate the effectiveness of this proposed method.
UR - http://www.scopus.com/inward/record.url?scp=29144506277&partnerID=8YFLogxK
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U2 - 10.1049/ip-vis:20045030
DO - 10.1049/ip-vis:20045030
M3 - Article
AN - SCOPUS:29144506277
SN - 1350-245X
VL - 152
SP - 724
EP - 730
JO - IEE Proceedings: Vision, Image and Signal Processing
JF - IEE Proceedings: Vision, Image and Signal Processing
IS - 6
ER -