Combination of Wavelet snd SIFT Features for Image Classification Using Trained Gaussion Mixture Model

Abstract

This paper presents an effective combination of Wavelet-based features and SIFT features. For the combined feature patches extracted from images we then adopt the PCA transformation to reduce the dimensionality of their feature vectors. And the reduced vectors are used to train Gaussian Mixture Models (GMMs) in which the mixture weights and Gaussian… (More)
DOI: 10.1109/IIH-MSP.2008.76

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@article{Wang2008CombinationOW, title={Combination of Wavelet snd SIFT Features for Image Classification Using Trained Gaussion Mixture Model}, author={Kejun Wang and Zhen Ren and Xinyan Xiong}, journal={2008 International Conference on Intelligent Information Hiding and Multimedia Signal Processing}, year={2008}, pages={79-82} }