%0 Journal Article
%T Comparative Analysis of Wavelet-Based Scale-Invariant Feature Extraction Using Different Wavelet Bases
%A Joohyun Lim
%A Youngouk Kim
%A Joonki Paik
%J International Journal of Signal Processing, Image Processing and Pattern Recognition
%D 2009
%I SERSC
%X In this paper, we present comparative analysis of scale-invariant feature extraction using different wavelet bases. The main advantage of the wavelet transform is the multi-resolution analysis. Furthermore, wavelets enable localization in both space and frequency domains and high-frequency salient feature detection. Wavelet transforms can use various basis functions. This research aims at comparative analysis of Haar, Daubechies and Gabor wavelets for scale-invariant feature extraction. Experimental results show that Gabor wavelets outperform better than Haar, Daubechies wavelets in the sense of both objective and subjective measures.
%K Haar
%K Daubechies wavelets
%K Gabor wavelets
%K Feature extraction
%K salient feature detection
%U http://www.sersc.org/journals/IJSIP/vol2_no4/3.pdf