Abstract
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 localigation 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 Daubechies, Haar and Gabor wavelets for scale-invariant feature extraction. Experimental results show that Gabor wavelets outperform better than Daubechies, Haar wavelets in the sense of both objective and subjective measures.
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