An Efficient Shape Representation and Description Technique

In this paper, we present a novel approach to shape representation and description based on the combination of the Hilbert space filling curve and wavelet analysis. Our objective is to capitalize on the localization-preserving nature of the Hilbert space filling curve and the approximation power of the wavelet transform. The object image is scanned using the Hilbert curve and the resulting vector is smoothed using the wavelet transform and sampled. The technique is O(N) for both representation and comparison. We present some experimental results on the MPEG-7 dataset, Kimia-99 dataset, ETH-80 dataset, and a logo dataset.