Wavelet Approximation-Based Affine Invariant 2-D Shape Matching and Classification (TP-P4)

Author(s) : Ibrahim El Rube' (University of Waterloo, Canada) Mohamed Kamel (University of Waterloo, Canada) Maher Ahmed (Wilfrid Laurier University, Canada)

Abstract : In this paper, a multiscale algorithm for matching and classifying 2-D shapes is developed. The algorithm uses the 1-D Dyadic Wavelet Transform (DWT) to decompose a shape's boundary into multi-scale levels. Features are extracted by calculating the curve moment invariants of the approximation coefficients. Two different dissimilarities are calculated from the Euclidean distances between the decomposed scale levels of the shapes. Shape clustering is achieved using hierarchical clustering algorithm with ward's linkage rules. The presented algorithm is invariant to affine transformation and to boundary starting point variation. The algorithm is also capable of finding and clustering similar shapes even if there are small deformations between their boundaries.

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