The USC Andrew and Erna Viterbi School of Engineering USC Signal and Image Processing Institute USC Ming Hsieh Department of Electrical Engineering University of Southern California

Technical Report USC-SIPI-238

“A Wavelet Descriptor of Planar Curves: Theory and Applications”

by Chun-Hsiung Chuang and C.-C. Jay Kuo

August 1993

By using the wavelet transform, we develop a hierarchical planar curve descriptor which decomposes a curve into components of different scales so that the coarsest scale components carry the global approximation information while the finer scale components contain the local detailed information. We show that the wavelet descriptor has many desirable properties such as multiresolution representation, invariance, uniqueness, stability and spatial localization. A deformable wavelet descriptor is also proposed by interpreting the wavelet coefficients as random variables. The application of the wavelet descriptor to character recognition and model-based contour extraction from low SNR images is examined. Numerical experiments are performed to illustrate the performance of the wavelet descriptor.

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