Multiscale Fourier descriptor for shape classification

The description of object shape is an important characteristic of an image. In image processing and pattern recognition, several different shape descriptors are used. In human visual perception, shapes are processed in multiple resolutions. Therefore, multiscale shape representation is essential in shape based image classification and retrieval. In the description of an object shape, the multiresolution representation provides also additional accuracy to the shape classification. We introduce a new descriptor for shape classification. This descriptor is called the multiscale Fourier descriptor, and it combines the benefits of a Fourier descriptor and multiscale shape representation. This descriptor is formed by applying a Fourier transform to the coefficients of the wavelet transform of the object boundary. In this way, the Fourier descriptor can be presented in multiple resolutions. We performed classification experiments using three image databases. The classification results of our method are compared to those of Fourier descriptors.

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